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RelatórioFinalMarkdown.html
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RelatórioFinalMarkdown.html
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<meta name="author" content="Maria Elisa Rocha Couto Gomes" />
<title>Lugar de mulher é na cozinha?</title>
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WZWHK5LZgl9279229we2OBUX50kuVjv5QDo7PBwnsvrhWJF%2BYDIuVagZDxeFHOF1MEKbsBMEQS%2BKJjOVdXJ1BKw61EH%2BfeqSTzTz3I7ZA3Zuv%2Bwhshy3sDFL2TjctJR6n2SDsfFJ3A0I5ewXfAgugw7s%2B0XQG0SAfFVWHOEsr6TyphSHW5NHFc9J6Wa%2B7B3Dfp42HguHAUINniPlZCpQ%2Fl0CogDIrW%2F8u85iv7sGv8ZzGzYAxjwV%2FMCxTwobJQCTWU8HRPQeruaaXpRqestVdUOXso7dupeF7px4Z8%2Bed3arKFc44AIg51W9ch4kIIiUEocmSk4sBpCcj15oUDRJXYYExl37RmirrkIv55rLASYJJF%2BS3t0nopeptU%2BE%2BmLrLK%2BlPgQyid3mCBU6UP1rVz8R2n770zc%2FXf7x8s%2FNn9fvaFi3rmFHPfmMLWRP4lycho%2FjNPY4W82Os88wiJ34K4tdAIQjAOQkx8YArcM2PaAOjSZBL8uolzAJFFvGDXd8ej67P2AvKpUkOYghcnK7zl300RBcsExwzJ%2Fhbrd7GuYBwhgAIYtbTx%2F3%2Bd4klJ3gtKCQnGIz9InYZEzqG8EkjSzNavCB%2FcXYlcQshhyMsZrI6PYLWc3lOG%2FvlA4rHr%2F3uTFD3r38%2Fr%2B3fMKOke9W4oJ9G566u7au84CpOz%2Fct5R99wF7W6dIYjjnawrHIAh3hlungFOWgXoyzVKbHOr1eD19Il6vISsrrU8kSzbY%2B0QMGpdjgYh60zDTHJKHoyP4404pw27zB4o1o62gq%2BBLL299am8j%2Bzv774zj995%2FdgTOZsOfWr3rnTWPj2h8qGbo1%2FM%2F%2FkYYvmxfms7TtPrM54E7ns4vwBw0rFy%2FaNJjRRVTet31OgCBPABhongUDOCAzuE0h6gnxChToCJ1ulB0iH0jeqvscFBZotflk%2BhMQ5oJDqhrC%2Fl%2F%2FFxmAUlGYeK5Z6Jl5MDec2yJQdc%2Bl5ViNduL1avoZ805eGll04jy6COKheT8S%2BU6kQwdw%2BlW6nPpXF4qtEoBziwAye3mMnRLkqlPRLqZdQlsKxTcLghkqhzjrLL5M%2BWgUwldSkjbL1HPLrCf51d8MHbv66zu%2FmcGl5Kz0YNZ0%2Bmcf759kbEB29qGGrZiYWop2b2R9fYqnKnlWOVzqXqgNfQIB5LtRr8fQLLT7CyT0ZLaL2K0WFzU5e0TcfmojkckcgvcyhJ4pNlr8Bd63VyEhIbiGhfIBFGTq8R9lqcWB2Dl1G79Rn%2F9i8n08OU3L%2F760UX2E369YuvqVUPrI9VryFR8CXc5V%2FrYefbW7svv%2FYNdxUHv%2FOnFVQ1V8yse2Dde0UcAIY%2FzU4L0sA1FEQg3jJT0jVAJFBlqbOOrALk1dCOmkuHNF%2BmpaKOYunHhldNAlZhEyFGpz4R20C%2Bc47Vmu%2B6gqXo9lewuq5TfXrLnZORk9Ink5JjAlNwvYvJBoF8E5N8qd9nN3jrmj7mOx8OPLDXqolpgwv0zZkpuzaeTynf%2BvWjNvnr22b%2BbsfDJR7%2Be%2BcL6dQ1bXlu3CDvOWfHIMytnrhJPHt7x4L7eg%2F48%2B8C5U0euLuu%2Ff8ozr1xteHTRssdGru8V3kwfeHTMsN937%2FzksLEzFdlO5NQpNsMLWdAtnJlizzQYAAQu26AljUvWZbEQlyuJi1Ymcr8Iaal2jjKNg5qJ9Ctqx02jMyDFKHJw8TpUIvjHKhXZQlZ0%2FIwe1eO%2B%2B6%2FRVHpg2mv%2FuPbBuguPMtfKLU%2BtuXfjkIFraEVzg2tlMuZg6O57%2FvXBP1C3kZ3H9od2PPV81RMVE%2FaNAy3HEcaokRS34Ta%2BLAA8XotzQMRiizkRDVfN87X0JXae6NzkVR6Znehb6J8XL%2BY3IKovXMjn0oEDMrkmmc2iXu9yGm0DIkab6hgTZklwj%2FT6FDccpXsmn6Rjlxv%2BknyrTFMR8%2BU%2FcF9%2BDiRwh%2FUCiChwdeXD58cDhSwsRjeikNNcTo83%2F0AtP2DDKLywji1nhxSezMTjgo9eVHOy3LBbJgIQ0OsEsToiIFRHrIjI4wHOlfxEz6a4ZOTXTLq9eTjdTofW1bEH6up%2Bg5GIBDhGEr2BkRNVlMZTa%2FP3HKVyrMMKrF3H%2FKPYUAWjlGsXaRnXrxTIhrJwqp%2FbMtnphFYWIdgGoLWtddqASGuPzdA7YhNaqFZLvVJSEa48LZwUd4YSN4mJ%2Baq%2FctSSXgtmD6gf2emV91%2F9KNj38bHd9l3PX0tq19dMnzFw3OSsgsWjj%2BzqPXn0w4On3e9nZ%2BNJLYFZ1yqkQ2ITFEM5zzwyA%2B1KLJ1kVwpAjsvSTgx3S%2BrQQeiisxv5Ky%2B9kGbnqUmllmSFEhOP6%2FG4ug6C2nJQUPdSt0td36R1IFMgbsUalrqlQAbw4KK1v1BwIH%2FudKqm8NCQbeMHP2LUtVk3rv7Fb4712N3Tt%2FDeaWvZt3%2B8wA7swe6Y%2F5cvjv3I1rHJn%2BAyhLM44ODVn14%2F7bBUDpq%2Fhpxb8c388XfdM%2BrU3veu%2BTws17Pv7O79aFvzMnvxc3aaHRq8sAZX4jgUsP7CfvYntoNhGYquJiAAAKJNPAIyWLjk0ojFqENR0SwqyILNaiG9I0bRYhFECoKD518xh6iplZYz%2B5W8H0OIlBsz%2FtURB6IHmnaT7itJORvb6A94cnbjGZYvHrnSg0zENwfPGTGddQIKJwCEo9xyW8ALGdA7nO0UUg1Wn89iEGQLjwd01iRrUlXEarWAxVcVsTjAWxUBevt4QnM9%2FgxBMbluwe4SAjxpj%2FmcgN0ef3cCt2IAhVVLsR%2F7%2BTIjjZjU9PTeY1ew4I9%2FOvhn8cCeI%2FNf9BnK2Pk3%2FkZ7TF00%2B6HoquhndauXPAGAMIdb09Oqr8gOu6jFpbdQb5IDekccglHi%2FHK2DL%2B4emRymUNIE3%2BRo3WokKfbtNP37Cs0%2F7rxjQ0X2Cvs2Rex%2FNNLuysbxBB7lX3FPmdvl64rwyU44QusOVSzuj8AUTgmDuEc04FdsYcWQQ8COJyiuSoiUsFSFREct4ppwc9rSBlA%2BZuAPZTBx2Az2Uo2CY%2FhIHysic%2F1z59PI%2FdU5CtWz%2BaJB9gi9gKmYebVKZgHgMq89Bc%2Br1GJWSSDAQXQoWAyS%2FreEUlCQsTeEUKRr3B03DZmUZBwxy%2F6S%2FMZmh%2BdTYZHt5OF4oH1LKc%2BeilhJj0UhpMlAKQ6pAbjTRPxSW45Q0CbAac3asPzwaNfrY9LTuyi2ilOhUvnI8SSohNapUJK7wiAaDLZe0dMgujtHRGdt4%2B8%2FHaphRyV9%2Brq5lT1xe9nfPc0a2IrDuKQL%2F%2F9bve3DrL%2Fso%2FQj0kbVrGXCYuWZWXjUhzzD7xn%2F%2BD6GvYau8Q%2BZe8H8LUY7WK6yuVQ2KdHBJ0giCCaTTraO6LTiQaJoshJV81RgnG%2FQbydi5f%2FDYnpjc2ssZGSRrI3Ws1z7dXkYQC8NoLNxfFqVpwaNht1OotVT4GzFDJj9GrpGI15%2BJJiPpxLMg0v6dVv9AONx9jclFWuR6fyFGvI0TNxvRC%2BUjHmnkjBViRGg4Ix0Yn6RGzLWkgJZRVRDKHw1TvRrzc2NpL1J6JN5M0l0dc5snnk4%2BjCBF0QIT1soQCCJCMFzgtw3EBXxTekkO0%2B0aio0pV%2FbIp9V%2BKIgpPrUZJOFCUev%2FJSmsuNBjuVjDK1gKQgp2DnLbuZlRjwuJUAn2MY4nce4COtZjadZSsCntbhh6zRomMm0bbpo%2Bbh4oGrVQLPOume7Uev%2FBCXo1IDsUG7sFsvcaytVpDB7jBS2aqjKCdypaUI4xPzabNJKZdj%2BWvNn%2BtsW4%2FRVB2xkGeEk582NR%2FnE3ZMwaxy2guAqFp99FZ5bu%2BIXqDW3hHqvLVNiOltBiTmueJRtpW9oZgjHIE9sBOOujo9%2Bv1%2Ffvn5h%2F9Eeb77LHuYa%2B94HIt1bArbxs6yU1iIuRjEAnYqZp%2BE8erqdUBRONnA%2Bc75DE6XQaiKGAySLDuqIjKVEtavhpXmSgW%2FmlplYChutYXx7Ay7tLsRZ5PWUePGL949euKoYPr7t1HOh2jK6mdXrVC5wHaoXLBCCp%2BZp8MeAIEa%2BOqmZtns6x0xC7KTL2yZM%2BMtlRs3J6I2pViG8q258sX7OOxndrH0tpz5ki3rzuqxivyf%2FDnN%2BWMCN1SGs8yIxKS3y0aDQdYTwePVm8EMVRGzmVDK5UepkSi6cntnp2Ku8ktw20SOf5bGNm4BcRXyGdhfcfkJ9jQ7%2FVXTzl2vfEZGRLeJB94%2Fzf4%2BLjqZjFi9cuWqJwDVHIFw29ha4V6a0wSQ5BSFrGxTGvV4uH30CFSfoEoJiY4mt0CGlozy8D%2Bo5jgx%2B6jmBbwy4BEI%2B9d3rHnZ0I%2FGN%2B7usnL1ey%2BxM389WLx%2F1%2BINHRbWXfoDLjz%2B6Z07su%2BYN73vyIFFvd959sV3qtf2nfFA35F3FQw8AoDgABCGcv7JvJ7iABSRUp1epgK3CYLmFeJ5qGYSi7k3IEsbWYFQyQrE9PWqJzjM14yPj2OHrLDdhgYZZafDrqOCmQ8UpzGUuFzsLkUnVHMYs4uij%2F2F%2FcJfFxrfee3ld8QDzf2vsC8wo5nuaa44%2BMabh%2BghQAAA4XW1%2FpMcNqJgMuooCJQqiPLlrxWvQhjgF8%2F%2FSgXTwej3O6M%2FNmF1x8zWHdVaFh%2F5uU3bnwXkmg1yXz6aT6km%2BQwpyW6LRdQn2Q0U9TGTotqUGOKqNclWAjJldKcyenwSZ0h8cyc75y5CT3v2xU42u%2BnL9p6UYpSa0Nne7yy%2B1EQ%2F7PaW6%2Fdbm0N88llHNx18ic5qnrv59RXv0YUK93QAQr1q9QNhhyCJ3ORLiskXFJMvtDT5KhocAz63Yu7rj%2FPIY0oTXmKdjuAkfHg%2F60QWROeQZnI4%2Bgq5M9oX4lybrUY5GWGrIBJRpnoDiChTUeOcJmE%2BqKL%2BGCJdcNEhlrSb%2BQ6T8%2BR887zoCZJPFyv1ZQBBscZ6pWKmQyqDLKBgMIoCNwcUdUrMcuuKmVot8AvlzU6qi9roq82%2F0LSFwoaNC69OAIQGdoRMVnSRY2mRUFAYoxcJlTDIOdBSfeJRD5nMSvEEu4B%2BdkS6svyKX6HWC0A%2Bi1c2Kd5c2XRy3h0mgYbo%2F4spg%2FKNEDuCzdrMFFACSacHOUgFevPMXj5rMb9CfMoLfOrSA%2BKF5b9KyigFJCgExOMgQVJYD1TWiQQEwrO%2BG5rpVFUTC3DfaPxsA1vG9pEg3dQ8jnwV9QJea2Zv0k3XKtUKsJLHIlEqwBgjmU%2FLQUfRp9mbCwCxTjhHHZIf9OA8AILRID2BkJ%2Bs1ZoxwDW1OMStBHU83G1fm5MZ0%2B4QzhUdK3f33F8MRKk50lPCUEXzoVc4K1NnTEvz%2BRw6yqMpYkzrFSFGI7jd1ooIt4LJFRHRA24o%2F98LVH4tX7NllapJZ7zS6LZn8QVeLKsVKjrQrxv43GPPvUychyc%2FVveH0F3HR77xCrNs%2FmPDWy89tOWB3js3Y1%2Bb1GPe7Jq5dxTuORZ11TZuHC3LD00fOhwI7OVWtVZygRPSeVUt0%2BD1Wq2mVGqiGX4zmNwOu8HOhccRljzgqoiArYV5DSXF1SDB1sddEk825YBijeRQiVcrvHAqyJ5Pv%2F3%2Bk0l%2F7GwKzGzQ6Wa811i%2FqXFjfb0wlJ1jP%2FDXxwMGLpdcbNHcsTuWvv7ll29fOPPJXwAQpnMOLxWGxbIaK6VuPU3ySmaOmQ0cHDPPzVmNGM9qlJ1DHgNzu6hmOGTcZXYV9f8d8HTbUOn8QrbvuW11Tz3swiw0oRPvyPQu96Sywe9%2B2mlNGRBlVqGU88fB%2BdM97E%2BVvGCx2CV7ht%2FhtgIgmqhez9mjt1FnRYR6bscerSYTkLTqvTcUDPLPA6osi%2BJOiG7ST%2F%2Fn2W%2B%2F%2B%2BTCTLMsNCxmTzdu3Ny4evOmNS9gNlr5647tA%2Frh0V%2B%2Fmfny%2B4Gv3r54%2Bi%2BfxLF0cN44IRk6hdOTDF4jpdzqtkrxGit4uRskyaUyyqIw6paZQyiRZQ632%2B%2BJsUuivNbh53Kb%2Bx%2F2JYp%2Fe%2F%2B7qFl8eecf%2FzBk65bfb7WQLstc2AZl1GMH9v3fJxx%2Fp2pttp%2F%2Bc%2FeGrS8oUksFoBYpHVxK3cVlMjkJ4UaSuj0GvhQMgKIsVkScspUqq0GtY98IAxWmOZS1p2QNgeJSXkPW3DX3mE%2BzrxreeANH3lObN6LH8KHopW83l9G3%2B3TugmsDC9PnPNkLgEKQuYQCzplcKIVu8HC4a56vQ5YpvYtY4ESnSHIzW6Vn%2BQzd72xlLbYWV0R0nXpFDJm6XKvOqvPk5pJekVxrm%2FJekTY2T7teEU9KnHUa%2Bzj%2F8pXd%2BrzbxD1uragaVBdAqDC%2BjaAUkrJv%2FOXKcGMXmJOnbhQXF%2FF3QsHJVnf87VhB3sSqoa%2Fte5X9jf3r7FdPzMgtC%2FccNOnTtwb3ZPb6ZWdOPLzh7amPD50%2F4z8%2F1T4uVE5ICkzt9ewxXYdBbfPqVx54ddvqMauTndXFnYfmBnY%2B2PS66ypEhs2ZFOn5IO08%2FZFvfn4cEPYCCD24nnuUzM5i0nFz7dF7vEkWvcMhVEQcNgOA3q0Y7xjlCatesVT2mALbtRUfM1P06cfm%2F%2BGZhgadoWD%2FjBMnyJuLfn%2Fkk%2BjrfHXnDOow4N5XP4gWAxDYDoDjxAtAwcr9tZ3PJCDa7Ga5MmImVlQ04%2F3EwqZSIqAJJVQc3NDQ1CG3TceObXI7CJWYU1Zc0qFDaSkAubaKudSxTZAEd4Q9TqPRrNP5kj22yognrLcC1z6ISzW5xSTOhATTljhb3v2det7Zv%2FeNGZnLt9g16B6h%2BaqNHZHv0yaP8TSV89QGJTzetxgMRqNOEkSdYHeYAGw2nY7KRje1xiKGfD5zeUyFyuJsRTUiQi0bdclYkzcER73JeuD5E2zOnB07dKSgy2icydpGlxLpQTZOcjW%2FXTo9NjcO5nNT4GQCoiASQHfca2tMVBjHYVRo6SRfJQGoCAfcdruDiz%2BgdwRo66xWHrfb4RPMPm5p0302p1UPDkUPuCLEt534Igi1bHVIVIgEzfAqepHh1bRDypryyOa1DVNmblnVsDhFl79rIuIAXcHhmYdfJicWLNj3cnSLcv%2Fzx9HjQmV99dDDg8e8%2BheuMZq2cnxdUBBOApeiri69x23S22xcWW02g%2FV2ytpSV72Jmrp7m4JG6NDUt95RNPXwJ%2Bq8d0XUSWM2dhSfU9EknsU6wSyDnOwzeLgds1GbYvxvmcVylSHFilGFxE4PYRT74fKaf%2FwOTZcvobX5lZ3PPffii88%2F10Cy2I%2FswyeR%2FAFNmMfeZ1f%2F8rfzH545p1j5vdyW1apU%2B6E8nOEzCrKsS3foHJkBwQhWq7siYrXprboUaHXDzMdZ0GLBqpaeO2hPAhMUr62Y%2BgRHrThpU8Niry7c%2BPBf%2F%2Bf7yzvryabGFc8%2B6xowcMRg1kUqqh9azT5h%2F1GcNr14%2BGTWl29fevfUeYVXHNNSlVexqMKW6qHJyT6bL8OfnOK1pqalecxOp8wtv80MFRHz%2F%2BY2VT5yJ1l63Ul6r3vQ0njtQyL9GzaIW15cvXnjnI8uf%2FfJ57P0SQsajObpM%2Fd9mHXp3YunT59birloRDO2a6z%2F9T38eEzFCzE9okGOpw1ywy6zXm8wEF4DsZrB4FYtg03rc2nRkaE5IY15ZEfvjt4eRQtfaahz6rrsFoaZNlk%2FfTbaJFSenDQjlrnS6XyW1twOtIplrqLzeuZaEfHYJKq%2Frj%2F5t8pdueG5kbsG25Hfpq50%2Bj%2Fe%2F%2BtjA%2FbXzF82%2BdmN88r%2FevSPL3Z6ftEjj7Yds%2BJ13jSzsaHnpjbt7h4Uvrdr2aAH%2ByzaXLm4R1W3O7p2KO71FCCkX%2FuG7BQrwKPWJlwu3jPioEKS1%2BC0OXtFLGGbVeaCkj1xU3kqIVjV5ONWqo52xVGXhtxKNuHyEMcdA5NSJuSy17ZurRiBXdlrw2vN8lyzHQeQZdU9%2F83mRWePngiAsIOvrjKhElx8fh86ZZPJ4DS4PSaz2aZzWdVV7TFqEbMS%2F4daVmW0rJcrhBY127EvX9TPNNQl6UP7Z7zztlAZLeMO6GMSvnpozV2Dj54hp7RcjgiVau%2BHAQ0ms6hHK6jhiJZl%2BNX0NFTicIYQt7ER%2B76ptuiMte%2FtYyP4oI%2F8o0cx9iPtrx6K5UpSgI%2FWinsblz4lNc3rsZipYBZ0yQ7ubnTuxCyYK7c2A1U2Z2Rlk8LhUHSq1BmbsoRPKeSfcBbp2qSdPsY%2B3jNxsk5nLHCcaHqjg0snBF7dzc6QBZ3OvHR%2FdK5QyUaz6j5l%2B4tJbXTp7trW9eRvHClACAIIOpXGzLBdFiVAUWlxQZ3RLaD1pnQ4ngmjmhUfYgteQT9m%2FJktwFVH2Cn27hFSQLxsGO6IfhU9jUdYD0AgfL1LfHw3z%2FsVMqnHK5jB7OBLO0UHfIJCVam1GRJo46KKOdrSUrLvuwFOnfnuS%2FtYTsWfl%2FStKu2xq3cXzuCVn9wf%2Bpn87mrGy5vtC03HtkAsZ6YPCZW3yJl7RUQr6npF0P2%2F5cz0oeZ%2FksHR0%2BTL6D5y31Q6eN685sPxrixetlPl5%2FYlJxu9AFbZRbmnpqlpTq09K3F7TdV%2FbpXcPJZTfEtxCddDvj7d3EK4ZLfHjedrpx794PFH58%2F49MClCxdM44aRZaRxE%2BaPjywnw0Zg4ebdS6Xj7NzZoCl4FhAvMxuZrfluorSo0RSABN%2BtlHzx8nKeJv3cDAiV7Ijaw5Oq4OwWDQ4H8UFqqsXiE2laujso0QScEzYFFXSDxYr7U7DPVNCV5Dj2pcRw4eKhDx%2BZ%2F9jjp45OnvHwVFIePIvB49LSPRvZ%2ByPvJcsjvOq5cRenZNg4zJn2qEvdpyXVQg6tAS%2FXAzu1JvkcpuoIdVglCaojEuTngS3pjfw38rSkOlOZT8nQVNOmbD9lKoU5HFg8t2TMUz2mRrqPyi95omTcisrHK%2FsMJSfuLFn%2FUKvsVinhsvqH%2FRkZSeoOPFuKdcJwrcuYCALV8343AGpSu4xtNPOWXcZcCQNO1%2FXt0PNKk%2FGszp3Ly0IVZPfVC2Lfxb3C5ZVhQDjK7fd5dVemazjNozNTahCARxo62irVJxKnwUz4SzDKgg%2B07k9ljt9sw2apra1KOJCldLR6NAOuqD89OWHNwpPHcdniPisKChY%2BtHv7My8sX%2FFdifTO%2Bxlov4LNXXfvoH7vstCH5z462QkQypUYSDzBpV4Zzk5y6s3mZI%2BdGD1OMS3dlORL6h%2FR%2B3xOcNr6RpxJIPa5uRWkRdPQzZ6Nm29lf5Lfinl2ypuduEqQxqONXTatnD0HG9jQblU05erVU2%2B99f%2FEEzUL%2B%2F1uGTs397MxS%2B7YtDz%2FxwtzsfO%2BU4psZqMkeIVtnHNByAibW0GmBSxtctLd7iwZeNSYn1gJchaVBku9il8r9co82Ja9clCxDnKwNLs0IXQ6VLV4%2BOLx8%2BeOq7t%2FUVXVgmF14%2BYuGrN42MKqeVtnzHh627QZW8mHj01aNmxh794Lhz059ZEFD%2FCHvfj7JZN%2BN2XbM1Onbd8BiscDEJT9Fw8MDrdzWGSj0WYS9URPTS6LW%2FYmGSwW2So5HBScbqsz3UmsTqvThG7JlATlWg%2B33RHrzL7lpjuGUOGj1uaovjBEKnH2HjYCJfY6dmGv72BvYGd%2BARu7j1wgZ5vZ3Ma57Ec08RslQBKsgaxUVYkkUR726QUqUDlmFjgmiYqtbgjFLYRiI5p%2FYebmnxVpXPuF1kupUABdeGdcdiE4pdy0Dj5fmkmCgNS13E07lbRqK%2Fn1%2FmCviN%2Btt%2FWK6OGGznh%2Fs4t9I39VVFmLztSUlwuwZdCiRC2l%2FKk33lG0dHD%2FqprTbw5%2FZmTxqMV9Z8yYvelw%2FcCqjf%2F%2B6K9P9H9t4KLl7R%2BcvmJR99W%2Ff6Ggbs3LPQbRnMF1WW0mD5q1NDW4IJjSKdy5prTH%2BklDl%2BfctXrZxm5rs9r27dWuY8e8oqHTRvWb0MVZPfnuKWXOMUCwWLTQ8eKH6u5TWpiTanKAI8lnpW495N90QCAhzctKeI%2FFxVnZpaXZWcU4pzgrq7Q0K6tYnFrUrl1RYUFBYfwOQGEM7xzvEdt5hxKeSwWDXmrNT0936a1esbSDZAKH1ZRuIuCwOYjJYXKk5AWcoRQByhNPBdhblgFRMxHuG90bnN2obu8KDjc3eYHM1py5DiFU2NqhNXTQOXMWz10weE77sRWvffDZq0880vHB5vXv4PB3les1tv2D02z76xP2YNvdezD3pT3s7N497JOXhMCeTTu3t%2F2dq9X3n575qfMjIXZI%2FQ7b%2Fu6brOGD0zj0rT%2BwD%2F%2BwB3P2xr8GQKCCushU8W1OdzqUhlt5pRQDokeJazP8rQwGh88D1EYJNTvSOakf3feGku9qVGpqG4xTV8ojfbXWGSt18iYUtdZJXEnDlt0%2FedPztWvHjM%2BbtnB%2BHauecmLUlAeov2bk6HHjJkhCcGFoRIcJs1jnI2OaCgRBqd8NhFraSI%2BCBGbICTupxI21YNTrBbMkWKwmUYegHGS5WbPRiyhjVuw2EAfPVEriM1kjLsUhtexzTK9lO0kQ1%2Fdk29mzvXB9yo23qh9EHfeDXhAhJWwiKKAki0J1RCSQr20nattixUJOXfM71Bv9Hhc%2BCdeuaV3LRAIbAAjXdUoX16r7wqGgF3iOLui5Zpn1JodXKu1gsnFoi9Pi0DmtjnQHAR63E4fT4bythikCCP22ZKVVoUS%2Bhp0Bqm51Fnr%2BL2UjHz5YPXLwfRNx36B%2Bl3eeXrwWxYbNVy%2F8n%2BpGrtwd7tNtSfXsNFaLo9jTdPZ89ub%2FpXB47YrkEiRpzW3r%2BoJ09UfBJLnmAoG5dBi5LJ5U83Z%2F2GIGp7L7nGwzHPNQhS3J7yWaAKe27LkytvA6c%2FfPn39g4Oqa%2Bfun195VPX3qwLunC2vmH9i%2FoGZlTdOCgdOm3l0zdZoiv%2FGASic8yQYLAMhwBiA6Q93NqCLLub9OUmpcstOLaHGCwAsItnQvZqjyadHEUVx6cz%2B0JMt%2Bsjy645vIQH91edGont0XbPj9msiaPXiIVI2%2FNHhk35IePbMLh0yeP6V6%2FZPPA4KflKlzBqAsnGkVRaCONIPUOstxn%2FMhJ%2BnrRKMzxUmcTl2yP92s88eVhKvIfTe2KDHRmKtlyd%2F2PpPpA3vsPbRzw4w1sz%2F8snbmA6Or7%2Bw%2BpUPP8mXDl2wVvqx%2BwJu%2F%2FYmVHWb32L5q0oAeXXrkBYa2LZl5056LnkfvwhP6xD0X5YAIN3pyAOvaT85494494cnCD133dnN3O1oEqNZDegiV4IHicLJoMOhs4HS6dC6%2BLeC2ulLMRKks6LWkMWHX6XqfaELKyMnTOhsGs13PNCxJNkz%2BZ%2F0Qg6GhAeewK698pKaNLwyr2caOScrsU1mzMEJygRWCYYcgIoBopDa7TidSq4jaQa%2F8RJkG7MortqVTEvILI6Z9PL1rzacn%2F%2Fov0pY1S3t%2FraYhx5WrKDBA2ED6Yh0dqvitsEECMJuofkCEQsyAJOqq2jzatUOseZR82L1nz%2B7xMwlZzIVNAOBQIge7xQhgUfrILXa7jtog%2F71CzQq3qDNoZYbSkOzBpo31obZtOw24a8BDQx4ubWIXRk7UT9S1Kckrtu%2BbHgSEvqQKP1d3kPleHwFKDSZuX2mGBGlK3sc5EGO7FpnEzw8MXLlQ8pQsvpNv4K4ld9471NP2%2FhFAoDt1kaPi26q3zgo7lONnEnBvHfMfbr3iP964r4XTTjgzJSYsWHJ0V%2F3qF3eu3%2FB8lN07fsKwYRMeGCZM3nHw8LPP7T%2Bw%2FTH%2Bb%2FYjjwCBau4hdsY9BF%2BZRr1AgMrEoJdu5R%2F4fBhELEUxdqM72c5aTGef1%2BIQVnvjPTGxCb3wfhzek01IufGW24c%2BAOIZzq8gnCYLACAbHrsGKMNHNDV6EPR%2FosTBA8ziYuCw7Tjs%2BThseQz2CwV2Ou3PYeV9xMZBVchkAMkvnuAQM34FFf4CxEZ9KD5qXmxUIBBiM2mNMBxSoY3Sba1zpQWwlbVVwCXk5EIqmmhqKj93lzEgkm2zG3tH7IEWecP9w%2B9rGZ4ohslCYnXDUm9MGF2J0ihbnJBfkf59Rs7q4vv9Y9X1ozq9%2BdbRTwPhSMnYbk2zOnXtXqqkXKHH1tZM7NOvw5ip2e0XjzjcWDEhMjB%2FyIz70jFvcU%2FeGRvmVKrdoPJ0bltbq9R1v%2FYaDgTdn4hNzIa84ltA1MLCGETS7SCOQSAGkdoSIv86xGsg3HKMrOsQE6CUQxiaKGmtgtyAkWIwIMNxKIN5QK4xAIk3MIIVnNA%2FfAdPM%2BwIOhPaRNEtuvROycm7kHm7iMHM7wabASUqOtByowkglmHm5an5G8bOiYau9y%2FSAF7vYVQ2zqR5UUeUXdxLDtMT0SMkNXqR9Lhag0cfURpetbZG%2FAvZr2jRHOZSOkc5ztkqzrMIAf55rM9N5VmbON8PqhxBs8aRmyFqoTwG4b4dxLFrV2MQyS0hsq5DTACHylWC%2FhhXgUA%2BgFip9id54Z5wod3t1glmAKcgCUk%2BrogS11erXC6%2FJJ%2BWL8jcIsuyoNfbqiJ6Kri17tNEXW55EDWhHZV7uVhLarxnM5QhVqpNqbM3bcJ9eBf%2Bbn%2F07S9xNlt4lIyKtaWSunqyntWxHSQcba5nhhhNYrmqS%2B3jurSmJdWx7jiVLwUx3sKsmLb5bgdRi4YYhP92EMegKQaR3RIiX4PgeGy65RhZ1yEmwMdxnW4b5z7CQrQJJmEDGMEX1st6ino0mXXgy0%2B0x2rMHLeOu0ewbTh8BHua7RiLw9m2MThS2DCa%2F3fbaLyfPTsaR%2BCIsWwrAOXzv877434CJ6RAQFkZnnRvmsAPExtcAA6rqFMCF0%2Ba32f2945YHTpRoDazQHnjnES1lrm3%2BFq4%2BYgL%2Fygm0lglwc7fxSoM1BZEj3qKzovZ1zsLv1479tEH9ykddGe2jnx04rGmh6Mjpu%2F9zy%2FNwbFk68SdWpPhmOUDNr2FDyl9dMMXV699l61D26bmvgOVZjp2ZRN9qTc7xVdOrI9LlUxpXLoVMfk7Nb7fDFELp2MQKbeDOAZzYhAZLSGyrkNMgA3xlRNMtEfCbHWUTvF5CmKjOFSQeO%2FfrHjvH9%2BpMOtFUbKDBB6vWeALiC8fs96sl2LdkZoVarkRrHVH8v9lCDcaJGexM%2BzzQ42NZ9GHnuYrO3mL5LvvUdvFy4zXWq%2FB6ei%2FV%2B5Y9yQAqv0oW6R0aK94ppxcMTUAXpMJUu25YkGhw5Hbrl12RaQd5LrV3S5tj%2Bvm0xpaZCBL2vZIQjWCo6Q2%2F2lnOTKUqE%2F1UYJv5ZAOKb36Lxv32p%2BOTCrfUnn27ofnjujZq094yVz2TcPf%2Fv7%2B58IPi6dX3OnPyC0L3b917LZdPTcF8w%2F0mVQxcHZN%2BcTisqHF1YMuXO0r7Nv3562c52pXkOTnPL8TACXovgLUVWlXOH6L57V56vN2t3t%2B7FP1eajFc%2FGz689fe%2BUW3xc%2FvP58whegruiOKsCNGRZehzj%2BcwyiTQwCqAIhKbtXOVDENWdkOJQLre3tedlIaF%2BWlJTe3ghi5y4pbYNtKyK%2BAqGgV6RD66BdECyZQU%2BxzqKriLgsNtBaO9R97viBxZsNL1corarUot3Jy%2F%2BqHSkOv7bLFExMz5TiAMaaVIb%2Fwg7NmPnUc0VVb4%2Ba%2F3xO8a6Hj%2F0reqcOO967tWbwurHswpy73lz03Mt7Jg1ZtfPpwzvoK7OWGon8BOY%2F%2ByddrEUqp%2Fie%2B4eMYP%2F9%2ByRWGwjyVpav5k5sXH9%2F5MVNo2XdQ6Sw4ektO5V1zXc4lW4kzreeMU%2BJFaqnVDtxVIn1ikl8vyqRVppEbn5e21993vp2z4%2F9rD7PafGcS1R7PsEQk1d7TaLX%2FgqAo9URXolZHHYXKGOgqI3xIgApTICovZYRgzDHIa79iUMMSoA4xl6IQTg0iG84RDrHQ4OYwA4CqBbHZ9d89VRlx1zyq6euqsJ5fsnUqhXwYN5jsTttkj7YRp9eETFSj91nsfLIR0%2B9LqSttY3QmLJw6%2F3b430QyITiIlAqxdlBMcj%2FlHpUk%2B6gRVqnV4kwil39%2Be%2FsK5T%2F9sUYXdkp9n3vr4YN77ll3OW%2Bpzc8v7NpC3vppe0vPUtC7Ev2FzR%2FcQmlWcInr25%2BcGHXgtrefZ6cNHMlm8b%2BtaaRbXjh4Aku21jXgbraqmOrzaLyJC1RNqNUrt0Vk%2F1HquySb%2Fe8drD6PPN2z4%2Bp45Ngi%2Bd8fu35a9%2Ff4vtcJtrzCSkx3Wh3fS2Ph2YhR9gJVO1CD4WTPAaDTSACKjsZTifKZjMqJ%2FQQ8tX1yhOfG8nPjUN6iccXE96Pp8ejezqVFHXsFCrqot3J8iefZP%2Fq3KW8Y1m4nPwYfwOUY3tEGCUsjvv7PvxEa3orl8vQ6iZn76u47uxt1M%2Bb2Kjnf3P2ZWVxBdGcfXw7QXSpTl4Si1SnX6L2X2yaUjNt%2BDw0Xd40o6Z25NzmV4rxTJ9pvAljfYjl95r63Iuxboyetf0XbEBQGjL6zuy7cMOvu8aRRcWffLRjTHRO6DzXjNjutSq5e2KSf0PVDI8mmZuf107VNOfWz4851OeBFs%2B5ZLXnE%2FyxtZarrfrYDqw6wr2xGWIjpKsAWu%2BI2t%2BVyXex0jOkFJfNZpfsrQMOsKeYPHqqT%2BNdjB7q5euvRZPnb3oYUWsXUUomXo%2FW9JUVbx7J4HugOKR748Sz333%2Fyd8fMwk63mSElTs38OYRzF9LmyID2Efsvwpjn83sV86KdcDaFQ1NOXQi58u3ce%2FZMxo1nF6Nmgn7Y%2FTmxejV%2BpuEyuv9TaJArLfsb%2BIw6gkU6UvxFLggHe4Ot0uSrE5nKpjtqZKY4bc6eDxpBaOR51hGGj%2BVwg8UUAc4b5zk4det2ia1fWVJO2TlvZF9aafq7NnSl1EYN4y9zJ7BYRgeN5RaonxdR8%2BRfs09fmXXEH%2Becs89LqzDiTgeF3ljSZmwlZ1m55QTGn6hNi32qy1yujAU0iAXCmBQuG26zkI8nqx8t7tVlk4oDOW1Mbbh0RHvSCKixdiunWg32pIyxcyKCIieFj7YoVjVRAeseV9R9a0q5rdyvYktTFkxnyvWs%2FNzup6pu8B%2BROnrBae6djz2%2BInL0aAOq4Y%2Fe8%2BQDVf9G154buPm5xvWCb3mrjKRjN%2B7vp4xEwtQh3q8Y%2Ba0KbPYz19MYDO5tw1mkLIPz3985rOPP%2F10x9NP7wBEE68Q7pH8YFF6wGWwWXmN0KJs3CSfKkwsE%2FIgzx1QzhIE0DR3nLfB89CcmUMWLuFF2u%2BWPJGTu3C%2Bt3TBoiIAgpP5iG2lhdp%2BkEMyxSpMejflw753u9KSrHUfcfpp29njxj46a8zY3z3YPRTq3rmsqJu4b9TM2lGjps8c3qFLlw78AkQdn%2Bk78TN1N5wPn%2BSzg2gC%2FnKrZc73En4mKLYb3o4vKU6BwvQ0olRTQpJEXXkDB%2FTOLAxZRpmn39tucP%2FKjIL21tHmqcL5rLZZnbvMquO3Tl1n1aldEci5Ff%2FFEyCCePMvngykw%2BK%2FeMIh5f8VUtYgffQ49lB7%2BR0HUNTpQenhP6WBBkscHEs5y%2BQZ1WF29yx63DMUTVyicNM3RdTpRZly061Rq55Od5RisXIk%2FbGKDPGARzmLjqmfcouq%2Fe4LkcAKAEQZizSpY1khOWwS0KwXbHbQUZP2M1%2Bx3pUgbyrhA%2FvjeGG9tcNjs9M6maNnb2B4FnXTeR1Tw7TF6DZldL0ZRcHuMIs2WRn9LW10DWe%2Fei9JQJ4ELUkjOsxJ7m6%2BQYbnXvbTY2Ow6D6FHh%2F7lTTBZZSVLOtqB8g4iCCHzeZK%2BdC1Y38ymWJ3vb5SBnteXszG7cAfyXB6EYzgPBD%2FURrIP3Wr6u%2BOqQ9OmDF94qRp5JtZj%2F9u9sx5C%2Ficym8TiHvgB8gGOwAEwU4c%2FM4nELJA1RaoJelK5ZPTbBAIlYikk0WuCInpvPM3e2CJ%2B16ASv2UpGqjUBAIkMRRWhRNSeqtK6QAyGYBkJXxUyYgEkE7ZYLxAQJIVjbPWkkXx4%2BZIJRzr1gnnuT0TQ2Xp3rTPZ5kI5Hl5NZ2wZDslYJtjN4kb%2F%2BILklMTUvtHyFp1rT0tPw0qqdJaUlpzsxM6BvJlJ0W3iDhg5ZN3bwwdMsfKruRW2ZQbuRlt9evdcorVpPyolGwuJT%2FdUDsCHUKOz4AWfRHQvA065Z1snHLxtW7%2FoddaNewgZANO4LY%2Bn9OPN%2BrQSxmD80rC7ed1%2FRm9%2FpuaEacl3tH9TwUsfXIpYPVzprl6o4iBXdYT0AUtDAtYc3y%2BEuJtrjkUwGEVlI650ylKvE%2B5ABA%2FHNTwuf9lc%2BBgItUcf0%2FAgZwQedwuks0ypTyaYjSqY%2BiqLe60l3E5aIWOZ1mxPuV70toergeGwR4g0v8V2eKi0otVJZJ05xV7GHcsHQO%2B0ESk9LSjDup6913x%2FKzVKdeX9THFGzb1v5TDDfpQ45bECoJ9%2B43cBcf0nCXXr%2FF8%2F43notvxJ6rVEnqc1TWG05X9cp%2BAAQRKWiHl2Knck80KgqljCAC4Aq1QvJpPHP6XaxCImp1FiUv6pwAUXstt2Ud9NrbHGJCAsQx9ufEKktsFtJBzroOMYF9EK%2FV%2BGK1mv8PflNJUQAAAAABAAAAARmahXJJOF8PPPUACQgAAAAAAMk1MYsAAAAAyehMTPua%2FdUJoghiAAAACQACAAAAAAAAeAFjYGRg4Oj9u4KBgXPN71n%2FqjkXAUVQwU0Ap6sHhAB4AW2SA6wYQRRF786%2B2d3atm3b9ldQ27atsG6D2mFt2zaC2ra2d%2FYbSU7u6C3OG7mIowAgGQFlKIBldiXM1CVQQRZiurMEffRtDLVOYqbqhBBSS%2Fohgnt9rG%2BooxYiTOXDMvUBGbnWixwgPUgnUoLMJCOj5n1IP3Oe1ImajzZpD0YOtxzG6rSALoOzOiUm6ps4K8NJPs6vc%2F4cZ1UBv4u85FoRnHWr4azjkRqYKFej8hP3eqCfDER61uyT44DbBzlkBTwZD8h8%2FsMabOD3ZmFWkAiUs5f4f2SFNZfv6iTPscW%2BjOHynEzEcLULuaQbivCdW5SDNcrx50uFYLzFHYotZl1umvNM1tgNWX%2BV%2F3gdebi3ThTgVEMWKYci4kHZhxBie3TYx3rHbGr%2BPdo7x4dIHTKe5DFn%2BO%2Fj%2BW2VnE3ooW6isf0LIUENvZs1gf%2FLHojJwdpplCP5gn%2F5gi26FoYa19ZVFOJ6Sxuoz%2Fq2Ti20IKVJdnqvYJwnhfPH%2F2f6YHoQF30aZaK9J8T026RxH5fA%2FWPW%2F8IW4zkpnIfoFLifGB86v0ffm5nbyRs5iaHR3hNBD0HSfTzoPugRM%2BhdN0x052KoHLBS0tdgpidAiEesDsgWYO73RWQz2LWIwjqnMe%2FuYISQtlbyf2NlT9Q9PoBcBnrO6I5ELoMeyHkNnIXGdv809H%2FDXNOTeAEc0jWMJFcQxvFnto%2F5LjEvHrdbmh2Kji9aPL4839TcKPNAa6mlZUyOmZk6lzbPJ3bo56%2F%2FCz%2BVaqqrat5rY8x7xnzxl3nvo%2B27jFnz8c%2FmI9Nmh2XBdMsilrBitsnD9rI8aiN5DI%2FjSftC9mIf9pMfIB4kHiI%2BhWfQY5aPAYYYYYwpcyfpMMX0aZzBWZzDeVygchGXcBlX8ApexWt4HW%2FgLbzNbnfwLt7DJ%2Fp0TX4%2BUucji1hCnY%2FU%2BcijVB7D46jzkb3Yh%2F3kB4gHiYeIT%2BEZ9JjlY4AhRhhjytxJOkwxfRpncBbncB4XqFzEJVzGFbyCV%2FEaXscbeAtvs9sdvIv3cjmftWavuWs2mg6byt3ooIsFOyx77Kos2kiWsIK%2FUVPDOjawiQmO4CgdxnAcJzClz2PVbNKsy2ZzvoncjQ66qE2kNpHaRJawgr9RU8M6NrCJCY6gNpFjOI4TmNIn36TNfGSH5RrssKtyN%2B59b410iF0sUFO0l2UJtY%2F8jU9rWMcGNjHBEUypf0z8mm7vZLvZaC%2FLzdhmV2XBvpBF25IlLJOvEFfRI%2BNjgCFGGGNK5Rs6Z7Ij%2F45yNzro4m9Ywzo2sIkJjuBj2ZnvLDdjGxntLLWzLGGZfIW4ih4ZHwMMMcIYUyq1s8xkl97bH0y3JkZyM36j%2F%2B58rvTQxwBDjDDGNzyVyX35Ccjd6KCLv2EN69jAJiY4go%2Flfr05F%2BUa7CCzGx10sYA9tiWLxCWs2BfyN%2BIa1rGBTUxwBEfpMIbjOIEpfdjHvGaTd9LJb0duRp2S1O1I3Y4sYZl8hbiKHhkfAwwxwhhTKt%2FQOZPfmY3%2F%2FSs3Y5tNpTpL9ZQeGR8DDDHCGN%2FwbCbdfHO5GbW51OZSm8sSlslXiKvokfExwBAjjDGlUpvLTBY0K5KbiDcT672SbXZY6k7lbnTQxQI1h%2B1FeZTKY3gcT2KvTWUf9pMZIB4kHiI%2BxcQzxGfpfA7P4wW8yG4eT%2FkYYIgRxvgb9TWsYwObmOAITlI%2Fxf7TOIOzOIfzuEDlIi7hMq7gFbyK1%2FA63sBbeJtvdwfv4j28zyaP8QmVL%2FimL%2FENJ5PJHt3RqtyMbbYlPfQxwBAjjPEN9ZksqkMqN6PuV7bZy7LDtuRudNDFwzx1FI%2FhcTzJp73Yh%2F3kB4gHiYeIT%2BEZ9JjlY4AhRhjjb1TWsI4NbGKCIzjJlCmcxhmcxTmcxwVcxCVcxhW8glfxGl7HG3gLbzPxDt7Fe%2FgY%2F%2Begvq0YCAEoCNa1n%2BKVyTUl3Q0uIhoe%2B3DnRfV7nXGOc5zjHOc4xznOcY5znOMc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A7%2BtETl5RXdNNZGDm%2BvXYXWjgLDRzEhoLBAYv0%2F0NHAAAAAADBQ8CvAAFAAgFmgUzAAABHwWaBTMAAAPRAGYB%2FAgCAgsIBgMFBAICBOAAAu9AACBbAAAAKAAAAAAxQVNDACAAIP%2F9Bh%2F%2BFACECI0CWCAAAZ8AAAAABF4FtgAAACAAA3gBY2BgYGRgBmIGBh4GFoYDQFqHQYGBBcjzYPBkqGM4zXCe4T%2BjIWMw0zGmW0x3FEQUpBTkFJQU1BSsFFwUShTWKAn9%2Fw%2FUpQBU7cWwgOEMwwWg6iCoamEFCQUZsGpLhOr%2Fjxn6%2Fz%2F6f5CB9%2F%2Fe%2Fz3%2Fc%2F7%2B%2Bvv877MHGx6sfbDmwcoHyx5MedD9IOGByr39QHeRAABARzfieAFjE2EQZ2Bg3QYkS1m3sZ5lQAEscUDxagaG%2F29APAT5TwRIgnSJ%2Fpny%2F%2FW%2F%2Fv8P%2Fu0Bigj9C2MgC3BAqKcM3xgZGLUZLjNsYmQCsoGY4S3DfYZNDAyMIQAKyCHTAAAAeAGNVEd320YQ3oUaqwO66gUpi6wpN9K9V4QEYCquKnxvoTRA7VE5%2BZLemEvKyvkvA%2BtC%2BeRj6m9Iv0VH5%2BrMLEiml1XhzPdNn3n0rj6%2FEKn2%2FNzszO1bN29cv%2FbcdOtqGPjNxrPelcuXLl44f%2B7smdOnjh09crhe279vqrpXPuM%2BPbmzYj%2B2rVws5HMT42OjIxZnNQE8DmCkKiphIgOZtOo1EUx2%2FHotkGEMIhGAH6NTstUykExAxAKmEqSGMFl6aLn6J0svs%2FSGltwWF9lFSiEFfO1L0eMLMwrlT30ZCdgy8g2S0cMoZVRcFz1MVVStCCB8raOD2Md4abHQlM2VQr3G0kIRxSJKsF%2FeSfn%2By9wI1v7gfGqxXBmDUKdBsgy3Z1TgO64b1WvTsE36hmJNExLGmzBhQoo1Kp2ti7T2QN%2Ft2WwxPlRalsvJCwpGEvTVI4HWH0HlEByQPhx468dJ7HwFatIP4BBFvTY7zHPtt5Qcxqq2FPohw3bk1s9%2FRJI%2BMl61HzISwWoCn1UuPSfEWWsdShHqWCe9R91FKWyp01JJ3wlw3Oy2Ao74%2FXUHwrsR2HGHn4%2F6rYez12DHzPMKrGooOgki%2BHtFumcdtzK0uf1PNMOxwDhN2HVpDOs9jy2iAt0ZlemCLTr3mHfkUARWTMyDAbOrTUx3wAzdY%2BniaOaUhtHq9LIMcOLrCXQXQSSv0GKkDdt%2BcVypt1fEuSORsRUwgrZrAsamYJy8fu%2BAd0Mu2iYFhexjy9FIVLaLcxLDUJxABnH%2F97XOJAYQOOjWoewQ5hV4Pgpe0t9YkB49gh5JjAtb880y4Yi8AztlY7hdKitYm1PGpe8GO5vA4qW%2BFxwJfMosAk2X9n9X2cVVfnA36pzHNHJGbbITj75NTwpn4wQ7ySKfAu9u4kVOBVotr8LTsbMMIl4VynHBizBEJNVKBAfMNA9867j0InNX8%2BranLw2s6DOmqIHBIbDfQR%2FCiOVk4XBY4VcNSeU5YxEaGgjIEIUZOMi%2FoeJag4mEB3PUOweCaG4wwbWWAYcEMGKn9mR%2FsegY3R6zdYg2jipGKfZctzINQ%2FvxkJa9BOjR44W0OpTKAskcnjLTcKyuU%2FSVIWSKzKSHQHebYW9mfGYjfSHYfbT3%2Bv877XhsIwGzEUaleEwITyE2u%2F0q0Yfqq0%2F0dMDWuicvDanKbjsB2RY%2BTQwOnfvbMUhiNPFyDCRwhZhdjE69Ty6FjoOoeX0spZz6qKxxu%2Bed523KNd2do1fm2%2FUa6nFGqnkH8%2BkHv94bkFt2oyJj%2BfVPYtbzbgRpXuRU5uCMc%2BgFqEIGkWQQpFmUckZe2fTY6xr2FEDGH2px5nBcgOMs6WelWF2lmiKEiFjITOaMd7AehSxXIZ1DWZeymhkXmHMy3l5r2SVLSflBN1D5D5nLM%2FZRomXuZOi16yBe7yb5j0ns%2BiihRdlFbd%2FS91eUBslhm7mPyZq0MNzmezgspUUgVimQ3kn6ug48mntu3E1%2BMuBy8u4JnkZCxkvQUGuNKAoG4RfIfxKho8TPoEnyndzdO%2Fi7m8Dpwt4XrnSBvH45462t2hTEX4Bafun%2Bq8jIzK%2FAAEAAgAIAAr%2F%2FwAPeAF8egd8lFXW9zn3PmX6PNMnPZNJMRRDMkzmDYgZMRRDCEmMMUPJIgZEepHlRYyIiNhRUdYuS4ksy9reLDYsdOmLLC%2FLy7L2CgKrrCJkLt%2B9T2YyYPl%2BD8804J5zT%2Fn%2FzznPBQKbACSTvAEoqJAdtUhUJpQYjBJVAUrKSkIOJ1ZUOEKOUGkfV8ARiPB7E72m87WJZF58ibzhXPVE6QsAAnMufI4H9XXsUBh1UpOJSJLmQNWqNsasLkKhsrKnA%2FT1HCF9PQzSAPYtD5V5PW4lmFeIK86EcCRbObLp2lGjGxpH4%2Bf0wLkjjU3NDSNGxYSMxbSdDkzomhE1SypQalCISvniob1lDuTL7injC1O%2BMr%2FxmeJtxeRt%2FiJviJ8mmrjFOr0BJCZ3QAbkQFu0ypCZ45HcRqNJQkiT%2FLKsOO02s2Ryudze7CxVUnw%2Bv9%2BtmKTcgEEymzPRlgN2e5rHaeOXyeeiisnJFagMOSsqSkr45kL8Tr450SfM5%2Fy1V66pGvBwTV1BcYcDEX67QjQkbo8cigTplyVI2OHh%2F6zdXHO4%2BiR6SjoxMPzo8O21h2tPx7O2lmylNV%2FtY5Nwubj3fXUA%2F8BuFveBr74CoNB84V6pSnFCLhRCL7g7OijfR7Oy3FalR49AcXYRFBnsQUcgkAYO6H15j6wiAGu%2BI%2BAo6pleFDAWKJZMX%2BaImNunWOpiskIVH796ewAqEzvV9gqX9nQ4Qd8S%2F1V%2FScSM%2FrmsTP9FfNUNIvzuVlRPMFxY5PB6fY6iwsJw3%2FJIOOTx%2BlT%2BWzaR%2BxYWecrR7fWFFanqi%2F33nnn9%2Bv%2BMvXr7mk933%2Fv5Gy3PrN6yZjg7WFV1D5s2oGoh7nx%2Bk2vvTrkeDT0HKlieXvvakkfecj%2F5uKnhm6iNHRk27a6bevTL%2BclH3ulVkX3cBTJUXjip%2FCDvBiO4wQ95PB6qo%2Flen0%2BWTRpofo8nLa04mB3UgpeX5PbMLEzzKz4%2FtapOlXt5a1llpXhN7FF7r8zJ37o%2FiN15Q2XhvsE8RdajOqwFyrwFGETXr%2F0F9u9dNnZsWW9869X1azow9qe%2Fkpc7D52mPRf%2F%2FHcJFrR1npvf9sWX336EO7%2F9x7lqeUMn6frt8y%2B%2F%2FZD%2FJjzecOGEAnxvWdzjpTAzWtHbGjRhlhdMXqvLVZSWnl5kpSoChLJVtcwXSPea8vNLSrT0dEnTegyPaZIUqIlJLnSKhAV%2FpfBuhb9EbE53bYVIM%2F3S45hfiZ%2B7th8IFPHN5QuXcscms1vF8kiAZ2qBsEEEFQX7FnJDeNy%2B8nIF2JLZ7%2F77DPtk3rJhVV9vefPD%2B57CzCF98cr82%2Bs631s4%2FvbxrKPf1XjT0Iqrh%2F%2BuafTMxR%2B9e%2B%2BmxqZnxzzx5l8embstxo7PeX0Ju3DjoqYJA7C611hyd3hAtH%2FzpD5jAAVm4DM6Zjj5C5WIAIu9DuxCIB0kuvEBAKGBbSTz%2BL%2B3Qm7UZjaZqCSBqtrN%2BVQgmAMTua3joeaMhBTicTt9wULS8PSj5x58eNk9Z5c9RUrRiPte3MTKzvyHRd5Yh9vFygP4yq3JlfmyfHG%2Bso1LyP%2F5yqgRNVjuDPclRSGvk7Q%2B%2FejZJY89%2FOA5sTT7ifVb%2Bzru%2FOEM7tv0EisFhErSJGUpbrBBOOo3ms0ypVZUVc0umUyqilarYrDxpN1aJrKQuykJwvwz%2FyPMUOCTXSqlRa6CiEzJy8U4J8DWf%2FjpM%2FeeOMZeLMKpxYqbPTyx088Oz8MKtnMuFqefm4gzAKEZPpUqpG1g5qivGRSjkSKAxWo2giJRKOFCysqS4vjNhQXCAa4Bxz1HEI%2ByNlx0FBextqOk9SjezW49yhaIHbGzuBtOggKe1wgFWVapDCXbdSNt5ghfoNCgMxLA3X1v%2B%2BdV%2Beg%2FvIsdR9MJYWVcS5rISqDg%2BCuVQQLkSiTc7QoHPANIGq49dw6wi7GwgmvujZoUrrSRNsaMLqjsmfjnkYu4aU6SlJZ28xECNyqt0mMrM2pBricBidueiNS5iDcRA0ir4h%2By4yQgGJP%2FDwLVF05IQ%2BW9XLoPLou6LYoTFPCnGT0jYkaV2kfEaBok8y%2B1kkYCeeDQnIEyQI2nUrlDE3kkDT3PzsfZhXMoxZHGw2OmTRl7w%2BSpLeQoW8gexttwNi7C6ewO9hD7%2FusTaELr8eOAMA%2BA1nJtTNAj6jJKAAZEs8WgqihJRgX9wJHOkYoXkf8iwR2RiKKqRRiitWw3lYdnr30cDzNae%2F8Tw%2F1L3sS5gFALINXpKDQgmp1pQxW86M3O8aoqMTlNtTGnSjATM2tjXEgCYfS3hKyuCkFHkzBeScI6WKhFVxLuD%2BEQLt4TkOo6CU5f1drrhvrrVly%2FdspDayfe%2B8EtQx7fuJG0HcbZLyyc1r%2B5qXbojtE1xa0dt4x%2F5c31r9hA6MYtP5DrVgijoiV5Po6KKs3MBOCVStFlgez8bG57v8%2Fvq4tZ%2FGilfr8pX7VqJm1EzJQGeg3j5%2FxX8ruWMbrG4oduFyXxMEFyQlkpkMeJTvhKbCMY1j%2Fo2ykPlEmSr335KxvYPvbZydev29P65KNrX58%2Bc92zfxv6%2BKil76PnU1Sl6fe%2Bl694%2F%2FzIweMjUO1ZPnH2TU3fxqa09%2Bl%2F6OHXAQgEAaSZuhddMDiaZ1epkRAzpTKAxyVzrnGh7JLreGi7qF1VqO5WvoGQ0DwF584uo3cpz4sCBzc9T9SAQPKgoqI082X2QfxhshCzXmZ5Jmoo6MvOYAk7gCWH6cudN5%2B98oSroZZNBoRWbuEw1ygDmqI9OZ36aJrbbTPYqIFmZrldRpdFA27ONADF4%2FHXxjyKYhkRU9LgYsIJ6e%2BpgHAkGUjkgUhLSBg2N9w3IMwpylMaKScT%2Fn6efcC%2BPLN8xActmMGOhu%2B4bH6EpsV%2FyAgOoO0n9%2F%2BHnR2B5h7hr455LAPJ1%2Bwc%2B1i1AYGhXOs6eQf4IR%2BuigYUp8WSlweZTnAWFNpz6mJ2u4d60kbEPGnUwENEvUTbVJbqTCjIAQJlPo8IXEUNdQEJcCAhMvd%2Fgvy8Q3E6TmsbErv%2B%2BZ2tRuuN%2F7f1X%2BzsNyv%2FvYhoN066sbVlcRuZiq%2FiWvuP7rEb%2F7LuhyPfsFPLMffdxfMnz7%2B1fu5qEc0RPdM6QIHLo14FgCDKRFYNMiWU1MaoAsLfupYpQwobhpDby4OfkoJ4iZQWPyy9jNLm8wLSdEtUyzvBB3lwOVwbLXYqnl6U%2Bo3%2BQo%2FHnp1ttBtL%2BihOZyBQXGwBS0Z9zJIGwfoYXGwTYYlLnVeWdKFwoCSqAj0%2FLqoW8qk7kShFiku3kK9cfCPVHyDedt%2FqpeyLL06zk4uXtU1DyfXfE2fPmrng0Ccjbhg%2Bflxtq7zz3ZUzXhrU%2FO6sjqN73mrbXD2iY%2FKzm89vbBp7Y%2F3VcwaOI3vqq674XdnlYysH1Ym8GajvcgekQQFURnOzZJfFEgyCCwqLtNy6mKZRrzd9RMyrUkMdR%2BNfdbfu7DIBzCIaw0J5kS16edcXuNOdBXwbyU1J1ewxtvTOqxtHP%2F3%2BJIOl3xOz3v0nmr9Y%2Bf2d8VNjp4xrbbm7jQ5mdazJdtYzasufW2r%2B83%2FH0fEE%2B3DTXbdNum1%2BHfd4stOSZuvMURh1OXnyAPjtnsaYXeumMPAnaOwXTOb4NVYT72PqU%2BxG7xcf6mPNQAQX6%2FIUcHKmcllV1UUlBRXFZdIaYyZNUjgzJ6Rpm8u6mKrApzM0vUgYbrTrbF2SFHbS18Xa5GhSmF5P7JYqZODSiqKajIK%2FVYNEqQIEZRigFxShVFwJURhGD6JU0ZlDP443kvW7ccNSPH2abWFfCns140peoYDeNeZHHSqlRgkMcp00ViJSV30QKhkjagSue7JMQH4304%2FFkrTgKC9Tjh69VLueUScBrhFPNVAUJJTKEur6Ce0u1dCFuorNZH28UayJb2IaDjjNtKWsWmioXPicrpB365FYFc3LTU9PA%2BB2dlqdhUV2QCMFCAazGmNBl900ImaXkg7mVCR4KJVkyfpRJFR5F86oRckaXOFoe0m%2F7W6YevPVY5uWvzf1w3P7vm99YGyIHU4139VjH6ob1tLvqqpxR9u2r5m2onVI9RVXsHUX9eMTLkxQdnCc6AuVEIv2VCsq3G5XOGzt77rMZaWBtEDvNOgN0au8hkhEMg3QTPzqkVUq5feAklS7rOucMleiPU7ivc6kQtuiYCqrfNTdlVF8fxLxCKgtj3iUQC44%2BjrzOa06UfyDSESH3x2j106vnpWmTXnhlT1o%2BUfT%2Fqt9NdGau79%2FZhf73%2BexCP2T2Pz%2FZefZXez6I%2FgIyv%2FEkRs7Yf3IFpM1FG27n5x%2B%2BNQ9Q%2FotPPTGQSQBH%2FPd%2F9Yf%2Fvjjne1sx152gh0p6f3eKHwYW3%2FEZZ93sA627uCCpcfMzwj7AIC8WN4IKljh6miAWKkBQZHNZgqip6CSZLOSmpjVSs0yBZocIpTouZRiZWGortKL8gsDiITjI5Uik%2BLHJ7FXiYTziRJnywoMgWdwNFstbzxXRcbikdvy72CqiPvXAaQznI%2Ft4Idczsm9VLdbktKzzeY83vfZ7QGDlqalDY9ZNLRSTbODPb0mZneCvyYG9BLcSxY9KQVDSTe5ArmSp7voCQYwWfE4HPqnwOu4AyOYNn%2FC%2FfPZh2fjx7C84%2FaZ8xev2nXHraxT3vDKpkVrHaacdQ%2B%2B%2FxGdXTuy8Zr4NrZo3PgNgDCXI%2FUBnh9eKI36VZeLN%2BNWnxscUBNzSKpskmtiJleyNBOvSfVEKuQRD2%2B0Iw4l2BUdoTI%2BZiikBS%2B9h9OfOtrxL7aJvdiOkQOHDrc2tEs72U%2FHmW846xyGi3DSZ3j9azd1FvUDImwoz%2BE2NIBd1OtGAIdVkjTZUhOTqWTlLbMzaamUcEELnGVzAbVA0BHKleew8ew2Ng534wR8gL3Dxq5ZjO%2FxGuQP7A55A7ubrcHDnUMBdY8RLs0Mg6L5BgnAqphMiBbFWBOzKNxLAnII3zehaKqJofOXXkp5iCsitPAkbol0bqDV8RN4ijmIm4tl7zK2BLqkUsalGqFvNN1AqVkBQDQJoSl5QlZS0MVSLhaCX7P9dHD8OHKMEwKWxLu8KBdxL6ZDTbQo3e8nNquVEFemy2DIsGlmjQdbOr9BNkt%2Br%2BzlsmTu1FB3wd0z5VlnstgW8BBwKLpv9YJL5RlPdMKNOALkU1L14E93sr%2ByVfg43vTxgZtW%2FGXnd1vevKGVHafhuOnyAlyMU3AcPjDybB377rOT591Y2mUHeYJu%2FUg004jIzW%2BQJFm2GGhNrMaABoNsUijK3QmbMnfKFN2XPIHtjr%2FNdmE5uRrDZG78Xj5t2EIGAOCFiawBT%2BozgRw%2BbSAGXiPLwM0MRsr79e4NCw4Rxa5IJL6kRnJurq0bOKEZy79hDV4k7gVL5JHn1l4AdgYS%2BtfxVS0wMJpjIcRkNiOAzUBl2cq%2FUrNZoXwP3VtwpgBXF1eWAOXEQAdVfSMRDKBcx1awhYvEZm7FB7CZETKxJf4D39CN6%2FHf8XkJ6VIlly6LPUkqBVCQArccJKJUl6GXoPq6r3PD1MsbzldfSPxvRcyR3dAvmukGo9nI1bbxUPHKisdJjEQxq9QGilBcN36X0mUp6hA6Y9DpEYujXuXykscVRBpkK4wudhzbcaSC07GdfUgtRrZEms9Wzok3cw1WSi3nqklH6R3oPr8kYcedOm6WR9NMYETFagVwUFlRVM1MVW5RVLtHv11adI%2FEnAKwL1KEcM%2FJO9nv43fpSiwh81U7%2BqQGdrQtXseFv4FZvycdQPQ8%2BVKfDHgE0jgAfBZF8RpdNTGjRO01Mer6daQROSBexQQy16Hxpkj%2Bkj3BXubXE3gz1vNr%2FPlDb76Bs9nSNzaSY%2BxxdivejVP5tZCj0mP%2FOYvf4smfoAvtpHU62rkEFkhGowdsNrvdbQXBV3ZNM9TENGr%2FTSzoRn%2FZLXHoEyAo4ckJSx%2Bau%2BBBspEdYacX8yA6iCb0UGXmlKkTd504Fz8rb%2FgchAXYat0CdkjjEZynUFmSCDVIJg9AhmYypVOVEwBXRFK5UWSV22N7Ev4uHU92T9OQe%2BLX7PPaKziWzWZnfL9pJMZW1bO5OPS3LSUP1S3lg9poocvnk0ySppm8njQw8cTzu4wWMA6PAZgtFm40C%2FWaRcikzJbSWfPzuXKqQ0sxKLdfgl3BF0A82brsgaXLW7gB12EPzH7oTqxuZWvZKtp73M0Tm%2BPz4vvlDUeOLdxZwVwPk1KRVS2cQX0ce4s4n%2BRlpKcHICC7LeCGy4rdAbAELNlGX3ZNzCdRYyq%2BuhvwVHHWrRpn%2BIvGGoVFl%2FMhDadWMcJP9LZen9cr%2Bdin7JuOx%2FZeN2FqnzFL7767DtWvZu2f2TrnyermlsJrn977BC7f%2Flkz5g4srx3e8%2Borqypveeqmzf8qL%2F13n8KGgcUDKqrHbRP6FwNIYiqrimdLCgBFNBhVKlHOuxSdv3y2lARgcoLtYrOlOn53IGEMEF7k%2BdXC13JCQdThQHSbDQaX08hRhsdSYuuXVBAOtyLx4BHI6%2B6CYLnlEXbyLfYFex%2FD9zz7BAf0ztqVZ%2B7EwHn6YufCPz33%2FDraBqjXfyHBI2K%2BRonRKAOiVZYkC3BDJ%2Bq9VNpUJOaj%2BsXtVx6h57CC2dmLTMMKdPlKFXO0a4DY%2BdTwvZeN%2FqJLhrqRy8gSsx%2BT0e52yQh%2Bv2ynlszMrKwci9mcnemSzdRvt6NJiOSi%2BEtCbgo1UyM3WkiKOMKJUtMlGvCIi78nPihD2fPbzWFJ6WPdxqngfix9q9Sr9HQdwoJDth5mUy%2Fnm1hKoRixV%2FmpUJxwVT85trLi1EAa6twb%2BaS%2B9uuhNBsStmnSbVMVzTXLnPpUo6oYTYpJ0C2VLGYDkWXJqFCUkhDL9evG%2BooUZ3VpjZj8Izex59h6fnXg56wfNmF%2FDGMtC5Pi%2BGHyHdka%2F47Y4j27dJCYyF2B7wZVlZEQEERvNFFF4QqiSgVDdslOjEH5Z65AarLLowIDZAGWchEZbA%2FLwDo6mozsXBTfQUqoXleVJiZ0RugfzTJISFUVEExmlYuSRP1I0IAGUcZdOgxNpl1qFqqPbALSzPPvkbfjTVJ6vIrs30m%2FRXi%2F0ykkLWUbyWw9T7KjVgXRIIFRJlTBfN2EuvH0BNZX4iUpmc0y8bOPPmIblXMHz60Xa1gA6MDkVFt%2FZIKYnGpfnBa6sUmAHY9%2FmJhqI4S4fJ%2BQL55xoKIY%2BVYNoOZTiaaCvQtCfCFHMMy1CH34IX7GMmfKjQd%2FUoR8AzFIA%2BR3QIHeUTdBWVYkSTznFd6SVJko0DW%2BxLKLeyTRZYcwiGjADQ%2FjqVO8uP6KGOiGzmqyKN4maq1OtpHWXhja9SRIRonoRhEaJZ5K0NrOFyl%2F%2FvMAAGKNdIQ%2BqATAwK1gBjVKRVTIdwCUpB%2FrioP0XWLww7EvHPD6PGRL5ZkqbKpcLx3ptW2gZ%2Fz7GYIdmjju9pfm6E8Zq6OFTovBQvLy%2FP78LIMhaEkbFrNYZLfbPjjm5jWdnDM4JnvBk0Az%2Fy%2BZVYSeXlcUJWdMvMcN9%2B1u8h0omny9N6YT%2BhuGr1r0xzd%2BOr%2F5xbv%2FOn7T8Y9PswO%2FX3znY5MWPHHDsNfXvfono1K6rn7f%2BK3vx32E27h55MJbxwOBFVznDsUNTsjh7BvIojRg1Mw2n89szrWA2WPUFFDSh8QUL7iGxEC7mCz83SHi7H5mUeZ0aISzRVANCgTlw1AfH9d2D8WobftHX%2B7YNsMT%2BhpLLZbJM2ZOJJNvaZk%2BQ5rNdrPv2XH2t6XzFTdbPuiJ9jP3rwh0PPOXNWvWAMLoCyfoMWk2eDi6esRYymclxCubh8RkDexcM%2B%2BlZZJuOTk32SdwmnJoYkjgUBQyIf4DZqJx81Mjh9525cmTzcuHVf%2FBTQZgFvauOZFVwBH49ZIydr4kH4iQK81M2CcaDRi9Gi%2BobTZhqFy7xwIOIyi6fTTdPt5ft4%2BoT4Q%2BecShOXlPGioU%2FBLkji3iOnVPiAnZ9vHnOw9ON%2Fmw7Jv%2B1omT5kyVp7dNmDnLjWVoRx7zq9vG4YSfTjyy5vt7ViWNk9BynD61y%2BDMEKROSUpzOLKcJlOm3%2BOkzuoYFVUUVMesmuoZHFNTel5aloiry3bI3RbgrbNeR4XKwOMJ6AVAxMMtOP2GaQZcT2aVs%2B%2FY3zDt7LdoiJfID985vmNc3Qb61PyZM%2Bd3NmAPdGAahth3Jx%2B789Eel5%2B4rCjB7nSOkgMeuCKa7SZElSn1%2BqwAPhndyHVz283akJgZqJ4bgp8v7QVDiRwWFgxH9KfOeieocBWpiZ1l%2B9eu3bj%2Fufm1o2uv6ocGOq9zCZ23rKHh3ZdLPsoafsVgoKAwtzSV26sYyiEKd0SrzFlZAwZIfRwOUqzmSkGUpIHpPXr4fJFg8Kp0K1jRqlj7qv2GxYy5Eke5wr7FpDpWXFxYWDksVqi5e1fH3BkXz%2Bn4pxIOWz79gRHv0LneqJs2FQ76ewKfPao%2BpSsqEvmsj%2BykQFfCF6ZeRcGFyUQK8v26El%2F4WGzqS33OfxjpXbL2ndc3sTfYvm9%2BvP3WksHVg5tvOnmsZKGTFc2buvrNabOfa5w5%2Fdrrmura10otT%2FceNqZjJ5Xzew187smt%2F1i1bPw9We5Roeh1xYVrZ732vkM6L1UOHVlb2WcEHT5q0qRRuwBhBYC0lmeDB8LRdATw2Y0Wg8Fo9Nolp1MaEnNqJkCjR6D%2FJfU5336yUOPaKqJJEuCQeFQirWX7O%2B6YxfZjqapqE%2F61bQ958LsXt8S%2F40CwpeDekav%2Fvh0ILAPAD7lsA1jEZFcyGsFksprtJg9Rr4kR6DJ%2FZWoO7uobKtNnnyJUlrW3X3ttO14phMgLHn98yIjzPqkFgFxoY259XSt4oSTqd%2FL0JgaDT%2FNcE9PAaBctOk%2FsjOTEKYEwCRGJxwB6tajQpMDBcxoHXzN8CJbum6GLZe60066mRmnd%2BeJXN6mThXRIWPMH%2FUn%2BNdGgxLmTUKrIsmYzWa0Gg8lkN4P41WCzUcXkofbu2oTf3cjSZdpuokXRuGOyi1dx22KswGZWhYd5AffOIrF9jYxdh40sI74Et93MVivueDXr0gYPcG0ouF4DRIkAevQioLvExgPivyvuhO7qQJ5BQRgeLXS7XPrsKDMzI6PAajSaTPkuq9WRKzu46XwOzWzPRJNH7%2BG7krl7%2BOC8ePqbjJDCRIiEfKFykdziVfBd8q%2Bke9n%2B%2BuvnTGL7vy529F437Xwso%2FdL097ZwvbVXz9jOnlw3rz12%2BLfSS1Lh1%2B%2FurZpy%2BF4kfhtxYuQjGCut1tMFxHAq6vrscoOoatQFU0Xx29SyV%2FXLRG8TS0ierkyof%2BZtWWXEPbn7boC9dce3JHE5yf0pzhpostXLJYMcLnSvcYhMa9mp0Nidu8vu%2FxUrvPeVQMOCCQs6MzrxGVT5986ecr8W6dQmX3ELvzxh7swGyl%2FI6Xt6%2F70Qnv7mhfYKbbnQTS8jE7s8wA7B4LrOep1cC1ckMMn1Hl%2BRVFNlKpZmqrlcuQEq9U9hBOEwa5mQEaKzBKmSBWoSQVlTvPepDFCnPndRKFJtuemosq2GZrG9p%2FtaZv8wfaPbt58TGf7vePdSx%2Fwsv5K9SPtbB87%2FT%2Fs7H10mU722JDgM67pTN1euaIq8dIsyh%2BTpOUZ%2Bfg6PcNnz%2FZanE5V4I0FhsQsv8m6iSfIBUmS5S2dL8HBXl8ook%2BLIkFBaLdMkafPPzxZ2v7R5zsmPXeFIQMJ22e1lq48uri9oOMZ9uLa9lNYiho3Z9%2B6xqU%2FbcBDAybXN3ZFFJ3LddVEh0mcejw5BCxZZVnUS7wGFxqlMrTMRy%2BJIqpdWewrCD%2B6iu3%2Fsre97yvSbCP7xLR8SXyH1LKxZTYkqp%2F1XIZ4dpmjpLktAEU5bnchWNw5lhxTli9rcMynUdPgGPX%2BvJ2%2F2BgiqPTHK2HB5clePsGgXCkPt082oetPnbx1%2FbDrDtW395oycuG8yJd%2F3%2FXu6MZHa5Zcv2zRrf2wZn1HILfzsvKx%2Bb0rCstHz73%2B8VXN%2F8y%2F%2FJriK%2FqHR%2F%2B30LeE6xuRa8AjToRYDHa7y2UyEIfB4fWZnHbn4JjVYrfL3HVyQt3QpktOVnRhgnBcxKOXvoLpIyFPwCO6cjK3bsas9tdeeHRt8xasYDuu%2BTD4aeiNN0jGwgknTn4e%2F%2FyqK4UOT%2FGc4zM%2BcENZ1E8cDrfby3t%2Fj9NoJ7JNtumyPcmJ1sVDgItr7tQYgH%2BgrxdrpR2zt72PpSLjsXRp7XUHt5Mj8dki4Ynt%2FEpI9JkPcrlm6BV1m0GWiYgIK0G0GNEuC5llKWndDU1X%2Fx0SbTfiOtaElf%2FINyryZYexkjVJLfFF86aMXUzaumS4AZRtXEaWOMsoSyaOIVng81ETVTMyMjNzVEXJ9plMVLbbMxQ7yDqidR3RdPz2LIDSIO1WQ8wBsin%2FpGskRZpuUfew19lm7LMwJ1eRcrT7sG6R5NCsqBgvN92NPdk7uARPdt4vtTDH4m9q1lxH%2FPGvvE03jMkcer4XnuKKI5gApOW6bWqi%2BYoMaKSUSAQlGWWzQVWtfIZmMSoUAA1mj4T2S2cBqaROkYZeq3KlhdkClOu%2FmD2BI48cxZHsMWxja46fYO2kPwmyZ7A1fiy%2BDRewhcJLzK17ycs1KTC73ZrXK0koahm%2FJgob%2FpNT8no0p9XJMTHDAFyVskQJkKKvhBlTUzxHyokifvTqgNsSaw9mmBRz7n4cwoqu%2BvcfR9RErqqfl%2Bfkfr2%2FYcZNo8ic866XXnR8Z72xNZI450HXce2MIn%2BoKqkIYDYgmvQhAm8c7YR%2FMwyOoefSIULSSMJGySlCWEwR6LrOB4nC0uhAZiCmDrLp6%2B3xekDI4T38Id7D54ipCHUbcnIcfn%2BuNTMzIFGXy8qjKd9qSbTzYosp2hbbF7bnuBrm%2BREWRw08Coc18VTQ4xFQ6%2BEJhDmL2m6%2Fc%2FOZG4cpn31T3XpmM9quH32qucGAVz7Z9jEdXMUObcyzBF8xskNVg%2BknbU8BIO5gJWSlYgMK7tcIpZJMAaCyhONDYlbqCOKOo0cV29lA1ylOauB7yBN7yOHlOmgGQ75bkoI52TabW3Z7qCzl%2F3%2F2IIuHzuFynuSi2BZnlftyiBSnzxyCyzwcrImh4e0Xbhz2%2B9mfKtWtL7xTP39x26LeM2aFPyFVQ7CnuWmyw5K3EXsOrqIfh2dPY5tNjY2nGm7QTxGQIqmCtoEHIlG%2FAg4zmKnd7qNeu82mSJSaHQ5QoCRU1lYi9ElBdqqp5pwa1sv%2FRAMmELwQB0baym968pqFwxaOC99ePv7pgf89chFZcXX5l1NzcyPRii%2Bnphf8lzhBwpbiQanl0rP6Dg26zurbad4v56mukCugE0Wi7Vh7JsTasSV5lIO0dJbKBcljHAhLOdJqfN6cwad7QYchPV3OyCA%2Bn4mYMrPSXCNiBtuIGMiGNH4pGWmKygXqpwH4S8%2BePzvOII575nOCTh4R15lS69q26gmSEBt94OCr7YtF6z7vlm8b7mpdcN%2BrL%2FfHcyhjZk77c8arjmflv%2FBn9kZObzbAuFFEB4A0ST%2Bd2BztZXeaidFqTfd6iV%2FzO51ado7Fn%2BavjxnT0sDFqcleG3P6QR7xs%2BNNXUfUIJTSVqjbjT%2BpBpRfbpXXFSKawsFwiBuQbNyyZcyzs2sbcS679w9k3%2Fmvbhr%2B6qufy7sbvojGrt10dOm6WtZ5ttes1keObtl5BAjMBCYFpHXcnkW8R87TLC6j7EsnBrDZ8jIhM%2FOyYp9LSycWo2xQPZ4ctYBHz%2FYyHc11H2qb9S%2BiA4oURXyC3SM%2B0WGqPrVIoJJaFCmMXFRdbixfuGzBqEk3j1qwfGE43Pbogt%2BNn93Y9siC8v1T6%2BqnzxxRO50cnPC7BcsWhCMLly6MTZs8uu2RtlBo%2FiNtYyYOnz6ttm7aDBHpCoDEp%2BPghZnR%2F7I53U6Plce2UaYyMYkJqxeRED%2FHBp%2FidDkbYkCRuuwmm93WEFPtdgt6FMsl5xX9mtiW3kNfypcpEhAfkgPKkCfoEXdAGF7cGCBD0YAVbOGWH374gX38448%2FvsOW4BViZBv3vHrfq8eO8RdyHMhFiKNCMGoniiKGmUaJSlTVsUcEbCpFdAhyJGBIAFHnAbag8wAAgUm89lnw%2F0o5D7g2jvTvPzOzu9KCJNSFaAKEBMYHAokSuQpiY04OODjYsWxCcjbkNaluuPdyiXuaS0jHpPfeE0N68fVO%2FObSe%2B8uy39mVlqEzr76oeyi%2BbG7U3bK83yfkUZBGZwCMyKlaRaXRRTLC6E4JyfkAld4DKmpsbkrK0ttpSafxzc15nHqTVNjepQycUvmivi5NiuyMYtA0qyNo3NOVr9OFfZJmt75WUW7VMhOWtE4fsubj9zRP33SzuaW6LxFB3rWTJj4xSuvXdHyYsOAb%2Fbpj257c%2BOS5s4tvmrim7appHXPputbn8kPlVdURssit194%2FxklXdGr7p3261Hh7uKKUGH0uu2nzi8Pxya1V5qmAUYu4UfygiRwVi0%2FYrQaWIvIdGcQ4pBB7dzU9snCdpLZJF%2FSOXJNjdRPPa0uMhVd2TKurqk5Mq5FXFPXEB0%2F7ucNExvqGieOb6wDIIw7lSbR99oBPqhmvm9ikm0mm7%2Fc7yzPc%2BbV1IrpYEmnX1mlhbZglpActKMVbEo36zBrHWyifBGnSASrw44ZvIhr6bwgFCxiuH4R45HIul%2Bc91p4c3j55tf%2FfvilPddGFx5b8zJqf5X9DCi9v%2Fm10vvcrj6U09uHsg%2F0Ke%2F29invHSBfX7VJ%2BTAv99nwkcNvfNd82xjlI%2F4%2FSu%2BrLyi3%2FObXaPaLTJb0b6xlBfCX%2BDHKMLqgAOoieZk65HLlmXXU56PLK%2FRmGI2e9HQbys4GEGweShSEA0F1mAtak3BQbR1SPGxVVo3K6irbp3YM1ToJV3pGr452r7n58XnrWi6tr79h3tY9yqTy%2FKbYvMvxsYvGRLrPu%2FBCWegef0l%2BcNcmpeGP%2FqIz6oqkNPas06Fd6BEEkMAIbZHRaUaDTKd2RMKCgERqGDdkGNkrBpBGCE4XBIMoIpOMsR4lWko4kLBqJI%2BK5j8Faab66Q897w8yR4ALIR3yqYfpaPGg8hFyDSo70RG06A12%2FoayC49HL1E%2Fs9K3DL2QNXzKGb8fhTCZCCJkRZgzSkcQkogAAdYJoQTf6LXQWZQQHjx2hLz1I7pgEIaGErEHWAIzAAhaezTEW%2BS5kUqBYFHUgcViJEbamxB9uT%2FROLFE8QLBIegdsp5%2BnaSN8spKbara53ErgY4FlFnoIwadmhP5X7VaYcvuz5QHAu8h%2FcO3K%2Bs89eFTJuceP%2Bdft9utd0xUFqDpyj3kqh3K1%2BH6uhrlzX%2FZctHQEckuSNLhJG8MjPTGCNLRbwWDZH%2BFr%2F6Jm7D5hAmyIDMiQ0ZGTrbVkMkqRQ3FUq17vL06HSowmDyctbXd2N5201ln3XjW5a88G6uvnz2nLjJHWMg%2B7W0766bZL10emd02YWJ7G%2BNFAYSwiCGdcx%2BZGTqdRB35BoSomd9sMRrSZYQkAYOKeoYC8S5MM5WnxriwyfZwnAs9I2%2Fh3kG0RVlFY12UNylYiiCAo%2FgZTriVRKwOA5LAgiyuTNnkwQ4Hyucer4lJXb96j39EPHUF%2BJnjK%2F5%2BbriipGXeqiuf3np9%2B4YudA6O3jbYEQv6S2bt37Cle8be7rMBwVgcxo%2BIr4APJkRy7enY7QbIl%2FLTzVK65C8mdrvDIed4PSa5IIE5pbQ8dlABTRX6S6xu1DgHrezj3QjuuaN9%2Fn1P7N541ards5oXtJ3REgwFWsOdE%2Fb9v3W9wlu7a432i6at2N7wzOzzq6tvrAr76ePuDExYn%2BqLI0JEDyCnCdwXdyjui3uFjR%2FVNMjMIUk6ao6YiGZWHZ0i%2FDX75U5H1aEgAOK2LmrkhkxmMUmXJFnOsjrBQR%2FdrXNlOGl7yiCq4Y2Z%2BzTTkbYwT8qwtv73xo0CxS6XhZtDZ7WvpVaAD0ZnlC6fNWF%2Bvigy%2Byj67YoVdz%2FPrAF7Z8wo%2F9mM65SDUhQQLFSOCbslO2RAIOJINwsiAoTMFr0emUykKWYSWc8XiHtk4gMlbe5qgAb7UsMIa0IFwu6bbumd0PqX1%2F72IW5Tjkmn%2F3QfCVmPHEWCwiKd8Cj0e7KGEUURmUU6Ebk1RiCQCHSypSLhfEr%2F%2B2Eqe2hQsaNeALBCVcRlNjI7Fh1Y7Gaz0W60ySYW9pXNXt9QQI0EXB1%2F3PjAIiZPQYprQ3RWgnr3Xd88KXuOu%2FGW5v7s6Kwj6xc5btOZJpzh7hmf2cktXDiKGxPRSYI8MjopD%2BWfMDoJeePRSb4QbvyciNkVzReismdxFD2z4Oyi0vHr6MwOwnTUfEt8ic9KPBFjIvYqgzhkDw%2FxTGK3kxc9YlKPgt969IarH3%2FwwP4nFG9dY%2BPEiY2NdULbnf0v3Hr7wAu3dHR2dnTMm5cy6s2OlKZTy49OL2AW1Ib01FNiGh70BD7YIdHEB79%2FOej1B9UBL%2B6NL0aoFonqQehRdg4ip%2FLxIFqsSMPn2KuMXYbaUNsyJZw1fMrGrnIA6Qpa2n5Y%2BTuAYvg1fgUA6eAP5Nrjj4L8IMFW%2BuJUVye0D51Au5h8T7W6B7CZSZlyNlXeJ75ClUs8XEnM8as%2BEb9qmXpVwDBeWUH%2BLLTzNU5DpKiQug4YJk0jh0pMoyDbnI1lQp0JPk9rzJdhoRy8xZvKwaN4g9Cm5HHsnddbrUub3bCVWHLF4ldiF1wYPjM27aFzzp37w3lvHP3F7rOrUcnw6jY6d1dT86yJ4eiY0sOnTO6%2F%2FYLru%2Bj0cyyamXhHhoZU2lu3GPuhiOexHiQ0HfQPYqfoh9HVJ1B0w2%2F%2FheIgzFQV2SMV52iKgYTCOlIxU1N0cUXaQwR7uWRYkxbXSNDfPYvXhpfEa4MpdD7OPtrg4sg4yUbMNmIRLCjNZEJsvgbgEETRbiYUvqb4syENGQkj%2FJFkkzkxTAQrMmlscsKiQLvUAAeUNb8G7yQ062PCs0QKkEYsI9rR6nzH9imOvcoLeLew9%2FghbKIUT%2BhoLlq5jiPvcYqZDnXNrC6WKXZGjNP8%2BVlGYAXOBfY556p5%2BZaodTT0KC89ZE%2BUXqqiG9pSFPdShT1JcXDoO1XhHnmNmZqia%2BgnXgMYFag1wGbucZ7cAJnQGCmivUCW3ep0GlBamtthAIqVWwGovcRJi9eKLYy8TgmP0%2BBgddahWmkscQqUlpiPo4MhBwPPA1tV5FzFz7cKwm9%2Bd%2BCzzzahATIdd1Du%2FG5GoOPWnR9%2BofQoyl1qHsRXeDuriLez36eUA%2BdUeTlUxtt7N1fgvJMpulHDv1AchOdUhXek4hxNMZBQZI1UzNQUXVzB2vvoeGkj2IAMglnogXTIjaRLBGTZYORGZXcgqMUn8260FqnLBlSM7lL%2BuB%2BVocqr6Rhetkf5tfL7vfj3qKxH%2BSMavZf%2B%2BVuaSiUAhD7DLeIHkgA2yIZCCEdyXJ4cuz0tB9LAW%2BTMK3Ab3QxXJQWpdOWImbyK8arGGFaJqpEG2V2IO%2FyqihEFV1Wm94Xts3tnv8iA1RevaL1x1sDRP56CjrR2UWL1%2FZBiOG0%2BWqzyvXWXXHDpANrEwNWGNfM3DSi%2FfHYJ%2Frbsp%2B8e6j5uKR4aUmlIXgO18Vocrdaz1uOkKrqR6V8oDkKPqsgfqZipKbq4gr0RJcl9kqDwq4yNv3kb1KtYuCSJSmbrqZpIDiOjjbIoSpJTMDbFZEdTTJAFWdIRyZowKGrdjOZBjePIDroW0tZGwh2UUz1yNcPaH1CQ4fikjst3rbt0NcHv%2FagMUij5c2Vc18rz5%2FNZJM3JfMkD1dAaGU3tegXFxQDlWSZTbXkgUGPKKtBBcbEui2SWhkqnxEIQcFgyozFLwnGq7ZUx0g03TH%2FaTYLqcnOkuuX8iaFL8zhXsVAn4a3SSDRSWl1%2FRVfoo3fmXTau%2BubIbfnTo2vnNjQ0TVjXsWQjbb4%2BhL9FfuGvkV%2BcNqai1JldVTJn7srmu%2B7JLfy6KLhqVGhcaeOylsh5lbWnl49r6TrnKPVMv%2FLO%2FazH5ASbVEBr5VQ%2BUtQfAPb2jbbEazY1vfvCE6Xna%2BkHfxhi6RUj001a%2BkAasPTikemClt4lAX%2B3T%2BGCYcUDmqJ%2FlKrwqwogTCEpQjeUQBBOgS2RydU1JDM%2FP2g3GoNBuabG7%2FGMKZPlsC%2FfW50fjVVXsyDp7OxQNJZtNo6aSoF3p%2BS0NFDHPHgbYiBJgQZGv%2FERLZmZ0t5q6wkJKnqMhzBz8MufZG0ZXsZRzHYYrWJk1TDShwoZfiVWbn2rce4L19%2F03NdfPRtr2nHzvKc%2Femdx%2Fd3LDyM4XkaJq%2Bcfm%2FbY8bqFq1fv6FyOvX%2B1oHvwefbOru7Y0zcz5q91cn3Tq52bInXKZx9RCGvWp8UlOEsQzpxD6T%2F05acLVrNap952xtZhP0xWx0%2B0iY%2BfnCrjtT1FbQ2389oqStRWanr34n%2BeflDP00eNTBe09C6rWpeVidoeugYAvcGv8LTaXynTgF0DGRLXuBwA%2Fy5J0T00eaRi6JdU8UmS4qDyuqqwJBTvUMXlkqApuriC9Vdu9UkSBIfk5fPVpZGx4MYuV46oJ%2BkEY0tOTnr6qEKLpcQNmZh%2BSJ2ImdjppB56CnnSKS02%2BRpiJifBU2MEnYC8izsQ2clwI9I%2B1YYLf3Gtkw8SVgdtm4XAwyNdtX46hDAvXCL2GCmnN3ZetuitjjuuvUr5%2F0PfKX9DwuFDDfpT17zfga0rz19x8fIFq84TXdXF99Wdtr1n%2Fm5lz4fKh8pLyPrJR8gyV%2Bhdtuva4%2FMv2Lj1ih27%2Blg74MwMf2tPV9%2FaEPAZUHI97ucl3KK2k5t4PReeOJ319ZfAyRW8pRiS%2BgUt3aSlD6jpeSPTBS29y6C2pIDWK8yCw0JYeIl7wbKhNGJ1pqWZBQEIyYUcNwVKAXHz0vPBYdBQiw8WTxJRTWOGj2%2BK1tf%2FPFpXNzVaf2ojO%2BKOwcEvTpva%2FPOG6c1EmNrUMqWhpRkIfcaHKAN0OZ81eEfOGnzxWQOjb0jBFAZx%2FC%2BzhmCNsJ9hQWsvOLVn0n5GBm1eUrt%2FzK5jR21o%2FOiJKy9AhwzKa%2F6alefjSoYJlXV2dVyL7IwUqpp%2BQes1ytH2RjTouvnWlnFKMOP2oSGVpeD1c2ZST4ByefGmpvMavgVOruA1XMnTC0emC1p6V0B9A0u1np977PkV5qi9zXh%2BBQ8XJOgmziYWsLhqD%2B1vHQZzli2Dxi8VWsCcbXDIRM6dEpOdxEnL%2BCQocxLLTDtnDWdWTT4Wyh0nAU7ot8Herhf%2F%2FuZLf5xv0ulUfvGjOONEDrXMYEgzK%2BCtE9qVsXpQVixvbB7mnLQ8CVqeut5Qc%2F0zNdcJKk9oH6byMk5M5VGJGk2mO108BE7wQmekxuJwGFF%2Bvs6WAeDL0umKLHa6drMgI7HQX0YznaWSNBddcwhCLotpRQ5tBcd%2BThplmiAy%2BBMMx2M6XcOLuERnVGvx%2B3WnH9vn31Wm9Cv3oTPQhPGbvaRDW9Q9dstdd%2FXVrfR7t8jpaBvqQuejTSZZXeCR145%2B8%2B1PDivZbnPyN%2BhT3SphMXhgNARhQWRMoMKEHQ6%2FX19RkWu3V%2BXr9aEchzvgiMYCATCbfxaNmc3YJNDOmfLEZnDT4VwQvFNiQupwHj45Cp00iOdT56kG4bniI7dDo6KTeT2fSk%2BLtyhf7dl5pPfHLSgb4QUvT7nsi2%2BR%2BbhTt2fL%2BU90tDx99FwN5Pu4fbWMBnC3%2FZprdiD9%2FciByqY1XcvYaf26naXlbOCeHGf7BhavuJhFHD0h%2FFXwSAVgZP0Zi5ozAMh6jE0ZWF4vsh39sg5pyx2NKqQzEZ2XGU%2BdFNAgrdc1Ne977elTUafn6kbhr2ed0XJ29tMLqh5sYBENqFX4M4lKD8Q9ehmS1eqmkUWyR8ay7CDxvRTYHVKNZ7qk8YhEdy1YcOklCy%2B67Pqa0tKaiorSGvGlCzavv%2BiCDZu7ykKhsrKqKkDwa%2BHPgkEygQuqIm4KNEUEQjLdBhvobPTrYvM6MzavFyCQ9fpZmoNENQebXw6qkISXvbF5mNVHiE23yjF6xRM27knfvXTUtKZoET%2B%2FfAk7F%2Buray7vKyjOr%2BKHAr4bGHqI3IN7%2BG5S%2BAS7SU0nbeih999Xlbp%2FqtQllG7Sj%2Fp4jIw7kiaIOqTTySBou5KZB5gLq7jGWhvCumKTs7N6sN5L%2Bp1zkG2h8t3HkHQFCVwRmQhIknSCRC8wvD8WUrffQHtNwbWDkz3iI84XlPdRySFI3luLeVIwEfnuWhIEtNuffHstwOzeZBl%2F%2BgzwRczUIGsiggSSZNFlkHRtI0Z%2BoT8E%2BbOoWSnwxY%2FoUzVPdILhSZyRP8ezp2Vz%2BE4SGJn%2FndpNDXwrMFMaMYjsRi%2BqN9Luoz60qB5QH885cqO31JNM8Ua1DBJFgVlJkOt5SRihMGIaeQcIpN7Ap91gROGgt0eWkkvbi2wunXrfKIyCdLA9wszuRplAgHssUq3uc6%2FavnXvvku37cGf9hzou3r%2FLbcAELbTizQXhfm75mXsYF6m6kEvys4gbKuXAofMQuS5LUhtbJnmP9AJy8gdX3yp56m7v%2BAps89kZzPacGPqPmctKUf%2BVkA7vpHbtCsijrgDV9RLQAg9pa0JI9VZmsxW0W%2FVN5vqlE12xKZeO24nRzp2bfoHPRPEf7z2SBs4vvHEBm8ApCxj83oe25YVSSeAEcaCFtqW8B8j5EX48mN%2F%2FIKMjge2AeK7BW0S%2B6EYdkQaJaL3%2BXI8RW5ntmywWIrSafaLika5cnP12dklBpdLzpRy83Knx0heRt66PJxOMvMy82yFPiiEabFCndlkMzXHbNp2YiNNoxZenyxzKUghO%2FCtQOhvro%2FH5DgKdA420DrVfS4oWELdb%2F7qWvq7BuL7XXhXXu9CVyrtGKN5yj0hZNq9ecn93ynPj9q6VMBLtvjQpG%2Be6ps7ebnwys5f3ucNFDzwTXgIxqK0Tx5wFVff9zVyT%2F%2FQ4%2BXsWgfzjp%2B0n6MTYDbdHRriMbs%2FSh7wQyNfQ04lboD45x8nfd7MPgcMBhzF34tPQRpYGbthFXUmWnBEBixim90k62TJikTRaiW6PJLPDTwBLSYu4RpNwn%2B8DhpfWI1CfA%2BzWrZnHP5%2BzefKBrTh0zXKHkmuzliH39q3rwfXHT%2FUN3Nu1gWuZ9Wn05u0pyuGRuJWn14KAMTT4QTpzcPp0q6k3PF0dS8BvtMDAcsjIIiIQGKXQLYPAt8FgTU2uvZ8EQDruB3sL%2FEV7krVDmZIWNNupYoPkxTdQ3NGKoYYgS4mKQ4q76sKS0JxHADfqZupKbq4gq9wuaT6%2FwCVeR0IAAAAAQAAAAEZmiehT9dfDzz1AAkIAAAAAADJQhegAAAAAMnoSqH7DP2oCo0IjQABAAkAAgAAAAAAAHgBY2BkYODo%2FbuCgYGr9zfPv0quXqAIKrgJAJZXBsIAeAFtkQOsGEEQhv%2Fbnd272rZtG0Ft27ZtW1G9dYMiamrbZlgrqN17M89K8uVfTna%2FoRs4AwCUGVBCU0zQl7DAlEIZWoPOfhXUs0BbVQAL1CG0ZepQd9STPdUW9dQ61FGN%2BU5LpOW1pswUpmU0hZj%2BTGOmWnQ2lPNyV2rEoO%2FA%2BmUw0CwATG8cNjkwyXzEYZrG9Of5NUyy%2BXBY7Q4Hm9a8tgCH%2FWU4bOcwPfmsjc7GvDcYPWk7StjU2G8qAf5xwHQE6D%2BzHRXUbqzi96bmrEQNEeim4V965jWnB%2Bho0sNRHnTn7E5H0V3nQAlaAGsawqkxWKfGhDPoO2Ts%2FGdwsk5fIecd011vh9O%2FOaegHO9toBWAfYLM5JBSxvoNquliyEeDvUucbeXvMd55vIqRtTGMJTnzAkP5bdnsXvTX6VGOPkbfYe%2ByRgh%2F6xHoLms6QDmmlvyFPThTB2PEtbczfMbr3XUu1JD7fmqUjaYre68jzpPD3wJIH6QH0RyQ5L6Ui%2FGeGFqDOZLiPj7iXnpkDsKJ5%2BTwO3LmEe8JYecb2fcazoXMC%2FEd4z0J7EFS3MdH3EuPJJX07gom%2Bff4%2FDMcpS1ee85bBLQNGO84cgiqPerpVcghUBEeK%2FS1jzBBfUZbwUv5X%2F7bkOlslqCEwJ5TBw4lBFsBJdRuHA4vYk%2Fown8RLYvLrQAAeAEc0jWMJFcQxvFnto%2F5LjEvHrdbmh2Kji9aPL4839TcKPNAa6mlZUyOmZk6lzbPJ3bo56%2F%2FCz%2BVaqqrat5rY8x7xnzxl3nvo%2B27jFnz8c%2FmI9Nmh2XBdMsilrBitsnD9rI8aiN5DI%2FjSftC9mIf9pMfIB4kHiI%2BhWfQY5aPAYYYYYwpcyfpMMX0aZzBWZzDeVygchGXcBlX8ApexWt4HW%2FgLbzNbnfwLt7DJ%2Fp0TX4%2BUucji1hCnY%2FU%2BcijVB7D46jzkb3Yh%2F3kB4gHiYeIT%2BEZ9JjlY4AhRhhjytxJOkwxfRpncBbncB4XqFzEJVzGFbyCV%2FEaXscbeAtvs9sdvIv3cjmftWavuWs2mg6byt3ooIsFOyx77Kos2kiWsIK%2FUVPDOjawiQmO4CgdxnAcJzClz2PVbNKsy2ZzvoncjQ66qE2kNpHaRJawgr9RU8M6NrCJCY6gNpFjOI4TmNIn36TNfGSH5RrssKtyN%2B59b410iF0sUFO0l2UJtY%2F8jU9rWMcGNjHBEUypf0z8mm7vZLvZaC%2FLzdhmV2XBvpBF25IlLJOvEFfRI%2BNjgCFGGGNK5Rs6Z7Ij%2F45yNzro4m9Ywzo2sIkJjuBj2ZnvLDdjGxntLLWzLGGZfIW4ih4ZHwMMMcIYUyq1s8xkl97bH0y3JkZyM36j%2F%2B58rvTQxwBDjDDGNzyVyX35Ccjd6KCLv2EN69jAJiY4go%2Flfr05F%2BUa7CCzGx10sYA9tiWLxCWs2BfyN%2BIa1rGBTUxwBEfpMIbjOIEpfdjHvGaTd9LJb0duRp2S1O1I3Y4sYZl8hbiKHhkfAwwxwhhTKt%2FQOZPfmY3%2F%2FSs3Y5tNpTpL9ZQeGR8DDDHCGN%2FwbCbdfHO5GbW51OZSm8sSlslXiKvokfExwBAjjDGlUpvLTBY0K5KbiDcT672SbXZY6k7lbnTQxQI1h%2B1FeZTKY3gcT2KvTWUf9pMZIB4kHiI%2BxcQzxGfpfA7P4wW8yG4eT%2FkYYIgRxvgb9TWsYwObmOAITlI%2Fxf7TOIOzOIfzuEDlIi7hMq7gFbyK1%2FA63sBbeJtvdwfv4j28zyaP8QmVL%2FimL%2FENJ5PJHt3RqtyMbbYlPfQxwBAjjPEN9ZksqkMqN6PuV7bZy7LDtuRudNDFwzx1FI%2FhcTzJp73Yh%2F3kB4gHiYeIT%2BEZ9JjlY4AhRhjjb1TWsI4NbGKCIzjJlCmcxhmcxTmcxwVcxCVcxhW8glfxGl7HG3gLbzPxDt7Fe%2FgY%2F%2Begvq0YCAEoCNa1n%2BKVyTUl3Q0uIhoe%2B3DnRfV7nXGOc5zjHOc4xznOcY5znOMc5zjHOc5xjnOc4xznOMc5znGOc5zjHOc4xznOcY5znOMc5zjHOc5xjnOc4xznOMc5znGOc5zjHOc4xznOcY5znOM8XZouTZemS1OAKcAUYAowBZgCTAHm3x31O7p3vNf5c1iXeBkEAQDFcbsJX0IqFBwK7tyEgkPC3R0K7hrXzsIhePPK%2F7c77jPM1yxSPua0WmuDzNcuNmuLtmq7sbyfsUu7De%2Fxu9fvvvDNfN3ioN9j5pq0ximd1hmd1TmlX7iky7qiq7qmG3pgXYd6pMd6oqd6pud6oZd6pdd6p%2Ff6oI%2F6pC%2FKSxvf9F0%2F1LFl1naRcwwzrAu7AHNarbW6oEu6rCu6qmu6ob9Y7xu%2BkbfHH1ZopCk25RVrhXKn4LCO6KiOGfvpd%2BR3is15xXmVWKGRptgaysQKpUwc1hEdVcpEysTI7xTbKHMcKzTSFDtCmVihkab4z0FdI0QQBAEUbRz6XLh3Lc7VcI%2FWN54IuxXFS97oH58%2BMBoclE1usbHHW77wlW985wcHHHLEMSecsUuPXMNRqfzib3pcllj5xd%2B0lSVW5nNIL3nF6389h%2BY5NG3Thja0oQ1taEMb2tCGNrQn%2BQwjrcwxM93gJre4Y89mvsdb3vGeD3zkE5%2F5wle%2B8Z0fHHDIEceccMaOX67wNz3747gObCQAQhCKdjlRzBVD5be7rwAmfOMQsUvPLj279OzSYBks49Ibl97In%2FHCuNDGO%2BNOW6qlWqqlWqqlWqqlWqqYUkwpphTzifnEfII92IM92IM92IM92IM92IM92I%2FD4%2FA4PA6Pw%2BPwODwOj8M%2Ff7kaaDXQyt7K3mqglcCVwNVAq4FWA60GWglZCVkJWQlZCVkJWQlZDbQyqhpoNdAPh3NAwCAAwwDM%2B7b2sg8kCjIO4zAO4zAO4zAO4zAO4zAO4zAO4zAO4zAO4zAO4zAO47AO67AO67AO67AO67AO67AO67AO67AO67AO67AO67AO63AO53AO53AO53AO53AO53AO53AO53AO53AO53AO53AO5xCHOMQhDnGIQxziEIc4xCEOcYhDHOIQhzjEIQ5xiEMd6lCHOtShDnWoQx3qUIc61KEOdahDHepQhzrUoQ6%2Fh%2BP6RpIjiKEoyOPvCARUoK9LctP5ZqXTop7q%2F6H%2F0H%2B4P9yfPz82bdm2Y9ee%2FT355bS3%2FdivDW9reFtDb4beDL0ZejP0ZujN0JuhN0Nvht4MvRl6M%2FRm6M3w1of3PVnJSlaykpWsZCUrWclKVrKSlaxkJStZySpWsYpVrGIVq1jFKlaxilWsYhWrWMUqVrGa1axmNatZzWpWs5rVrGY1q1nNalazmtWsYQ1rWMMa1rCGNaxhDWtYwxrWsIY1rGENa1nLWtaylrWsZS1rWcta1rKWtaxlLWtZyzrWsY51rGMd61jHOtaxjnWsYx3rWMc61rEeTf1o6kdTP%2F84rpMqCKAYhmH8Cfy2JjuLCPiYPDH1Y%2BrH1I%2BpH1M%2Fpn5M%2FZh6FEZhFEZhFEZhFEZhFEZhFFZhFVZhFVZhFVZhFVZhFVbhFE7hFE7hFE7hFE7hFE7hFCKgCChPHQFlc7I52ZxsTgQUAUVAEVAEFAFFQBFQBBQBRUARUAQUAUVAEVAEFAFFQBFQti5bl63L1mXrsnXZuggoAoqAIqAIKAKKgCKgCCgCioAioAgoAoqAIqAIKAKKgCKgCCgCyt5GQBFQBPTlwD7OEIaBKAxSOrmJVZa2TsJcwJ6r0%2F%2B9sBOGnTDshOF%2BDndyXG7k7vfh9%2Bn35fft978Thp2wKuqqqKtarmq58cYbb7zzzjvvfPDBBx988sknn3zxxRdfPHnyVPip8FPhp8JPhZ8KP78czLdxBDAMAMFc%2FbdAk4AERoMS5CpQOW82uWyPHexkJzvZyU52spOd7GQnu9jFLnaxi13sYhe72MVudrOb3exmN7vZzW52s8EGG2ywwQYbbLDBBnvZy172spe97GUve9nLJptssskmm2yyySabbLHFFltsscUWW2yxxX6%2B7P%2BrH%2Fqtf6%2B2Z3u2Z3u2Z3u2Z3u2Z3s%2BO66jKoYBGASA%2FiUFeLO2tqfgvhIgVkOshvj%2F8f%2FjF8VqiL8dqyG%2Bd4klllhiiSWWWGKJJY444ogjjjjiiCOO%2BPua0gPv7paRAHgBLcEDlNxQAADArI3Ydv7Vtm3btm3btm3btm3bD7VvBoIgLXVVqCf0ztXT9dzd3j3cvcX90CN5Snmae%2Fp45np2e356gbeH94HP8Q3x3feH%2FX38NwJwoHigQ2Ba4GBQCK4NfgxVDE0OnQr7w1nCI8P7wi8jdqR4ZGzkRDQSLRmdH%2F0UqxTrEVsbux%2FPHe8b3xh%2FlgglzESJRJfE6MS6ZChZJzkj%2BRouCA9GJKQuMhI5hsZRHR2A7kZ%2FYZWxldhtPDPeFd%2BIPybyE0OIy2SIrEy2IneSX8mvFKB6UpfodPQYeiOTjmnK3GOzsCPYpexaLjdXiRvBHeJ%2B8BX5Lvxe%2FqOACmWEnsJ60SsyYjqxiLhE3CoeE6%2BLL8RvUlRqJXWThkszpJXSbjkq83JaOZ9cXm4gd5IXKZACK4qSSSmiVFWmq0lVUtOr%2BdXyagO1oxbRSM3UsmnFtOpaC62nNkqbo7M60HPppfXaemu9j77X4IwUI49RxqhrtDWOGzeM92Y985lFWWWtcdZia4d10%2FpiU3YZu6%2B91j7rME5xp5szGVAgDcgBioDhYDpYDjaDE%2BAmeAW%2Bp8R%2FA5ajfCcAAAABAAAA3QCKABYAWAAFAAIAEAAvAFwAAAEAAQsAAwABeAF9jgNuRAEYhL%2FaDGoc4DluVNtug5pr8xh7jj3jTpK18pszwBDP9NHTP0IPs1DOexlmtpz3sc9iOe9nmddyPsA8%2BXI%2BqI1COZ%2FkliIXhPkiyDo3vCnG2CaEn0%2B2lH%2BgmfIvotowZa3769ULZST4K%2BcujqTb%2Fj36S4w%2FQmgDF0tWvalemNWLX%2BKSMBvYkhQSLG2FZR%2BafmERIsqPpn7%2ByvxjfMlsTjlihz3OuZE38bTtlAAa%2FTAFAHgBbMEDjJYBAADQ9%2F3nu2zbtm3b5p9t17JdQ7Zt21zmvGXXvJrZe0LA37Cw%2F3lDEBISIVKUaDFixYmXIJHEkkgqmeRSSCmV1NJIK530Msgok8yyyCqb7HLIKZfc8sgrn%2FwKKKiwIooqprgSSiqltDLKKqe8CiqqpLIqqqqmuhpqqqW2Ouqqp74GGmqksSaaaqa5FlpqpbU22mqnvQ466qSzLrrqprs9NpthprNWeWeWReZba6ctQYR5QaTplvvhp4VWm%2BOyt75bZ5fffvljk71uum6fHnpaopfbervhlvfCHnngof36%2BGappx57oq%2BPPpurv34GGGSgwTYYYpihhhthlJFGG%2BODscYbZ4JJJjphoykmm2qaT7445ZkDDnrujRcOOeyY46444qirZtvtnPPOBFG%2BBtFBTBAbxAXxQYJC7rvjrnv%2FxpJXmpPDXpqXaWDg6MKZX5ZaVJycX5TK4lpalA8SdnMyMITSRjxp%2BaVFxaUFqUWZ%2BUVQQWMobcKUlgYAHQ14sAAAeAFFSzVCLEEQ7fpjH113V1ybGPd1KRyiibEhxt1vsj3ZngE9AIfgBmMR5fVk8qElsRjHOHAYW%2BQwyumxct4bKxXkWDEvx7JjdszQNAZcekzi9Zho8oV8NCbnIT%2FfEXNRJwqmlaemnQMbN8E1OE7Mzb%2FP%2F8xzKZrEMA2hl3rQATa0Uxs2bN%2B2f8M2AEpwj5yQBvklvJ3AqRcEaMKrWq%2F19eWakl7NsZbyJoNblqlZc7KywcRbRnBjc00FeF6%2Fenoi05EcG62tsXhkPcdk87BHVC%2BZXleUPrOsUHaUI2tb4y%2F8OwbsTEAJAA%3D%3D%29%20format%28%22woff%22%29%7Dbody%7Bmargin%2Dtop%3A26px%3Bfont%2Dsize%3A16px%7D%2A%2C%3Aafter%2C%3Abefore%7B%2Dwebkit%2Dbox%2Dsizing%3Aborder%2Dbox%3B%2Dmoz%2Dbox%2Dsizing%3Aborder%2Dbox%3Bbox%2Dsizing%3Aborder%2Dbox%7Darticle%2Caside%2Cdetails%2Cfigcaption%2Cfigure%2Cfooter%2Cheader%2Chgroup%2Cnav%2Csection%7Bdisplay%3Ablock%7Dhtml%7Bfont%2Dsize%3A100%25%3B%2Dwebkit%2Dtext%2Dsize%2Dadjust%3A100%25%3B%2Dms%2Dtext%2Dsize%2Dadjust%3A100%25%7Da%3Afocus%7Boutline%3Athin%20dotted%20%23333%3Boutline%3A5px%20auto%20%2Dwebkit%2Dfocus%2Dring%2Dcolor%3Boutline%2Doffset%3A%2D2px%7Da%3Aactive%2Ca%3Ahover%7Boutline%3A0%7Dsub%2Csup%7Bposition%3Arelative%3Bfont%2Dsize%3A75%25%3Bline%2Dheight%3A0%3Bvertical%2Dalign%3Abaseline%7Dsup%7Btop%3A%2D%2E5em%7Dsub%7Bbottom%3A%2D%2E25em%7Dblockquote%7Bmargin%3A0%7Dimg%7Bmax%2Dwidth%3A100%25%3Bheight%3Aaut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<h1 class="title toc-ignore entry-title">Lugar de mulher é na cozinha?</h1>
<h3 class="author">Maria Elisa Rocha Couto Gomes</h3>
<h3 class="date">28/10/2021</h3>
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<div id="prefácio" class="section level2">
<h2>Prefácio</h2>
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<p>Este relatório foi produzido como trabalho final do curso “R para Ciências de Dados I”, organizado pela <a href="https://curso-r.com/"><em>Curso-R</em></a>.</p>
<p>Considerando que nós, alunos do curso, podíamos escolher o tema e os dados que fossem de nossa preferência, aproveitei esta oportunidade para analisar a divisão das tarefas domésticas e de cuidado não remuneradas sob uma perspectiva diferente daquela que tem me guiado em minha dissertação de mestrado. Enquanto, nela, tenho me dedicado à análise dos determinantes da alocação do tempo de homens e mulheres, em casais heterossexuais e homoafetivos, na realização destas tarefas, neste relatório, me voltarei às crenças e expectativas de gênero, alguns dos principais fatores que moldam nossos comportamentos perante os afazeres domésticos e de cuidado.</p>
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<div id="introdução" class="section level2">
<h2>Introdução</h2>
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<p>Dito isto, gostaria de começar com a seguinte provocação: “lugar de mulher é na cozinha”. Arrisco dizer que todo brasileiro, em algum momento de sua vida, já se deparou com este ditado popular. Suas poucas palavras servem como uma espécie de lembrete para o que significa “ser mulher” em uma sociedade altamente generificada: realizar as tarefas domésticas e de cuidado não remuneradas.</p>
<p>Tendo em mente as importantes mudanças que, desde a segunda metade do século XX, temos observado na família, principalmente, naquilo que diz respeito ao aumento da participação das mulheres no mercado de trabalho, neste relatório, tentarei avaliar o quão pertinente este ditado popular é entre mulheres e homens brasileiros casados no começo do século XXI. Em outras palavras, meu principal objetivo é responder à seguinte pergunta: no Brasil do século XXI, lugar de mulher é na cozinha ou onde ela quiser?</p>
<p>Procurando respondê-la, utilizarei dados do módulo <a href="https://www.gesis.org/en/issp/modules/issp-modules-by-topic/family-and-changing-gender-roles/2002"><em>Family and Changing Gender Values</em></a>, coletados em 2002 como parte do <em>International Social Survey Programme</em> (ISSP). Além desta introdução, o presente trabalho contém as seguintes seções:</p>
<ul>
<li><p>Em <strong>“Divisão Sexual do Trabalho: um obstáculo à verdadeira”Revolução de Gênero”?“</strong>, discutirei brevemente a literatura sociológica sobre a divisão dos trabalhos domésticos e de cuidado não remunerados, dando maior atenção à hipótese derivada da perspectiva de gênero, uma vez que esta será a principal hipótese a ser abordada neste relatório.</p></li>
<li><p>Em <strong>“Metodologia”</strong>, apresentarei o banco de dados e as variáveis utilizadas para a realização da análise aqui pretendida. Além disto, descreverei a estratégia metodológica adotada.</p></li>
<li><p>Em <strong>“Resultados”</strong>, realizarei uma breve descrição acerca do perfil da amostra selecionada e os principais resultados obtidos durante a execução deste trabalho. Como também possuía o intuito de aprender a programar em R, os códigos também serão apresentados.</p></li>
<li><p>Em <strong>“Considerações finais”</strong>, tecerei comentários gerais sobre aquilo que foi descoberto durante a elaboração deste relatório.</p></li>
<li><p>Por fim, na seção <strong>“Para saber mais: dicas de leituras</strong>”, listarei algumas referências bibliográficas que, embora não tenham sido devidamente citadas neste trabalho, têm guiado meus estudos sobre a divisão dos afazeres domésticos e de cuidado para aqueles que tiverem interesse em aprender mais sobre este tema.</p></li>
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<div id="divisão-sexual-do-trabalho-um-obstáculo-à-verdadeira-revolução-de-gênero" class="section level2">
<h2>Divisão Sexual do Trabalho: um obstáculo à verdadeira “Revolução de Gênero”?</h2>
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<p>A maioria dos estudos dedicados à investigação do trabalho doméstico não remunerado discute como é feita sua distribuição entre os membros de famílias formadas por casais heterossexuais. A partir de medidas, como, por exemplo, a quantidade de horas que as pessoas dedicam aos afazeres domésticos, tais pesquisas procuram identificar quais são os fatores que levam aos desequilíbrios entre seus membros.</p>
<p>Dentre as principais hipóteses explicativas disponíveis na literatura sobre este tema, observa-se a tendência de se atribuir suas causas às diferenças existentes entre estes homens e mulheres, como, por exemplo, de poder de negociação, renda, escolaridade, tempo livre disponível e, até mesmo, aos momentos do ciclo de vida em que se encontram. Tais abordagens recebem, respectivamente, os seguintes nomes: teoria da barganha, teoria do capital humano, hipótese da disponibilidade de tempo e perspectiva do ciclo de vida.</p>
<p>Ao comparar os resultados destes estudos, é possível observar um ponto comum: as mulheres, geralmente, se dedicam muito mais às tarefas domésticas do que seus respectivos maridos. Tem-se, portanto, que todas estas abordagens se mostram insuficientes se não consideramos o sistema de normas e expectativas de gênero. Este consistiria, justamente, nos aspectos psicológicos e sociológicos constituintes da identidade de gênero. Em outras palavras, podemos dizer que tal sistema se refere a um conjunto de obrigações decorrentes do “ser homem” e do “ser mulher”, em sociedades em que tais categorias são rigidamente separadas e controladas.</p>
<p>Dentre elas, temos as obrigações decorrentes da divisão sexual do trabalho, que consiste em um fenômeno histórico e social por meio do qual se definiu a divisão social do trabalho, tendo como base as relações entre os sexos. Os principais aspectos deste fenômeno seriam a separação e a hierarquização. O primeiro aspecto, portanto, se refere à própria distinção dos trabalhos entre aqueles que, pertencentes à esfera produtiva, deveriam ser realizados por homens, e aqueles que, pertencentes à esfera reprodutiva, deveriam ser realizados por mulheres. Já o segundo, por sua vez, se traduz na ideia de que os “trabalhos de homem” são considerados superiores aos “trabalhos de mulher”. No entanto, é importante observar que, se, por um lado, a divisão das tarefas domésticas é determinada conforme as normas de gênero da sociedade, por outro, é por meio de sua realização que os papéis, associados a elas, são demonstrados e reafirmados.</p>
<p>Embora muito tenha sido conquistado no Século XX, as mulheres continuam realizando grande parte do trabalho doméstico e de cuidado não remunerados. Talvez, o descompasso entre aquilo que, por elas, fora conquistado na esfera pública e a persistência das desigualdades na esfera privada, especialmente, as que dizem respeito à divisão das tarefas domésticas e cuidado, seja o principal entrave à igualdade de gênero. Tal constatação levou diversos autores a afirmarem que, durante este período, houve, na verdade, uma revolução “incompleta” ou “lenta” de genêro. Ambas possuindo a intenção de nos remeter à ideia de que, se, por um lado, foi promovida por mudanças significativas no comportamento das mulheres na esfera pública, por outro, é desacelarada pela persistência dos comportamentos tradicionais dos homens na esfera privada.</p>
<p>Este é, portanto, o “arcabouço teórico e empírico”, a partir do qual, ao longo deste trabalho investigarei a que pé andavam, em 2002, as principais crenças que, supostamente, servem de base para tais comportamentos.</p>
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<div id="metodologia" class="section level2">
<h2>Metodologia</h2>
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<p>Nesta seção, apresentarei, em linhas gerais, o banco de dados e a estratégia metodológica utilizados para a realizaçao deste trabalho.</p>
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<div id="banco-de-dados" class="section level3">
<h3>Banco de dados</h3>
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<p>Neste relatório, utilizei dados do módulo <em>Family and Changing Gender Values</em>, coletados em 2002 pelo <em>International Social Survey Programme</em> (ISSP), associação internacional independente, cujo principal objetivo é coletar periodicamente, em 57 países membros, informações sobre diferentes temas socialmente relevantes.</p>
<p>O módulo, aqui utilizado, contém informações sobre os valores familiares e de gênero dos seguintes países: Alemanha, Austrália, Austria, Bélgica, Brasil, Bulgaria, Chile, Chipre, Dinamarca, Eslovênia, Eslováquia, Espanha, Estados Unidos da América, Filipinas, Finlândia, França, Holanda, Húngria, Irlanda, Irlanda do Norte, Israel, Japão, Letônia, México, Noruega, Nova Zelândia, Pôlonia, Portugal, Reino Unido, República Tcheca, Rússia, Suécia, Suíça e Taiwan.</p>
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<div id="amostra-selecionada" class="section level3">
<h3>Amostra selecionada</h3>
<div style="text-align: justify">
<p>Para o módulo <em>“Family and Changing Gender Values”</em>, o ISSP entrevistou46638pessoas, com mais de 18 anos de idade, nos países anteriormente citados, das quais 2000 eram brasileiras. No entanto, neste relatório, apenas considerei os casos em que, além de brasileiros, os indivíduos também eram casados ou cohabitavam com seus respectivos cônjuges, sendo importante observar que, nesta pesquisa, apenas foram considerados casais heterossexuais. Uma vez que tais filtros foram feitos, restaram 866 casos na amostra.</p>
<p>Tal seleção se deu por dois motivos principais, sendo eles:</p>
<ol style="list-style-type: decimal">
<li><p>O fato de o Brasil se destacar enquanto um país em que, além de os valores familiares e de gênero permanecerem muito tradicionais, há elevadíssimas desigualdades de gênero e também severa escassez de políticas públicas por meio das quais o Estado busque contribuir para a redução de tais desigualdades, auxiliando, por exemplo, no provimento de cuidado para pessoas dependentes;</p></li>
<li><p>Na literatura sobre este tema, defende-se a ideia de que o casamento é a instituição generificada por excelência. Ou seja, segundo diversos autores, fazer parte de um casal heterossexual influenciaria, consideravelmente, os valores familiares e de gênero dos indivíduos.</p></li>
</ol>
</div>
</div>
<div id="estratégia-metodológica" class="section level3">
<h3>Estratégia metodológica</h3>
<p>Neste relatório, apresentarei apenas estatísticas descritivas a respeito da amostra selecionada. Considerando que seu perfil sociodemográfico pode vir a influenciar os resultados que obtivermos a respeito dos comportamentos e crenças de gênero de homens e mulheres, em primeiro lugar, analisarei as seguintes variáveis:</p>
<ul>
<li><p>Sexo;</p></li>
<li><p>Idade;</p></li>
<li><p>Cor/raça;</p></li>
<li><p>Anos de escolaridade;</p></li>
<li><p>Situação de emprego atual;</p></li>
<li><p>Horas trabalhadas semanalmente;</p></li>
<li><p>Rendimento;</p></li>
<li><p>Renda familiar;</p></li>
<li><p>Número de filhos de 0 a 6 anos de idade que residem no mesmo domicílio;</p></li>
<li><p>Número de filhos com 7 anos de idade ou mais que residem no mesmo domicílio.</p></li>
</ul>
<p>Em seguida, observarei em que medida homens e mulheres concordam ou discordam das seguintes frases:</p>
<ul>
<li><p>“Trabalhar é bom, mas o que a maioria das mulheres realmente quer é ter um lar e filhos”;</p></li>
<li><p>“Ser dona de casa é tão gratificante quanto trabalhar fora”;</p></li>
<li><p>“O trabalho do homem é ganhar dinheiro, o trabalho da mulher é cuidar da casa e da família”;</p></li>
<li><p>“Os homens deveriam assumir mais trabalhos domésticos do que fazem atualmente”;</p></li>
<li><p>“Os homens deveriam cuidar mais das crianças do que cuidam atualmente”;</p></li>
</ul>
<p>Por fim, também analisarei como os entrevistados e seus respectivos cônjuges dividem os afazeres domésticos e quais são suas percepções a respeito desta dinâmica, a frequência com que esta é alvo de conflitos e sua satisfação (ou insatisfação) com sua vida familiar. Isto será feito a partir das seguintes perguntas:</p>
<ul>
<li><p>“Na casa do senhor(a), quem faz as seguintes coisas:</p>
<ul>
<li><p>Lava e passa roupa;</p></li>
<li><p>Faz pequenos consertos na casa;</p></li>
<li><p>Cuida dos familiares doentes, velhos e incapacitados;</p></li>
<li><p>Compra comida (faz supermercado);</p></li>
<li><p>Limpa a casa;</p></li>
<li><p>Cozinha (prepara a comida);</p></li>
<li><p>Lava os pratos”;</p></li>
</ul></li>
<li><p>“Em média, qual o número de horas por semana o senhor(a) gasta fazendo trabalhos domésticos, sem incluir cuidar das crianças e se divertir”;</p></li>
<li><p>“Qual das seguintes opções melhor se aplica à divisão do trabalho doméstico entre seu(sua) cônjuge e o(a) senhor(a)?</p></li>
<li><p>“Com que frequência, o senhor(a) e seu(sua) cônjuge discordam da divisão do trabalho de casa?”;</p></li>
<li><p>“Considerando sua vida familiar, você está?”.</p></li>
</ul>
</div>
</div>
<div id="resultados" class="section level2">
<h2>Resultados</h2>
<div style="text-align: justify">
<p>Nesta seção, serão apresentados os principais resultados obtidos.</p>
<p>Em um primeiro momento, farei uma breve descrição do perfil sóciodemográfico da amostra selecionada, explorando as seguintes características: sexo, idade, cor/raça, escolaridade, situação de ocupação, rendimento, número de filhos residentes no mesmo domicílio.</p>
<p>Em seguida, explorarei dados referentes aos valores familiares e de gênero e à divisão dos afazeres domésticos segundo o sexo dos entrevistados.</p>
</div>
<div id="uma-breve-descrição-da-amostra" class="section level3">
<h3>Uma breve descrição da amostra</h3>
<div id="sexo" class="section level4">
<h4>Sexo</h4>
<div style="text-aling: justify">
<p>Como é possível observar a partir da leitura da Figura 1, em nossa amostra, 50,46% dos entrevistados eram mulheres, enquanto 49,54% eram homens. Isto nos indica que a distribuição relativa dos entrevistados segundo seu sexo segue aquilo que era esperado, de acordo com a presença de homens e mulheres na população brasileira em geral.</p>
</div>
<div class="sourceCode" id="cb1"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb1-1"><a href="#cb1-1" aria-hidden="true" tabindex="-1"></a><span class="co"># Distribuição relativa de brasileiros casados por sexo</span></span>
<span id="cb1-2"><a href="#cb1-2" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb1-3"><a href="#cb1-3" aria-hidden="true" tabindex="-1"></a>sexo_grafico <span class="ot"><-</span> brasil_casados_vs <span class="sc">%>%</span></span>
<span id="cb1-4"><a href="#cb1-4" aria-hidden="true" tabindex="-1"></a> <span class="fu">group_by</span>(sexo) <span class="sc">%>%</span></span>
<span id="cb1-5"><a href="#cb1-5" aria-hidden="true" tabindex="-1"></a> <span class="fu">summarise</span>(<span class="at">n =</span> <span class="fu">n</span>()) <span class="sc">%>%</span></span>
<span id="cb1-6"><a href="#cb1-6" aria-hidden="true" tabindex="-1"></a> <span class="fu">mutate</span>(<span class="at">freq_sexo =</span> n <span class="sc">/</span> <span class="fu">sum</span>(n)) <span class="sc">%>%</span></span>
<span id="cb1-7"><a href="#cb1-7" aria-hidden="true" tabindex="-1"></a> <span class="fu">mutate</span>(<span class="at">freq_sexo =</span> freq_sexo <span class="sc">*</span> <span class="dv">100</span>) <span class="sc">%>%</span></span>
<span id="cb1-8"><a href="#cb1-8" aria-hidden="true" tabindex="-1"></a> <span class="fu">mutate</span>(<span class="at">freq_sexo =</span> <span class="fu">round</span>(freq_sexo, <span class="dv">2</span>)) <span class="sc">%>%</span></span>
<span id="cb1-9"><a href="#cb1-9" aria-hidden="true" tabindex="-1"></a> <span class="fu">ungroup</span>() <span class="sc">%>%</span></span>
<span id="cb1-10"><a href="#cb1-10" aria-hidden="true" tabindex="-1"></a> <span class="fu">ggplot</span>() <span class="sc">+</span></span>
<span id="cb1-11"><a href="#cb1-11" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_col</span>(<span class="fu">aes</span>(<span class="at">x =</span> sexo, <span class="at">y =</span> freq_sexo, <span class="at">fill =</span> sexo), <span class="at">show.legend =</span> <span class="cn">TRUE</span>) <span class="sc">+</span></span>
<span id="cb1-12"><a href="#cb1-12" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_label</span>(<span class="fu">aes</span>(<span class="at">x =</span> sexo, <span class="at">y =</span> freq_sexo,</span>
<span id="cb1-13"><a href="#cb1-13" aria-hidden="true" tabindex="-1"></a> <span class="at">label =</span> freq_sexo)) <span class="sc">+</span></span>
<span id="cb1-14"><a href="#cb1-14" aria-hidden="true" tabindex="-1"></a> <span class="fu">scale_fill_manual</span>(</span>
<span id="cb1-15"><a href="#cb1-15" aria-hidden="true" tabindex="-1"></a> <span class="at">labels =</span> <span class="fu">c</span>(<span class="st">"Masculino"</span>, <span class="st">"Femino"</span>),</span>
<span id="cb1-16"><a href="#cb1-16" aria-hidden="true" tabindex="-1"></a> <span class="at">values =</span> <span class="fu">c</span>(<span class="st">"lightblue3"</span>, <span class="st">"hotpink1"</span>)</span>
<span id="cb1-17"><a href="#cb1-17" aria-hidden="true" tabindex="-1"></a> ) <span class="sc">+</span></span>
<span id="cb1-18"><a href="#cb1-18" aria-hidden="true" tabindex="-1"></a> <span class="fu">labs</span>(</span>
<span id="cb1-19"><a href="#cb1-19" aria-hidden="true" tabindex="-1"></a> <span class="at">y =</span> <span class="st">"Frequência relativa"</span>,</span>
<span id="cb1-20"><a href="#cb1-20" aria-hidden="true" tabindex="-1"></a> <span class="at">fill =</span> <span class="st">"Sexo"</span>,</span>
<span id="cb1-21"><a href="#cb1-21" aria-hidden="true" tabindex="-1"></a> <span class="at">title =</span> <span class="st">"Figura 1- Distribuição relativa de brasileiros casados por sexo"</span>,</span>
<span id="cb1-22"><a href="#cb1-22" aria-hidden="true" tabindex="-1"></a> <span class="at">caption =</span> <span class="st">"Fonte: ISSP, 2002."</span></span>
<span id="cb1-23"><a href="#cb1-23" aria-hidden="true" tabindex="-1"></a> ) <span class="sc">+</span></span>
<span id="cb1-24"><a href="#cb1-24" aria-hidden="true" tabindex="-1"></a> <span class="fu">theme_minimal</span>()<span class="sc">+</span> </span>
<span id="cb1-25"><a href="#cb1-25" aria-hidden="true" tabindex="-1"></a> <span class="fu">theme</span>(</span>
<span id="cb1-26"><a href="#cb1-26" aria-hidden="true" tabindex="-1"></a> <span class="at">axis.title.x =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb1-27"><a href="#cb1-27" aria-hidden="true" tabindex="-1"></a> <span class="at">axis.ticks.x =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb1-28"><a href="#cb1-28" aria-hidden="true" tabindex="-1"></a> <span class="at">axis.title.y =</span> <span class="fu">element_text</span>(<span class="at">size =</span> <span class="dv">8</span>),</span>
<span id="cb1-29"><a href="#cb1-29" aria-hidden="true" tabindex="-1"></a> <span class="at">axis.text.x =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb1-30"><a href="#cb1-30" aria-hidden="true" tabindex="-1"></a> <span class="at">plot.title =</span> <span class="fu">element_text</span>(<span class="at">hjust =</span> <span class="fl">0.5</span>, <span class="at">size =</span> <span class="dv">12</span>, <span class="at">face =</span> <span class="st">"bold"</span>),</span>
<span id="cb1-31"><a href="#cb1-31" aria-hidden="true" tabindex="-1"></a> <span class="at">plot.caption =</span> <span class="fu">element_text</span>(<span class="at">hjust =</span> <span class="fl">0.5</span>)</span>
<span id="cb1-32"><a href="#cb1-32" aria-hidden="true" tabindex="-1"></a>)</span>
<span id="cb1-33"><a href="#cb1-33" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb1-34"><a href="#cb1-34" aria-hidden="true" tabindex="-1"></a><span class="fu">print</span>(sexo_grafico)</span></code></pre></div>
<p><img src="data:image/png;base64,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" /><!-- --></p>
</div>
<div id="idade" class="section level4">
<h4>Idade</h4>
<p>Já a Figura 2 contem a distribuição da idade dos brasileiros casados de acordo com seu sexo. Sendo assim, a partir dela, é possível perceber que, em nossa amostra, as mulheres são ligeiramente mais novas que os homens, uma vez que, para elas, a mediana desta variável foi, aproximadamente, 39 anos, enquanto, para os homens, foi 43 anos.</p>
<p>No entanto, considerando esta é uma medida extremamente sensível a valores discrepantes, é interessante ressaltar que, por um lado, o valor da mediana dos homens pode estar sendo influenciada pelo valor máximo de 85 anos encontrado na amostra. Por outro, a das mulheres pode estar sendo afetada pelo valor mínimo de 18 anos.</p>
<div class="sourceCode" id="cb2"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb2-1"><a href="#cb2-1" aria-hidden="true" tabindex="-1"></a><span class="co"># Distribuição dos brasileiros casados por idade, de acordo com seu sexo</span></span>
<span id="cb2-2"><a href="#cb2-2" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb2-3"><a href="#cb2-3" aria-hidden="true" tabindex="-1"></a>idade_sexo <span class="ot"><-</span> brasil_casados_vs <span class="sc">%>%</span> </span>
<span id="cb2-4"><a href="#cb2-4" aria-hidden="true" tabindex="-1"></a> <span class="fu">group_by</span>(sexo) <span class="sc">%>%</span> </span>
<span id="cb2-5"><a href="#cb2-5" aria-hidden="true" tabindex="-1"></a> <span class="fu">ggplot</span>() <span class="sc">+</span></span>
<span id="cb2-6"><a href="#cb2-6" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_boxplot</span>(<span class="fu">aes</span>(<span class="at">x =</span> sexo, <span class="at">y =</span> idade, <span class="at">fill =</span> sexo)) <span class="sc">+</span></span>
<span id="cb2-7"><a href="#cb2-7" aria-hidden="true" tabindex="-1"></a> <span class="fu">scale_y_continuous</span>(<span class="at">breaks =</span> <span class="fu">c</span>(<span class="dv">0</span>, <span class="dv">5</span>, <span class="dv">10</span>, <span class="dv">15</span>, <span class="dv">20</span>, <span class="dv">25</span>, <span class="dv">30</span>, <span class="dv">35</span>, <span class="dv">40</span>, <span class="dv">45</span>, <span class="dv">50</span>, <span class="dv">55</span>, <span class="dv">60</span>, <span class="dv">65</span>, <span class="dv">70</span>, <span class="dv">75</span>, <span class="dv">80</span>, <span class="dv">85</span>)) <span class="sc">+</span></span>
<span id="cb2-8"><a href="#cb2-8" aria-hidden="true" tabindex="-1"></a> <span class="fu">scale_fill_manual</span>(<span class="at">labels =</span> <span class="fu">c</span>(<span class="st">"Masculino"</span>, <span class="st">"Femino"</span>),</span>
<span id="cb2-9"><a href="#cb2-9" aria-hidden="true" tabindex="-1"></a> <span class="at">values =</span> <span class="fu">c</span>(<span class="st">"lightblue3"</span>, <span class="st">"hotpink1"</span>)) <span class="sc">+</span></span>
<span id="cb2-10"><a href="#cb2-10" aria-hidden="true" tabindex="-1"></a> <span class="fu">labs</span>(<span class="at">fill =</span> <span class="st">"Sexo"</span>,</span>
<span id="cb2-11"><a href="#cb2-11" aria-hidden="true" tabindex="-1"></a> <span class="at">title =</span> <span class="st">"Figura 2 - Distribuição da idade por sexo para brasileiros casados"</span>,</span>
<span id="cb2-12"><a href="#cb2-12" aria-hidden="true" tabindex="-1"></a> <span class="at">caption =</span> <span class="st">"Fonte: ISSP, 2002."</span>)<span class="sc">+</span></span>
<span id="cb2-13"><a href="#cb2-13" aria-hidden="true" tabindex="-1"></a> <span class="fu">theme_minimal</span>() <span class="sc">+</span></span>
<span id="cb2-14"><a href="#cb2-14" aria-hidden="true" tabindex="-1"></a> <span class="fu">theme</span>(<span class="at">axis.title.y =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb2-15"><a href="#cb2-15" aria-hidden="true" tabindex="-1"></a> <span class="at">axis.title.x =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb2-16"><a href="#cb2-16" aria-hidden="true" tabindex="-1"></a> <span class="at">axis.ticks.x =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb2-17"><a href="#cb2-17" aria-hidden="true" tabindex="-1"></a> <span class="at">axis.text.x =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb2-18"><a href="#cb2-18" aria-hidden="true" tabindex="-1"></a> <span class="at">plot.title =</span> <span class="fu">element_text</span>(<span class="at">hjust =</span> <span class="fl">0.5</span>, <span class="at">size =</span> <span class="dv">12</span>, <span class="at">face =</span> <span class="st">"bold"</span>),</span>
<span id="cb2-19"><a href="#cb2-19" aria-hidden="true" tabindex="-1"></a> <span class="at">plot.caption =</span> <span class="fu">element_text</span>(<span class="at">hjust =</span> <span class="fl">0.5</span>))</span>
<span id="cb2-20"><a href="#cb2-20" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb2-21"><a href="#cb2-21" aria-hidden="true" tabindex="-1"></a><span class="fu">print</span>(idade_sexo)</span></code></pre></div>
<p><img src="data:image/png;base64,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" /><!-- --></p>
</div>
<div id="autodeclaração-de-corraça" class="section level4">
<h4>Autodeclaração de cor/raça</h4>
<p>A Figura 3 possui a distribuição relativa dos brasileiros casados de acordo com sua autodeclaração de cor/raça. Assim como na população brasileira em geral, na amostra selecionada, a maioria, 49,54%, dos entrevistados se declarou branca. O segundo grupo racial a apresentar maior frequência relativa foi o grupo de pardos, representando 33,6% dos brasileiros casados. Os entrevistados pretos, indígenas e amarelos, por sua vez, somaram 9,24%, 2,66% e 1,85%, respectivamente.</p>
<p>Além da frequência relativa dos grupos anteriormente mencionados, na Figura 3, também é possível observar que 3,12% dos entrevistados preferiram não declarar sua cor/raça.</p>
<div class="sourceCode" id="cb3"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb3-1"><a href="#cb3-1" aria-hidden="true" tabindex="-1"></a><span class="co"># Distribuição relativa dos brasileiros casados de acordo com sua autodeclaração de cor/raça</span></span>
<span id="cb3-2"><a href="#cb3-2" aria-hidden="true" tabindex="-1"></a><span class="co"># OBS.: Antes de elaborar o gráfico, a variável foi modificada para que as categorias correspondessem àquelas utilizadas pelo IBGE</span></span>
<span id="cb3-3"><a href="#cb3-3" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb3-4"><a href="#cb3-4" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb3-5"><a href="#cb3-5" aria-hidden="true" tabindex="-1"></a>raca <span class="ot"><-</span> brasil_casados_vs <span class="sc">%>%</span> </span>
<span id="cb3-6"><a href="#cb3-6" aria-hidden="true" tabindex="-1"></a> <span class="fu">mutate</span>(<span class="at">identidade_etnica =</span> <span class="fu">case_when</span>(</span>
<span id="cb3-7"><a href="#cb3-7" aria-hidden="true" tabindex="-1"></a> <span class="fu">is.na</span>(identidade_etnica) <span class="sc">~</span> <span class="st">"Não declarada"</span>,</span>
<span id="cb3-8"><a href="#cb3-8" aria-hidden="true" tabindex="-1"></a> identidade_etnica <span class="sc">==</span> <span class="st">"American Indian,Navajo,Ind.Dialect"</span> <span class="sc">~</span> <span class="st">"Indígena"</span>,</span>
<span id="cb3-9"><a href="#cb3-9" aria-hidden="true" tabindex="-1"></a> identidade_etnica <span class="sc">==</span> <span class="st">"Asia,other Asian"</span> <span class="sc">~</span> <span class="st">"Amarela"</span>,</span>
<span id="cb3-10"><a href="#cb3-10" aria-hidden="true" tabindex="-1"></a> identidade_etnica <span class="sc">==</span> <span class="st">"Black/African/Carribean,No-Spanish"</span> <span class="sc">~</span> <span class="st">"Preta"</span>,</span>
<span id="cb3-11"><a href="#cb3-11" aria-hidden="true" tabindex="-1"></a> identidade_etnica <span class="sc">==</span> <span class="st">"Europe,White/European"</span> <span class="sc">~</span> <span class="st">"Branca"</span>,</span>
<span id="cb3-12"><a href="#cb3-12" aria-hidden="true" tabindex="-1"></a> identidade_etnica <span class="sc">==</span> <span class="st">"Other,mixed origin,one-non-swedish"</span> <span class="sc">~</span> <span class="st">"Parda"</span></span>
<span id="cb3-13"><a href="#cb3-13" aria-hidden="true" tabindex="-1"></a> )) <span class="sc">%>%</span></span>
<span id="cb3-14"><a href="#cb3-14" aria-hidden="true" tabindex="-1"></a> <span class="fu">group_by</span>(identidade_etnica) <span class="sc">%>%</span> </span>
<span id="cb3-15"><a href="#cb3-15" aria-hidden="true" tabindex="-1"></a> <span class="fu">summarise</span>(<span class="at">n =</span> <span class="fu">n</span>(), <span class="at">na.rm =</span> <span class="cn">TRUE</span>) <span class="sc">%>%</span> </span>
<span id="cb3-16"><a href="#cb3-16" aria-hidden="true" tabindex="-1"></a> <span class="fu">mutate</span>(<span class="at">freq_raca =</span> n<span class="sc">/</span><span class="fu">sum</span>(n)) <span class="sc">%>%</span></span>
<span id="cb3-17"><a href="#cb3-17" aria-hidden="true" tabindex="-1"></a> <span class="fu">mutate</span>(<span class="at">freq_raca =</span> freq_raca<span class="sc">*</span><span class="dv">100</span>) <span class="sc">%>%</span> </span>
<span id="cb3-18"><a href="#cb3-18" aria-hidden="true" tabindex="-1"></a> <span class="fu">mutate</span>(<span class="at">freq_raca =</span> <span class="fu">round</span>(freq_raca, <span class="dv">2</span>)) <span class="sc">%>%</span> </span>
<span id="cb3-19"><a href="#cb3-19" aria-hidden="true" tabindex="-1"></a> <span class="fu">ungroup</span>() <span class="sc">%>%</span> </span>
<span id="cb3-20"><a href="#cb3-20" aria-hidden="true" tabindex="-1"></a> <span class="fu">ggplot</span>() <span class="sc">+</span></span>
<span id="cb3-21"><a href="#cb3-21" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_col</span>(<span class="fu">aes</span>(<span class="at">x =</span> identidade_etnica, <span class="at">y =</span> freq_raca, <span class="at">fill =</span> identidade_etnica)) <span class="sc">+</span></span>
<span id="cb3-22"><a href="#cb3-22" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_label</span>(<span class="fu">aes</span>(<span class="at">x =</span> identidade_etnica, <span class="at">y =</span> freq_raca, </span>
<span id="cb3-23"><a href="#cb3-23" aria-hidden="true" tabindex="-1"></a> <span class="at">label =</span> freq_raca)) <span class="sc">+</span></span>
<span id="cb3-24"><a href="#cb3-24" aria-hidden="true" tabindex="-1"></a> <span class="fu">scale_fill_manual</span>(<span class="at">values =</span> <span class="fu">c</span>(<span class="st">"darksalmon"</span>, <span class="st">"aquamarine"</span>, <span class="st">"darkseagreen1"</span>, <span class="st">"grey"</span>, <span class="st">"khaki1"</span>, <span class="st">"plum2"</span>)) <span class="sc">+</span></span>
<span id="cb3-25"><a href="#cb3-25" aria-hidden="true" tabindex="-1"></a> <span class="fu">labs</span>(<span class="at">y =</span> <span class="st">"Percentual de entrevistados"</span>, <span class="at">fill =</span> <span class="st">"Cor/raça"</span>,</span>
<span id="cb3-26"><a href="#cb3-26" aria-hidden="true" tabindex="-1"></a> <span class="at">title =</span> <span class="st">"Figura 3 - Distribuição relativa da amostra por cor/raça"</span>,</span>
<span id="cb3-27"><a href="#cb3-27" aria-hidden="true" tabindex="-1"></a> <span class="at">caption =</span> <span class="st">"Fonte: ISSP, 2002."</span>) <span class="sc">+</span></span>
<span id="cb3-28"><a href="#cb3-28" aria-hidden="true" tabindex="-1"></a> <span class="fu">theme_minimal</span>() <span class="sc">+</span></span>
<span id="cb3-29"><a href="#cb3-29" aria-hidden="true" tabindex="-1"></a> <span class="fu">theme</span>(</span>
<span id="cb3-30"><a href="#cb3-30" aria-hidden="true" tabindex="-1"></a> <span class="at">axis.title.y =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb3-31"><a href="#cb3-31" aria-hidden="true" tabindex="-1"></a> <span class="at">axis.title.x =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb3-32"><a href="#cb3-32" aria-hidden="true" tabindex="-1"></a> <span class="at">axis.ticks.x =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb3-33"><a href="#cb3-33" aria-hidden="true" tabindex="-1"></a> <span class="at">axis.text.x =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb3-34"><a href="#cb3-34" aria-hidden="true" tabindex="-1"></a> <span class="at">plot.title =</span> <span class="fu">element_text</span>(<span class="at">size =</span> <span class="dv">12</span>, <span class="at">face =</span> <span class="st">"bold"</span>, <span class="at">hjust =</span> <span class="fl">0.5</span>),</span>
<span id="cb3-35"><a href="#cb3-35" aria-hidden="true" tabindex="-1"></a> <span class="at">plot.caption =</span> <span class="fu">element_text</span>(<span class="at">hjust =</span> <span class="fl">0.5</span>))</span>
<span id="cb3-36"><a href="#cb3-36" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb3-37"><a href="#cb3-37" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb3-38"><a href="#cb3-38" aria-hidden="true" tabindex="-1"></a><span class="fu">print</span>(raca)</span></code></pre></div>
<p><img src="data:image/png;base64,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" /><!-- --></p>
</div>
<div id="anos-de-escolaridade" class="section level4">
<h4>Anos de escolaridade</h4>
<p>Na Figura 4, é possível observar a distribuição dos anos de escolaridade que possuem os brasileiros casados de acordo com seu sexo. Neste gráfico, o eixo y contém quatro númeris diferentes, cada um deles correspondentes à quantidade de anos de estudos necessários para a finalização de importantes níveis educacionais. Enquanto 8 anos representa a finalização do Ensino Fundamental, 11 anos corresponde ao encerramento do Ensino Médio e 15 anos à conclusão do Ensino Superior.</p>
<p>Posto isto, a partir da leitura da Figura 4, tem-se que as mulheres, como mediana, apresentaram, aproximadamente, 6 anos de escolaridade, enquanto os homens obtiveram apenas 5 anos. Embora ambos valores sejam extremamente baixos, eles refletem aquilo que é afirmado pela literatura sociológica a respeito das desigualdades educacionais. No Brasil, as mulheres são, geralmente, mais escolarizadas do que os homens.</p>
<div class="sourceCode" id="cb4"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb4-1"><a href="#cb4-1" aria-hidden="true" tabindex="-1"></a><span class="co"># Distribuição de brasileiros casados por anos de escolaridade, de acordo com seu sexo</span></span>
<span id="cb4-2"><a href="#cb4-2" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb4-3"><a href="#cb4-3" aria-hidden="true" tabindex="-1"></a>escolaridade_sexo <span class="ot"><-</span> brasil_casados_vs <span class="sc">%>%</span></span>
<span id="cb4-4"><a href="#cb4-4" aria-hidden="true" tabindex="-1"></a> <span class="fu">mutate</span>(<span class="at">anos_escolaridade =</span> <span class="fu">na_if</span>(anos_escolaridade, <span class="dv">97</span>)) <span class="sc">%>%</span></span>
<span id="cb4-5"><a href="#cb4-5" aria-hidden="true" tabindex="-1"></a> <span class="fu">group_by</span>(sexo) <span class="sc">%>%</span></span>
<span id="cb4-6"><a href="#cb4-6" aria-hidden="true" tabindex="-1"></a> <span class="fu">ggplot</span>() <span class="sc">+</span></span>
<span id="cb4-7"><a href="#cb4-7" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_boxplot</span>(<span class="fu">aes</span>(<span class="at">x =</span> sexo, <span class="at">y =</span> anos_escolaridade, <span class="at">fill =</span> sexo)) <span class="sc">+</span></span>
<span id="cb4-8"><a href="#cb4-8" aria-hidden="true" tabindex="-1"></a> <span class="fu">scale_y_continuous</span>(<span class="at">breaks =</span> <span class="fu">c</span>(<span class="dv">0</span>, <span class="dv">8</span>, <span class="dv">11</span>, <span class="dv">15</span>)) <span class="sc">+</span></span>
<span id="cb4-9"><a href="#cb4-9" aria-hidden="true" tabindex="-1"></a> <span class="fu">scale_fill_manual</span>(</span>
<span id="cb4-10"><a href="#cb4-10" aria-hidden="true" tabindex="-1"></a> <span class="at">labels =</span> <span class="fu">c</span>(<span class="st">"Masculino"</span>, <span class="st">"Femino"</span>),</span>
<span id="cb4-11"><a href="#cb4-11" aria-hidden="true" tabindex="-1"></a> <span class="at">values =</span> <span class="fu">c</span>(<span class="st">"lightblue3"</span>, <span class="st">"hotpink1"</span>)</span>
<span id="cb4-12"><a href="#cb4-12" aria-hidden="true" tabindex="-1"></a> ) <span class="sc">+</span></span>
<span id="cb4-13"><a href="#cb4-13" aria-hidden="true" tabindex="-1"></a> <span class="fu">labs</span>(</span>
<span id="cb4-14"><a href="#cb4-14" aria-hidden="true" tabindex="-1"></a> <span class="at">y =</span> <span class="st">"Anos de escolaridade"</span>,</span>
<span id="cb4-15"><a href="#cb4-15" aria-hidden="true" tabindex="-1"></a> <span class="at">fill =</span> <span class="st">"Sexo"</span>,</span>
<span id="cb4-16"><a href="#cb4-16" aria-hidden="true" tabindex="-1"></a> <span class="at">title =</span> <span class="st">"Figura 4 - Distribuição dos anos de escolaridade"</span>,</span>
<span id="cb4-17"><a href="#cb4-17" aria-hidden="true" tabindex="-1"></a> <span class="at">caption =</span> <span class="st">"Fonte: ISSP, 2002."</span></span>
<span id="cb4-18"><a href="#cb4-18" aria-hidden="true" tabindex="-1"></a> ) <span class="sc">+</span></span>
<span id="cb4-19"><a href="#cb4-19" aria-hidden="true" tabindex="-1"></a> <span class="fu">theme_minimal</span>()<span class="sc">+</span></span>
<span id="cb4-20"><a href="#cb4-20" aria-hidden="true" tabindex="-1"></a> <span class="fu">theme</span>(</span>
<span id="cb4-21"><a href="#cb4-21" aria-hidden="true" tabindex="-1"></a> <span class="at">axis.title.y =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb4-22"><a href="#cb4-22" aria-hidden="true" tabindex="-1"></a> <span class="at">axis.title.x =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb4-23"><a href="#cb4-23" aria-hidden="true" tabindex="-1"></a> <span class="at">axis.ticks.x =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb4-24"><a href="#cb4-24" aria-hidden="true" tabindex="-1"></a> <span class="at">axis.text.x =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb4-25"><a href="#cb4-25" aria-hidden="true" tabindex="-1"></a> <span class="at">plot.title =</span> <span class="fu">element_text</span>(<span class="at">size =</span> <span class="dv">11</span>, <span class="at">face =</span> <span class="st">"bold"</span>, <span class="at">hjust =</span> <span class="fl">0.5</span>),</span>
<span id="cb4-26"><a href="#cb4-26" aria-hidden="true" tabindex="-1"></a> <span class="at">plot.caption =</span> <span class="fu">element_text</span>(<span class="at">hjust =</span> <span class="fl">0.5</span>)</span>
<span id="cb4-27"><a href="#cb4-27" aria-hidden="true" tabindex="-1"></a> )</span>
<span id="cb4-28"><a href="#cb4-28" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb4-29"><a href="#cb4-29" aria-hidden="true" tabindex="-1"></a><span class="fu">print</span>(escolaridade_sexo)</span></code></pre></div>
<pre><code>## Warning: Removed 43 rows containing non-finite values (stat_boxplot).</code></pre>
<p><img src="data:image/png;base64,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" /><!-- --></p>
</div>
<div id="situação-de-emprego" class="section level4">
<h4>Situação de emprego</h4>
<p>Assim como a Figura 4 anteriormente apresentados, a Figura 5 nos revela importantes diferenças existentes entre os homens e mulheres que compõem a amostra selecionada. Ao nos mostrar sua distribuição relativa por situação de emprego de acordo com sexo, a Figura 5 demonstra que, enquanto 64% dos homens possuem empregos em tempo integral, apenas 27,2% das mulheres se encontram na mesma situação.</p>
<p>Em contrapartida, se, por um lado, 50,88% das mulheres eram donas de casa, por outro, apenas 0,81% dos homens também o eram. Tais resultados, embora sejam simplesmente descritivos, nos indicam que, em 2002, a maioria das mulheres casadas assumiam as tarefas de manutenção da casa e de cuidados com outros moradores como sua principal atividade.</p>
<p>Uma vez que o regime de emprego adotado também pode nos indicar uma tentativa de conciliação entre as esferas produtiva e reprodutiva, também merece destaque a pequena porcentagem de mulheres que possuíam empregos em tempo parcial, 8,82%. Em outras palavras, os resultados aqui discutidos apontam, em primeiro lugar, para uma predominância das mulheres casadas nas atividades domésticas, em detrimento do mercado de trabalho.</p>
<p>Entre os homens, também se destacaram aqueles que estavam aposentados e aqueles que trabalhavam em tempo parcial, correspondendo a 22,58% e 6,72% respectivamente.</p>
<p>Tanto entre os homens quanto entre as mulheres, os desempregados correspondiam, aproximadamente, a apenas 3,3%.</p>
<div class="sourceCode" id="cb6"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb6-1"><a href="#cb6-1" aria-hidden="true" tabindex="-1"></a><span class="co"># Distribuição dos brasileiros casados por situação de emprego, de acordo com seu sexo</span></span>
<span id="cb6-2"><a href="#cb6-2" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb6-3"><a href="#cb6-3" aria-hidden="true" tabindex="-1"></a>emprego_sexo_grafico <span class="ot"><-</span> brasil_casados_vs <span class="sc">%>%</span> </span>
<span id="cb6-4"><a href="#cb6-4" aria-hidden="true" tabindex="-1"></a> <span class="fu">mutate</span>(<span class="at">emprego_status =</span> <span class="fu">case_when</span>(</span>
<span id="cb6-5"><a href="#cb6-5" aria-hidden="true" tabindex="-1"></a> emprego_status <span class="sc">==</span> <span class="st">"Employed-full time"</span> <span class="sc">~</span> <span class="st">"Trab. tempo integral"</span>,</span>
<span id="cb6-6"><a href="#cb6-6" aria-hidden="true" tabindex="-1"></a> emprego_status <span class="sc">==</span> <span class="st">"Housewife,home duties"</span> <span class="sc">~</span> <span class="st">"Dona de casa"</span>,</span>
<span id="cb6-7"><a href="#cb6-7" aria-hidden="true" tabindex="-1"></a> emprego_status <span class="sc">==</span> <span class="st">"Retired"</span> <span class="sc">~</span> <span class="st">"Aposent."</span>,</span>
<span id="cb6-8"><a href="#cb6-8" aria-hidden="true" tabindex="-1"></a> emprego_status <span class="sc">==</span> <span class="st">"Helping family member"</span> <span class="sc">~</span> <span class="st">"Parente que ajuda"</span>,</span>
<span id="cb6-9"><a href="#cb6-9" aria-hidden="true" tabindex="-1"></a> emprego_status <span class="sc">==</span> <span class="st">"Oth, not i labor force"</span> <span class="sc">~</span> <span class="st">"Outro"</span>,</span>
<span id="cb6-10"><a href="#cb6-10" aria-hidden="true" tabindex="-1"></a> emprego_status <span class="sc">==</span> <span class="st">"Unemployed"</span> <span class="sc">~</span> <span class="st">"Desempreg."</span>,</span>
<span id="cb6-11"><a href="#cb6-11" aria-hidden="true" tabindex="-1"></a> emprego_status <span class="sc">==</span> <span class="st">"Permanently disabled"</span> <span class="sc">~</span> <span class="st">"PCD"</span>,</span>
<span id="cb6-12"><a href="#cb6-12" aria-hidden="true" tabindex="-1"></a> emprego_status <span class="sc">==</span> <span class="st">"Employed-part time"</span> <span class="sc">~</span> <span class="st">"Trab. tempo parcial"</span>,</span>
<span id="cb6-13"><a href="#cb6-13" aria-hidden="true" tabindex="-1"></a> emprego_status <span class="sc">==</span> <span class="st">"Studt,school,vct.trng"</span> <span class="sc">~</span> <span class="st">"Estudante"</span></span>
<span id="cb6-14"><a href="#cb6-14" aria-hidden="true" tabindex="-1"></a> )) <span class="sc">%>%</span> </span>
<span id="cb6-15"><a href="#cb6-15" aria-hidden="true" tabindex="-1"></a> <span class="fu">mutate</span>(<span class="at">sexo =</span> <span class="fu">case_when</span>(</span>
<span id="cb6-16"><a href="#cb6-16" aria-hidden="true" tabindex="-1"></a> sexo <span class="sc">==</span> <span class="st">"Male"</span> <span class="sc">~</span> <span class="st">"Masculino"</span>,</span>
<span id="cb6-17"><a href="#cb6-17" aria-hidden="true" tabindex="-1"></a> sexo <span class="sc">==</span> <span class="st">"Female"</span> <span class="sc">~</span> <span class="st">"Feminino"</span>,</span>
<span id="cb6-18"><a href="#cb6-18" aria-hidden="true" tabindex="-1"></a> )) <span class="sc">%>%</span> </span>
<span id="cb6-19"><a href="#cb6-19" aria-hidden="true" tabindex="-1"></a> <span class="fu">filter</span>(<span class="sc">!</span><span class="fu">is.na</span>(emprego_status)) <span class="sc">%>%</span> </span>
<span id="cb6-20"><a href="#cb6-20" aria-hidden="true" tabindex="-1"></a> <span class="fu">group_by</span>(sexo, emprego_status) <span class="sc">%>%</span> </span>
<span id="cb6-21"><a href="#cb6-21" aria-hidden="true" tabindex="-1"></a> <span class="fu">summarize</span>(<span class="at">n =</span> <span class="fu">n</span>()) <span class="sc">%>%</span> </span>
<span id="cb6-22"><a href="#cb6-22" aria-hidden="true" tabindex="-1"></a> <span class="fu">mutate</span>(<span class="at">emprego_sexo =</span> <span class="dv">100</span><span class="sc">*</span>n<span class="sc">/</span><span class="fu">sum</span>(n)) <span class="sc">%>%</span> </span>
<span id="cb6-23"><a href="#cb6-23" aria-hidden="true" tabindex="-1"></a> <span class="fu">ggplot</span>(<span class="fu">aes</span>(<span class="at">x =</span> sexo, <span class="at">y =</span> emprego_sexo, <span class="at">fill =</span> emprego_status)) <span class="sc">+</span></span>
<span id="cb6-24"><a href="#cb6-24" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_bar</span>(<span class="at">stat =</span> <span class="st">"identity"</span>, <span class="at">show.legend =</span> F) <span class="sc">+</span></span>
<span id="cb6-25"><a href="#cb6-25" aria-hidden="true" tabindex="-1"></a> <span class="fu">facet_grid</span>(<span class="sc">~</span> emprego_status, <span class="at">labeller =</span> <span class="fu">label_wrap_gen</span>(<span class="at">width =</span> <span class="dv">12</span>)) <span class="sc">+</span></span>
<span id="cb6-26"><a href="#cb6-26" aria-hidden="true" tabindex="-1"></a> <span class="fu">coord_flip</span>() <span class="sc">+</span></span>
<span id="cb6-27"><a href="#cb6-27" aria-hidden="true" tabindex="-1"></a> <span class="fu">ylim</span>(<span class="fu">c</span>(<span class="dv">0</span>, <span class="dv">90</span>)) <span class="sc">+</span></span>
<span id="cb6-28"><a href="#cb6-28" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_text</span>(<span class="fu">aes</span>(<span class="at">label =</span> <span class="fu">round</span>(emprego_sexo, <span class="dv">2</span>)), <span class="at">hjust =</span> <span class="sc">-</span>.<span class="dv">1</span>) <span class="sc">+</span></span>
<span id="cb6-29"><a href="#cb6-29" aria-hidden="true" tabindex="-1"></a> <span class="fu">theme</span>(<span class="at">strip.text =</span> <span class="fu">element_text</span>(<span class="at">size =</span> <span class="dv">12</span>)) <span class="sc">+</span></span>
<span id="cb6-30"><a href="#cb6-30" aria-hidden="true" tabindex="-1"></a> <span class="fu">scale_fill_manual</span>(<span class="at">values =</span> <span class="fu">c</span>(<span class="st">"lightsalmon"</span>, <span class="st">"aquamarine"</span>, <span class="st">"darkseagreen1"</span>, <span class="st">"grey"</span>, <span class="st">"khaki1"</span>, <span class="st">"plum2"</span>)) <span class="sc">+</span></span>
<span id="cb6-31"><a href="#cb6-31" aria-hidden="true" tabindex="-1"></a> <span class="fu">labs</span>(<span class="at">title =</span> <span class="st">"Figura 5 - Distribuição relativa dos brasileiros casados por situação de emprego de acordo com seu sexo"</span>,</span>
<span id="cb6-32"><a href="#cb6-32" aria-hidden="true" tabindex="-1"></a> <span class="at">caption =</span> <span class="st">"Fonte: ISSP, 2002."</span>)<span class="sc">+</span></span>
<span id="cb6-33"><a href="#cb6-33" aria-hidden="true" tabindex="-1"></a> <span class="fu">theme_minimal</span>() <span class="sc">+</span></span>
<span id="cb6-34"><a href="#cb6-34" aria-hidden="true" tabindex="-1"></a> <span class="fu">theme</span>(<span class="at">axis.title.x =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb6-35"><a href="#cb6-35" aria-hidden="true" tabindex="-1"></a> <span class="at">axis.title.y =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb6-36"><a href="#cb6-36" aria-hidden="true" tabindex="-1"></a> <span class="at">plot.title =</span> <span class="fu">element_text</span>(<span class="at">size =</span> <span class="dv">12</span>, <span class="at">face =</span> <span class="st">"bold"</span>, <span class="at">hjust =</span> <span class="fl">0.5</span>),</span>
<span id="cb6-37"><a href="#cb6-37" aria-hidden="true" tabindex="-1"></a> <span class="at">plot.caption =</span> <span class="fu">element_text</span>(<span class="at">hjust =</span> <span class="fl">0.5</span>))</span></code></pre></div>
<pre><code>## `summarise()` has grouped output by 'sexo'. You can override using the `.groups` argument.</code></pre>
<div class="sourceCode" id="cb8"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb8-1"><a href="#cb8-1" aria-hidden="true" tabindex="-1"></a><span class="fu">print</span>(emprego_sexo_grafico)</span></code></pre></div>
<p><img 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" /><!-- --></p>
</div>
<div id="rendimento" class="section level4">
<h4>Rendimento</h4>
<p>A Figura 6 se volta a outra dimensão das desigualdades de gênero amplamente discutidas na Sociologia: os diferentes rendimentos médios que homens e mulheres obtêm no mercado de trabalho. Sendo assim, a partir de sua leitura, percebe-se que as mulheres, mesmo sendo mais escolarizadas que os homens, recebem, em média, R$ 225,25 mensais a menos.</p>
<p>Este resultado é um indicativo de que, mesmo quando inseridas no mercado de trabalho, as mulheres enfrentam uma série de obstáculos que as levam a receber menos que os homens. Além de, geralmente, possuírem ocupações de menos prestígio social e também menor valorização, mulheres também enfrentam diferentes tipos de discriminação, dentre os quais estão, por exemplo, a discriminação decorrente do fato de serem mães ou, até mesmo, da possibilidade de se tornarem mães, por estarem em idade reprodutiva.</p>
<div class="sourceCode" id="cb9"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb9-1"><a href="#cb9-1" aria-hidden="true" tabindex="-1"></a><span class="co"># Rendimento médio dos brasileiros casados de acordo com seu sexo</span></span>
<span id="cb9-2"><a href="#cb9-2" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb9-3"><a href="#cb9-3" aria-hidden="true" tabindex="-1"></a>rendimento_médio_gráfico <span class="ot"><-</span> brasil_casados_vs <span class="sc">%>%</span> </span>
<span id="cb9-4"><a href="#cb9-4" aria-hidden="true" tabindex="-1"></a> <span class="fu">group_by</span>(sexo) <span class="sc">%>%</span></span>
<span id="cb9-5"><a href="#cb9-5" aria-hidden="true" tabindex="-1"></a> <span class="fu">summarize</span>(<span class="at">rendimento_medio =</span> <span class="fu">mean</span>(rendimento, <span class="at">na.rm =</span> <span class="cn">TRUE</span>)) <span class="sc">%>%</span> </span>
<span id="cb9-6"><a href="#cb9-6" aria-hidden="true" tabindex="-1"></a> <span class="fu">mutate</span>(<span class="at">rendimento_medio =</span> <span class="fu">round</span>(rendimento_medio, <span class="dv">2</span>)) <span class="sc">%>%</span> </span>
<span id="cb9-7"><a href="#cb9-7" aria-hidden="true" tabindex="-1"></a> <span class="fu">ggplot</span>() <span class="sc">+</span></span>
<span id="cb9-8"><a href="#cb9-8" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_col</span>(<span class="fu">aes</span>(<span class="at">x =</span> sexo, <span class="at">y =</span> rendimento_medio, <span class="at">fill =</span> sexo), <span class="at">show.legend =</span> <span class="cn">TRUE</span>) <span class="sc">+</span></span>
<span id="cb9-9"><a href="#cb9-9" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_label</span>(<span class="fu">aes</span>(<span class="at">x =</span> sexo, <span class="at">y =</span> rendimento_medio, <span class="at">label =</span> rendimento_medio))<span class="sc">+</span></span>
<span id="cb9-10"><a href="#cb9-10" aria-hidden="true" tabindex="-1"></a> <span class="fu">scale_y_continuous</span>(<span class="at">breaks =</span> <span class="fu">c</span>(<span class="dv">100</span>, <span class="dv">200</span>, <span class="dv">300</span>, <span class="dv">400</span>, <span class="dv">500</span>, <span class="dv">600</span>, <span class="dv">700</span>, <span class="dv">800</span>, <span class="dv">900</span>, <span class="dv">1000</span>, <span class="dv">1100</span>)) <span class="sc">+</span></span>
<span id="cb9-11"><a href="#cb9-11" aria-hidden="true" tabindex="-1"></a> <span class="fu">scale_fill_manual</span>(<span class="at">labels =</span> <span class="fu">c</span>(<span class="st">"Masculino"</span>, <span class="st">"Femino"</span>),</span>
<span id="cb9-12"><a href="#cb9-12" aria-hidden="true" tabindex="-1"></a> <span class="at">values =</span> <span class="fu">c</span>(<span class="st">"lightblue3"</span>, <span class="st">"hotpink1"</span>)) <span class="sc">+</span></span>
<span id="cb9-13"><a href="#cb9-13" aria-hidden="true" tabindex="-1"></a> <span class="fu">labs</span>(<span class="at">fill =</span> <span class="st">"Sexo"</span>,</span>
<span id="cb9-14"><a href="#cb9-14" aria-hidden="true" tabindex="-1"></a> <span class="at">title =</span> <span class="st">"Figura 6 - Rendimento mensal médio em R$ por sexo"</span>,</span>
<span id="cb9-15"><a href="#cb9-15" aria-hidden="true" tabindex="-1"></a> <span class="at">caption =</span> <span class="st">"Fonte: ISSP, 2002."</span>)<span class="sc">+</span></span>
<span id="cb9-16"><a href="#cb9-16" aria-hidden="true" tabindex="-1"></a> <span class="fu">theme_minimal</span>() <span class="sc">+</span></span>
<span id="cb9-17"><a href="#cb9-17" aria-hidden="true" tabindex="-1"></a> <span class="fu">theme</span>(</span>
<span id="cb9-18"><a href="#cb9-18" aria-hidden="true" tabindex="-1"></a> <span class="at">axis.title.y =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb9-19"><a href="#cb9-19" aria-hidden="true" tabindex="-1"></a> <span class="at">axis.title.x =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb9-20"><a href="#cb9-20" aria-hidden="true" tabindex="-1"></a> <span class="at">axis.ticks.x =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb9-21"><a href="#cb9-21" aria-hidden="true" tabindex="-1"></a> <span class="at">axis.text.x =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb9-22"><a href="#cb9-22" aria-hidden="true" tabindex="-1"></a> <span class="at">plot.title =</span> <span class="fu">element_text</span>(<span class="at">size =</span> <span class="dv">12</span>, <span class="at">face =</span> <span class="st">"bold"</span>, <span class="at">hjust =</span> <span class="fl">0.5</span>),</span>
<span id="cb9-23"><a href="#cb9-23" aria-hidden="true" tabindex="-1"></a> <span class="at">plot.caption =</span> <span class="fu">element_text</span>(<span class="at">hjust =</span> <span class="fl">0.5</span>))</span>
<span id="cb9-24"><a href="#cb9-24" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb9-25"><a href="#cb9-25" aria-hidden="true" tabindex="-1"></a><span class="fu">print</span>(rendimento_médio_gráfico)</span></code></pre></div>
<p><img src="data:image/png;base64,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" /><!-- --></p>
</div>
<div id="filhos" class="section level4">
<h4>Filhos</h4>
<p>Dentre as características sociodemográficas da amostra aqui apresentadas, as últimas serão as quantidades de filhos com até 6 anos e com mais de 7 anos de idade.</p>
<p>Segundo a literatura sociológica sobre a divisão dos afazeres domésticos e de cuidado, a presença de filhos no domicílio é um fator extremamente importante para a compreensão deste fenômeno, uma vez que, dependendo de sua idade e de seu sexo, eles podem tanto aumentar quanto diminuir o tempo que os indivíduos dedicam à realização destas atividades.</p>
<p>Sendo assim, na Figura 7, é possível observar que mais de 70% dos entrevistados residem no mesmo domicílio que, pelo menos, 1 filho com menos de 6 anos, enquanto, na Figura 8, percebemos que 40% deles convive com, ao menos, 1 filho com mais de 7 anos de idade.</p>
<div class="sourceCode" id="cb10"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb10-1"><a href="#cb10-1" aria-hidden="true" tabindex="-1"></a><span class="co"># Distribuição de brasileiros casados de acordo com o número filhos com mais de 7 anos no domicílio</span></span>
<span id="cb10-2"><a href="#cb10-2" aria-hidden="true" tabindex="-1"></a><span class="co"># OBS.: antes de elaborar o gráfico, a variável referente ao número de filhos com menos de 6 anos (categórica) foi transformada em variável numérica.</span></span>
<span id="cb10-3"><a href="#cb10-3" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb10-4"><a href="#cb10-4" aria-hidden="true" tabindex="-1"></a>filhos_pequenos_gráfico <span class="ot"><-</span> brasil_casados_vs <span class="sc">%>%</span> </span>
<span id="cb10-5"><a href="#cb10-5" aria-hidden="true" tabindex="-1"></a> <span class="fu">mutate</span>(crianças<span class="at">_pequenas =</span> <span class="fu">case_when</span>(</span>
<span id="cb10-6"><a href="#cb10-6" aria-hidden="true" tabindex="-1"></a> crianças_pequenas <span class="sc">==</span> <span class="st">"1 child"</span> <span class="sc">~</span> <span class="dv">1</span>,</span>
<span id="cb10-7"><a href="#cb10-7" aria-hidden="true" tabindex="-1"></a> crianças_pequenas <span class="sc">==</span> <span class="st">"2 children"</span> <span class="sc">~</span> <span class="dv">2</span>,</span>
<span id="cb10-8"><a href="#cb10-8" aria-hidden="true" tabindex="-1"></a> crianças_pequenas <span class="sc">==</span> <span class="st">"3 children"</span> <span class="sc">~</span> <span class="dv">3</span>,</span>
<span id="cb10-9"><a href="#cb10-9" aria-hidden="true" tabindex="-1"></a> crianças_pequenas <span class="sc">==</span> <span class="st">"4 children"</span> <span class="sc">~</span> <span class="dv">4</span>,</span>
<span id="cb10-10"><a href="#cb10-10" aria-hidden="true" tabindex="-1"></a> crianças_pequenas <span class="sc">==</span> <span class="st">"5 children"</span> <span class="sc">~</span> <span class="dv">5</span>,</span>
<span id="cb10-11"><a href="#cb10-11" aria-hidden="true" tabindex="-1"></a> crianças_pequenas <span class="sc">==</span> <span class="st">"6 children"</span> <span class="sc">~</span> <span class="dv">6</span>,</span>
<span id="cb10-12"><a href="#cb10-12" aria-hidden="true" tabindex="-1"></a> crianças_pequenas<span class="sc">==</span> <span class="st">"7 children"</span> <span class="sc">~</span> <span class="dv">7</span>,</span>
<span id="cb10-13"><a href="#cb10-13" aria-hidden="true" tabindex="-1"></a> crianças_pequenas <span class="sc">==</span> <span class="st">"8 children"</span> <span class="sc">~</span> <span class="dv">8</span>,</span>
<span id="cb10-14"><a href="#cb10-14" aria-hidden="true" tabindex="-1"></a> crianças_pequenas <span class="sc">==</span> <span class="st">"9 children"</span> <span class="sc">~</span> <span class="dv">9</span>,</span>
<span id="cb10-15"><a href="#cb10-15" aria-hidden="true" tabindex="-1"></a> crianças_pequenas <span class="sc">==</span> <span class="st">"10 children"</span> <span class="sc">~</span> <span class="dv">10</span>)) <span class="sc">%>%</span> </span>
<span id="cb10-16"><a href="#cb10-16" aria-hidden="true" tabindex="-1"></a> <span class="fu">filter</span>(<span class="sc">!</span><span class="fu">is.na</span>(crianças_pequenas)) <span class="sc">%>%</span> </span>
<span id="cb10-17"><a href="#cb10-17" aria-hidden="true" tabindex="-1"></a> <span class="fu">group_by</span>(crianças_pequenas) <span class="sc">%>%</span> </span>
<span id="cb10-18"><a href="#cb10-18" aria-hidden="true" tabindex="-1"></a> <span class="fu">summarize</span>(<span class="at">n =</span> <span class="fu">n</span>()) <span class="sc">%>%</span> </span>
<span id="cb10-19"><a href="#cb10-19" aria-hidden="true" tabindex="-1"></a> <span class="fu">mutate</span>(freq_crianças<span class="at">_pequenas =</span> n<span class="sc">*</span><span class="dv">100</span><span class="sc">/</span><span class="fu">sum</span>(n)) <span class="sc">%>%</span> </span>
<span id="cb10-20"><a href="#cb10-20" aria-hidden="true" tabindex="-1"></a> <span class="fu">mutate</span>(freq_crianças<span class="at">_pequenas =</span> <span class="fu">round</span>(freq_crianças_pequenas, <span class="dv">2</span>)) <span class="sc">%>%</span> </span>
<span id="cb10-21"><a href="#cb10-21" aria-hidden="true" tabindex="-1"></a> <span class="fu">ggplot</span>() <span class="sc">+</span></span>
<span id="cb10-22"><a href="#cb10-22" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_col</span>(<span class="at">mapping =</span> <span class="fu">aes</span>(<span class="at">x =</span> crianças_pequenas, <span class="at">y =</span> freq_crianças_pequenas, <span class="at">fill =</span> crianças_pequenas), <span class="at">show.legend =</span> <span class="cn">TRUE</span>) <span class="sc">+</span></span>
<span id="cb10-23"><a href="#cb10-23" aria-hidden="true" tabindex="-1"></a> <span class="fu">scale_y_continuous</span>(<span class="at">breaks =</span> <span class="fu">c</span>(<span class="dv">0</span>, <span class="dv">10</span>, <span class="dv">20</span>, <span class="dv">30</span>, <span class="dv">40</span>, <span class="dv">50</span>, <span class="dv">60</span>, <span class="dv">70</span>, <span class="dv">80</span>, <span class="dv">90</span>, <span class="dv">100</span>)) <span class="sc">+</span></span>
<span id="cb10-24"><a href="#cb10-24" aria-hidden="true" tabindex="-1"></a> <span class="fu">scale_x_continuous</span>(<span class="at">breaks =</span> <span class="fu">c</span>(<span class="dv">1</span>, <span class="dv">2</span>, <span class="dv">3</span>, <span class="dv">4</span>, <span class="dv">5</span>)) <span class="sc">+</span></span>
<span id="cb10-25"><a href="#cb10-25" aria-hidden="true" tabindex="-1"></a> <span class="fu">scale_fill_gradient</span>(<span class="at">low =</span> <span class="st">"tomato"</span>, <span class="at">high =</span> <span class="st">"tomato4"</span>,</span>
<span id="cb10-26"><a href="#cb10-26" aria-hidden="true" tabindex="-1"></a> <span class="at">breaks =</span> <span class="fu">c</span>(<span class="dv">2</span>, <span class="dv">3</span>, <span class="dv">4</span>)) <span class="sc">+</span></span>
<span id="cb10-27"><a href="#cb10-27" aria-hidden="true" tabindex="-1"></a> <span class="fu">labs</span>(<span class="at">y =</span> <span class="st">"Frequência relativa"</span>, <span class="at">fill =</span> <span class="st">"Número de filhos com </span><span class="sc">\n</span><span class="st">menos de 6 anos"</span>,</span>
<span id="cb10-28"><a href="#cb10-28" aria-hidden="true" tabindex="-1"></a> <span class="at">title =</span> <span class="st">"Figura 7 - Distribuição relativa dos brasileiros casados </span><span class="sc">\n</span><span class="st">de acordo com o número de filhos com menos de </span><span class="sc">\n</span><span class="st">6 anos no domicílio"</span>,</span>
<span id="cb10-29"><a href="#cb10-29" aria-hidden="true" tabindex="-1"></a> <span class="at">caption =</span> <span class="st">"Fonte: ISSP, 2002"</span>)<span class="sc">+</span></span>
<span id="cb10-30"><a href="#cb10-30" aria-hidden="true" tabindex="-1"></a> <span class="fu">theme_minimal</span>() <span class="sc">+</span></span>
<span id="cb10-31"><a href="#cb10-31" aria-hidden="true" tabindex="-1"></a> <span class="fu">theme</span>(</span>
<span id="cb10-32"><a href="#cb10-32" aria-hidden="true" tabindex="-1"></a> <span class="at">plot.subtitle =</span> <span class="fu">element_text</span>(<span class="at">hjust =</span> <span class="fl">0.5</span>),</span>
<span id="cb10-33"><a href="#cb10-33" aria-hidden="true" tabindex="-1"></a> <span class="at">axis.title.x =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb10-34"><a href="#cb10-34" aria-hidden="true" tabindex="-1"></a> <span class="at">axis.title.y =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb10-35"><a href="#cb10-35" aria-hidden="true" tabindex="-1"></a> <span class="at">plot.title =</span> <span class="fu">element_text</span>(<span class="at">size =</span> <span class="dv">12</span>, <span class="at">face =</span> <span class="st">"bold"</span>, <span class="at">hjust =</span> <span class="fl">0.5</span>),</span>
<span id="cb10-36"><a href="#cb10-36" aria-hidden="true" tabindex="-1"></a> <span class="at">plot.caption =</span> <span class="fu">element_text</span>(<span class="at">hjust =</span> <span class="fl">0.5</span>))</span>
<span id="cb10-37"><a href="#cb10-37" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb10-38"><a href="#cb10-38" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb10-39"><a href="#cb10-39" aria-hidden="true" tabindex="-1"></a><span class="fu">print</span>(filhos_pequenos_gráfico)</span></code></pre></div>
<p><img src="data:image/png;base64,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" /><!-- --></p>
<div class="sourceCode" id="cb11"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb11-1"><a href="#cb11-1" aria-hidden="true" tabindex="-1"></a><span class="co"># Distribuição de brasileiros casados de acordo com o número filhos com mais de 7 anos no domicílio</span></span>
<span id="cb11-2"><a href="#cb11-2" aria-hidden="true" tabindex="-1"></a><span class="co"># OBS.: antes de elaborar o gráfico, a variável referente ao número de filhos com mais de 7 anos (categórica) foi transformada em variável numérica.</span></span>
<span id="cb11-3"><a href="#cb11-3" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb11-4"><a href="#cb11-4" aria-hidden="true" tabindex="-1"></a>filhos_maiores_gráfico <span class="ot"><-</span> brasil_casados_vs <span class="sc">%>%</span> </span>
<span id="cb11-5"><a href="#cb11-5" aria-hidden="true" tabindex="-1"></a> <span class="fu">mutate</span>(<span class="at">filhos_maiores =</span> <span class="fu">case_when</span>(</span>
<span id="cb11-6"><a href="#cb11-6" aria-hidden="true" tabindex="-1"></a> filhos_maiores <span class="sc">==</span> <span class="st">"1 child"</span> <span class="sc">~</span> <span class="dv">1</span>,</span>
<span id="cb11-7"><a href="#cb11-7" aria-hidden="true" tabindex="-1"></a> filhos_maiores <span class="sc">==</span> <span class="st">"2 children"</span> <span class="sc">~</span> <span class="dv">2</span>,</span>
<span id="cb11-8"><a href="#cb11-8" aria-hidden="true" tabindex="-1"></a> filhos_maiores <span class="sc">==</span> <span class="st">"3 children"</span> <span class="sc">~</span> <span class="dv">3</span>,</span>
<span id="cb11-9"><a href="#cb11-9" aria-hidden="true" tabindex="-1"></a> filhos_maiores <span class="sc">==</span> <span class="st">"4 children"</span> <span class="sc">~</span> <span class="dv">4</span>,</span>
<span id="cb11-10"><a href="#cb11-10" aria-hidden="true" tabindex="-1"></a> filhos_maiores <span class="sc">==</span> <span class="st">"5 children"</span> <span class="sc">~</span> <span class="dv">5</span>,</span>
<span id="cb11-11"><a href="#cb11-11" aria-hidden="true" tabindex="-1"></a> filhos_maiores <span class="sc">==</span> <span class="st">"6 children"</span> <span class="sc">~</span> <span class="dv">6</span>,</span>
<span id="cb11-12"><a href="#cb11-12" aria-hidden="true" tabindex="-1"></a> filhos_maiores <span class="sc">==</span> <span class="st">"7 children"</span> <span class="sc">~</span> <span class="dv">7</span>,</span>
<span id="cb11-13"><a href="#cb11-13" aria-hidden="true" tabindex="-1"></a> filhos_maiores <span class="sc">==</span> <span class="st">"8 children"</span> <span class="sc">~</span> <span class="dv">8</span>,</span>
<span id="cb11-14"><a href="#cb11-14" aria-hidden="true" tabindex="-1"></a> filhos_maiores <span class="sc">==</span> <span class="st">"9 children"</span> <span class="sc">~</span> <span class="dv">9</span>,</span>
<span id="cb11-15"><a href="#cb11-15" aria-hidden="true" tabindex="-1"></a> filhos_maiores <span class="sc">==</span> <span class="st">"10 children"</span> <span class="sc">~</span> <span class="dv">10</span>)) <span class="sc">%>%</span> </span>
<span id="cb11-16"><a href="#cb11-16" aria-hidden="true" tabindex="-1"></a> <span class="fu">filter</span>(<span class="sc">!</span><span class="fu">is.na</span>(filhos_maiores)) <span class="sc">%>%</span> </span>
<span id="cb11-17"><a href="#cb11-17" aria-hidden="true" tabindex="-1"></a> <span class="fu">group_by</span>(filhos_maiores) <span class="sc">%>%</span> </span>
<span id="cb11-18"><a href="#cb11-18" aria-hidden="true" tabindex="-1"></a> <span class="fu">summarize</span>(<span class="at">n =</span> <span class="fu">n</span>()) <span class="sc">%>%</span> </span>
<span id="cb11-19"><a href="#cb11-19" aria-hidden="true" tabindex="-1"></a> <span class="fu">mutate</span>(<span class="at">freq_filhos_maiores =</span> n<span class="sc">*</span><span class="dv">100</span><span class="sc">/</span><span class="fu">sum</span>(n)) <span class="sc">%>%</span> </span>
<span id="cb11-20"><a href="#cb11-20" aria-hidden="true" tabindex="-1"></a> <span class="fu">mutate</span>(<span class="at">freq_filhos_maiores =</span> <span class="fu">round</span>(freq_filhos_maiores, <span class="dv">2</span>)) <span class="sc">%>%</span> </span>
<span id="cb11-21"><a href="#cb11-21" aria-hidden="true" tabindex="-1"></a> <span class="fu">ggplot</span>() <span class="sc">+</span></span>
<span id="cb11-22"><a href="#cb11-22" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_col</span>(<span class="at">mapping =</span> <span class="fu">aes</span>(<span class="at">x =</span> filhos_maiores, <span class="at">y =</span> freq_filhos_maiores, <span class="at">fill =</span> filhos_maiores), <span class="at">show.legend =</span> <span class="cn">TRUE</span>) <span class="sc">+</span></span>
<span id="cb11-23"><a href="#cb11-23" aria-hidden="true" tabindex="-1"></a> <span class="fu">scale_y_continuous</span>(<span class="at">breaks =</span> <span class="fu">c</span>(<span class="dv">0</span>, <span class="dv">10</span>, <span class="dv">20</span>, <span class="dv">30</span>, <span class="dv">40</span>, <span class="dv">50</span>, <span class="dv">60</span>, <span class="dv">70</span>, <span class="dv">80</span>, <span class="dv">90</span>, <span class="dv">100</span>)) <span class="sc">+</span></span>
<span id="cb11-24"><a href="#cb11-24" aria-hidden="true" tabindex="-1"></a> <span class="fu">scale_x_continuous</span>(<span class="at">breaks =</span> <span class="fu">c</span>(<span class="dv">0</span>, <span class="dv">2</span>, <span class="dv">4</span>, <span class="dv">6</span>, <span class="dv">8</span>, <span class="dv">10</span>)) <span class="sc">+</span></span>
<span id="cb11-25"><a href="#cb11-25" aria-hidden="true" tabindex="-1"></a> <span class="fu">scale_fill_gradient</span>(<span class="at">low =</span> <span class="st">"palegreen1"</span>, <span class="at">high =</span> <span class="st">"darkseagreen4"</span>,</span>
<span id="cb11-26"><a href="#cb11-26" aria-hidden="true" tabindex="-1"></a> <span class="at">breaks =</span> <span class="fu">c</span>(<span class="dv">0</span>, <span class="dv">2</span>, <span class="dv">4</span>, <span class="dv">6</span>, <span class="dv">8</span>)) <span class="sc">+</span></span>
<span id="cb11-27"><a href="#cb11-27" aria-hidden="true" tabindex="-1"></a> <span class="fu">labs</span>(<span class="at">y =</span> <span class="st">"Frequência relativa"</span>, <span class="at">fill =</span> <span class="st">"Número de filhos com mais de 7 anos"</span>,</span>
<span id="cb11-28"><a href="#cb11-28" aria-hidden="true" tabindex="-1"></a> <span class="at">title =</span> <span class="st">"Figura 8 - Distribuição relativa de brasileiros casados de acordo com o número de filhos com mais de 7 anos que residem no domicílio"</span>,</span>
<span id="cb11-29"><a href="#cb11-29" aria-hidden="true" tabindex="-1"></a> <span class="at">caption =</span> <span class="st">"Fonte: ISSP, 2002"</span>)<span class="sc">+</span></span>
<span id="cb11-30"><a href="#cb11-30" aria-hidden="true" tabindex="-1"></a> <span class="fu">theme_minimal</span>() <span class="sc">+</span></span>
<span id="cb11-31"><a href="#cb11-31" aria-hidden="true" tabindex="-1"></a> <span class="fu">theme</span>(<span class="at">axis.title.x =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb11-32"><a href="#cb11-32" aria-hidden="true" tabindex="-1"></a> <span class="at">axis.title.y =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb11-33"><a href="#cb11-33" aria-hidden="true" tabindex="-1"></a> <span class="at">plot.title =</span> <span class="fu">element_text</span>(<span class="at">size =</span> <span class="dv">12</span>, <span class="at">face =</span> <span class="st">"bold"</span>, <span class="at">hjust =</span> <span class="fl">0.5</span>),</span>
<span id="cb11-34"><a href="#cb11-34" aria-hidden="true" tabindex="-1"></a> <span class="at">plot.caption =</span> <span class="fu">element_text</span>(<span class="at">hjust =</span> <span class="fl">0.5</span>))</span>
<span id="cb11-35"><a href="#cb11-35" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb11-36"><a href="#cb11-36" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb11-37"><a href="#cb11-37" aria-hidden="true" tabindex="-1"></a><span class="fu">print</span>(filhos_maiores_gráfico)</span></code></pre></div>
<p><img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAqAAAAHgCAMAAABNUi8GAAACfFBMVEUAAAAAACsAAFUAKysAK1UAK4AAVaorAAArACsrAFUrKysrK1UrK4ArVVUrVYArVaorgKorgNRNTU1NTWtNTYhNa6ZNiMRVAABVACtVAFVVKwBVKytVK4BVVStVgIBVgKpVgNRVqqpVqtRVqv9pi2lpjGlqjWpqjmprTU1rTWtrTYhra4hra6Zrj2trkGtrpuFskWtskmxtk21tlW1ulW5ulm5vl25vmG9wmW9wmnBwm3BxnHBxnXFynnFyn3JzoHJzoXNzonN0o3R0pHR1pXR1pnV2p3V2qHZ2qXZ3qnZ3q3d4rHd4rXh5rnh5r3l6sHl6sXl6snp7s3p7tHt8tXt8tnx9t3x9uH19uX1+un1+u35/vH5/vX+AKwCAKyuAVQCAVSuAgCuAgFWAgKqAqoCAqtSAvn+Av3+AwICA1KqA1NSA1P+BwYCBwoGCw4GCxIKDxYKDxoKEx4OEyIOEyYSFyoSFy4WGzIWGzYWGzoaHz4aH0IeITU2ITWuITYiIa02Ia6aIxP+I0YeI0oiJ04iJ1YiJ1YmK1omK14qL2IqL2ouM3IuM3IyN3oyN342O4I2O4Y6O4o6P446P5I+Q5Y+Q5pCR55CR6JGR6ZGS6pGS65KT7JKT7ZOT7pOU75SU8JSV8pSV8pWW9JWW9JaW9paX95eX+JeY+ZiY+piY+5iZ/JmZ/Zma/pqa/5qma02ma2umiE2mxKam4eGm4f+qVQCqVSuqVVWqgCuqgFWqqoCq1Kqq1P+q///EiE3E///UgCvUgFXUqlXUqoDU1NTU1P/U///hpmvh///r6+v/qlX/xIj/1ID/1Kr/1NT/4ab//6r//8T//9T//+H///8b5WRVAAAACXBIWXMAAA7DAAAOwwHHb6hkAAAXlUlEQVR4nO2dh38mx12HV8an14YjINln2aafAjjOwdF7C733TmQH49BEh1DPDoIAofdeQ68XklNwwD69GJDupNdR23+I3dk2uzu776t5tafvSM/zudO+75Tfzs4+7+zM6u7dKAYQJjrrBgD0gaAgDYKCNAgK0iAoSIOgIA2CgjQICtIYQSej+146pXi70ZRQUwucesVuxtH7bZ9KS155PIreO+nEtCMPVqLVU2mdi44z1WrRbpQxXEvqVO2a6zQ5Kl9kQSejpVNqyWbiwvsiqLMpJ6FL0FMkJEF9cQmaqT64oDO3KGUzuuRzgRiiKf6Vo4UPLfp14ZnRfS/Gk+Rqdf8bk5xXPiCKFq4W5V4eRdGrksM9eleUvSizy5T4v0fR/e82u+gIUhVIXqU7NlQBip2U9YtGOSLXWlUmT0YLzz4e3f9i8v7+4lDtKok9V99g6mQepT3SrJO3rdUhnYdwtJYcwMKz1Qh69V2NZnV0Zk+zGylFH5mRapZOrZ3tonZ19FNPUdU9tbjWCTFJReVsBG01pX1cziY0jqPeK1Hy4c/7NUo+cfm14Wps3pfXiLF5k3wgN82LRSu7SMnLpLvoDZIWyOrkF9hGgGQn9fqXth2R660qkycj8+K9RlnE7DxZVfIGZQdQClqrU7St2SHdh9AStDigaZ3Z02xnoxZjawf9nWpaVbxunLSpTasLasfNO6XWR2llI2i7Ke3jcjWhcRyNXplU/bq4/X/m59EL2biyntTKLhJJcrq3hfWDlfTjY2eXKVnVtfKVK0heYGJGpnzaYgcodlLUtxtVj9xoVbXD5NXLUbL4GVeF6lUuvXi0WTsD9Tpl25od0nMI5hJvdeSlF+MXevtherPrKVa3z9aptQHU7uHq6PtPkd09tZOVdkqZVFYuO6zeFOfpaDWhtWe7V8wHoJo6ZQ1JXyd/F171xnwOYx330X9+UP4JK7LzlKzMbvmqI0haoDGFrwWIG41YtStWObVWVcmmx8yP3fJM21Wqfq9d4q06ZduaHdJ3CA1BV2foh6nNrqdYfTRjp1YDqH3SpjUt2WGje2pxi+Sqj7LKxcE3qrSPy9WE+nE0esUStGhbfnDpTKAY2ctPo5nNmIG4yC5TsjJpqN4gaYGxfcyNALHdCLtRjch2q6rkdo/Uq0wXdFx1fqNDug+hQ9BpndnX7HpK2Ufm7M3QqYVr9ZM2tWmZHPWjqMXNOqVKKipXJ6fWlD5Bu3q20SvlbaZs1zWt35N87rKjLD/0u9HCh/zvbnZByLLLlOrT1xmkKDC2l5dWAMcImjXKGblnKDIzmROOoHmdsm2ODuk6hKkjqLsz+5ttpzT7aGqnpknl27L2DE1rj6C1uIWgVVJWubze16u0j6t7BG2f40zQl8sLR1qimgAkZdfLj2GS/P7brzweLY2T1djR02btkGeXKabqK/VZRDNIXiCZXFyNX86bbAfIdmLPQctGveKcgzYrOHukXiXvn+QjWrbGrlO2rdkhPYfQIei0zuxrdvNTk/dRPsRM7dS0SYuFQ3YP9zct65THG91jxS0+tXlSWbmcg9ar9Ana1bONXomqVbxp424xeJulaVR8FMblZTh/UWaXKe11mDtI1FgYNgPY9fNGOSLXWlUlt3ukXqW1OG33YrVCrXdIzyF0CDqtM/ua3RxBy7ZaXd/XInsKWtae3rTdRrRm3LxTiqSycucqvlvQzp6t90pk3Qc1H6L/KW5OHb0hyu9XpZhbdy9md6v+Ky1aZpcp1p2sjiBlgaMXrFt2VYBiJ2X9olGOyLVWlckOQWtVrP5Jm3b53W1Bi7a1OqTnEDoEndaZPc1upBR9ZFJm6dREnerXBUXtGZpWRSu6pxY375QyqajcuA9a5PcK2tWz9V7hH4tAE53f2cX8ayZog6AgDYICzAqCgjQICtIgKEiDoCANgoI08wh6lwKnFgI6QFAElQZBEVQaBEVQaRAUQaVBUASVBkERVBoERVBpEBRBpUFQBJUGQRFUGgRFUGkQFEGlQVAElQZBEVQaBEVQaRAUQaVBUASV5kSC/lsv7fIK9iBo2CAogkqDoAgqDYIiqDQIiqDSICiCSoOgCCoNgiKoNAiKoNIgKIJKg6AIKg2CIqg0CIqg0vQJerdJv6Ct4jAj9+xsBwgjKCOoNAiKoNIgKIJKg6AIKg2CIqg0CIqg0iAogkqDoAgqDYIiqDQIiqDSICiCSoOgCCoNgiKoNAiKoNIgKIJKg6AIKg2CIqg0CIqg0iAogkqDoAgqDYIiqDQIiqDSICiCSoOgCCoNgiKoNAiKoNIgKIJKg6AIKg2CIqg0CIqg0iAogkqDoAgqDYIiqDQIiqDSICiCSmMJenxzI44PbyxfudNVGEEHCwEdWILuLG8YSXce6SqMoIOFgA4qQfdf++aN+PD5rXj/ya2Owgg6WAjooBT0+O3vTEbP/Wt34sPnbmVJrcel9At6Bs9vOSec0bkPglLQnevp5X3viiVoC0bQwUJAB4WgydB53BxBWyDoYCGgg0LQneWU68xBPQog6IA0bjMd37zOKv6kBRB0QLgPiqDS8JskBJUGQRFUGgRFUGkQFEGlQVAElQZBEVQaBEVQaRAUQaVBUASVBkERVBoERVBpEBRBpUFQBJUGQRFUGgRFUGkQFEGlQVAElQZBEVQaBEVQaRAUQaVBUASVBkERVBoERVBpEBRBpUFQBJUGQRFUGgRFUGkQFEGlQVAElQZBEVQaBEVQaRAUQaVBUASVBkERVJo+QVvP8+kX9AweMHROuGdnO0BOdwT9q17aARXGP0ZQaRAUQaVBUASVBkERVBoERVBpEBRBpUFQBJUGQRFUGgRFUGkQFEGlQVAElQZBEVQaBEVQaRAUQaVBUASVBkERVBoERVBpEBRBpUFQBJUGQRFUGgRFUGkQFEGlQVAElQZBEVQaBEVQaRAUQaVBUFlBD1YW083ufS+lP6OlE1XOalWMo4VnH1ifmD8+jenBFbGx+93IsOoRHUGFBTVn1Jzro7UTntyGIQcrpv4ggs6we8PmpW2PSAgqLOgHX952n+vpNGrlWp6loLsLXjtGUGFBVzeXzLk2Uhm5nh1F0dJkZK6WR2tRlHgwefDbk036ZrGsGC08k+TkBRLSGouT/BL/TFRWX8zziotvkZZv6/uLmwmm5pKR3w7S3n0WumheWe3ZUWdDKhBUWdDJgy/VBB0lV8lxlP5IlUzO6vjS9mS0mJ3+QoGDlaXkb1UgTTMSZYKOqurp3yz2yIiRvk8nA2WevT8Txk4w04axaZ0dxLX72BpAy2o9DbFAUGVB4/FSXdDV/Bwmb8xVNJU4fW/e5NdVs0nOfFEgTbMFtaqnsR+sLsbF5b/Ms/dnCtgJ79mOi0mDHcS1+4TNYgAtq/U0xAJBpQU9eHS9dolfz11JfoyzlfGSeb+bjlS5RWbUSk53USBNswTNq5c1Nqu5QTFzLPJq+yvCWD/SxfnCeiOIa/e2qXa1roZYIKi0oPF4sVPQ/OrZLai1au4R1EwarbE3nlXQg5WF9bJUFcS1e3vVVKvW0RALBNUW9OipZzoELSZ1maDpG/sSn/ywl80OQa0a9kTARMjz+gU1Zu0ulPcF8iCu3dcmo3a1joZYlILuLS8/vBXHhzeWr9zp6jIEHSyEg+xk7UbpcmQpWUcs1AU9WkvOdHGi64ukxXyVkhVI09qCFjWMGrljRVp93dIpaDoSjkwD7CCu3VtT0Niq1tkQi0LQ/Se34p1H4uObG+mmAwQdLISDfDTZTG8ljaLowx5tXHLT2zPZ1TKu7tVkFav7PNYwWxe0rJHNCLOardtMvXPQZNK48D3JKi15aQdx7D55Xf0izKrW2ZAK+xKfSHr4/JZx1Q2CDhYCOrAFTYbO/Wt34sPnbmXvW49L6Rc0KdAv6L1/vksgnMWJD4VK0P0nHroV712xBG3BCDpYCOjAHkETM2sjaAsEHSwEdFC7zXR7gzmoRwEEHZBC0PzafnzzOqv4kxZA0AEpR9Cd5eVkDsp9UI8CCDog/CYJQaVBUFlBX+3GJ1TAIKisoB/uxidUwCCorKAf4cYnVMAgqKygH+nGJ1TAIKisoB/lxidUwCCorKAf7cYnVMAgqKygH+PGJ1TAIKisoB/rxidUwCAogkqDoLKCfpwbn1ABg6Cygn68G59QAYOgsoJ+ghufUAGDoLKCfqIbn1ABg6Cygn6SG59QAYOgsoJ+shufUAGDoLKCfoobn1ABg6Cygn6qG59QAYOgsoJ+mhufUAGDoLKCfrobn1ABg6Cygn6GG59QAYOgsoJ+phufUAGDoLKCfpYbn1ABg6Cygn62myJ7Mmp/HfE5BEFlBf0cN3nuwaPr8djr0VhhgaCygr7OTZ47ubwdHzx2/odQBJUVNOVza9g5jKAOEHSwEA4+z02RfbASXQA/EVRX0M93k+eab4a/AKskBJUV9Avc5Lnp01zSy/x5B0FlBf1CN3kuI6gDBB0shIMvclNk77oe2nL+QFBZQb/YjU+ogEFQWUG/xI1PqIDpE7T1PJ9+Qe/ynCRP3N3/pW4G0UAXRlDZEfTL3PiEChgElRX0y934hAoYBJUV9Cvc+IQKGASVFfQr3fiEChgElRX0q9z4hAoYBJUV9Kvd+IQKGASVFfRr3PiEChgElRX0a934hAoYBJUV9Ovc+IQKGASVFfTr3fiEChgElRX0G9z4hAoYBJUV9Bvd+IQKGASVFfSb3PiEChgElRX0m934hAoYBJUV9FvcFNlHa/yL+iYIOlgIB9/qpsjeXDX/ce68g6Cygn6bmzz3InyrSAqCygqa8voads7k8tNc4psg6GAhHHynmzx3Mlo138903kFQWUG/y02ea748jC9uqIOgg4Vw8N1u8tyDD0TQFgg6WAgH3+emyN7kEt8CQQcL4eD73RTZByt8w3ITBB0shIMfcOMTKmAQVFbQH3TjEypgEFRW0B9y4xMqYBBUVtAfduMTKmAQVFbQH3HjEypgEFRW0B914xMqYBBUVtAfc+MTKmAQVFbQN7nxCRUwCCor6I+78QkVMAgqK+hPuPEJFTAIKivoT7rxCRUwCCor6E+58QkVMKWg+08sL2/E8eGN5St3ugoj6GAhHPy0G59QAVMIevjcrXj/NbeOb27EO490FUbQwUI4+Bk3PqECphB0L7Xy9sbh81vx/pNbHYURdLAQDn7OjU+ogLHnoMkoun/tjhlMDa3HpfQLepfH0HjiPjU/72ZoI8SwBD2+eT3eu2IJ2oIRdLAQDt7ixidUwFSCHt64niyVriHoiQsMJOgvuKkKHK2t+sQNC2sVn6zhY+agHgUGEvQX3VQFxtEFEjTz01zmWcWfsMBAgv6SmzJ/8j6PXyBBd5ZTNrgP6lFgIEFT3lqjlnX01PdeqEv8LCDoYCEc/LKbInu8dLHmoLOAoIOFcPArbvLcyeVtBG2CoIOFcNAv6DhKWfIJHBQIKivor7qpCjCCNkHQwUI4+DU3VQEEbYKgg4Vw8OtufEIFDILKCvobbnxCBQyCygr6m258QgUMgsoK+ltufEIFDILKCvrbbnxCBQyCygr6O258QgUMgsoK+rtufEIFDILKCvp7bnxCBQyCygr6+258QgUMgsoK+gdufEIFDILKCvqHbnxCBQyCygr6R258QgUMgsoK+sdufEIFDILKCvonbnxCBQyCygr6p258QgUMgsoK+mdufEIFDILKCvrnborsySi6SP8vfiYQdLAQDv7CTZ6bPul48gBPO66BoIOFcPCXbvLc3cXYPPH4vIOgsoKmvK1GM5fnxTdA0MFCOHibm6rA0dr5/1/HCKor6F+7KfMPVi6AnwiqK+jfuCmyJ6PzPwGNEVRY0L91k+deED8RVFfQv3OT52ZffXP+JUVQWUH/3o1PqIBBUFlB/8GNT6iAQVBZQf/RjU+ogEFQWUH/yY1PqIDpE7T1PJ9+Qe/ynCRP3N3/z24G0UAXRlDZEfRf3PiEChgElRX0X934hAoYBJUVFFIQFEGlQVAElQZBEVQaBEVQaRAUQaVBUASVBkERVBoERVBpEBRBpUFQBJUGQRFUGgRFUGkQFEGluceCdjz7p/MRQAr+IehZgqAIKg2CIqg0CIqg0iAogkqDoAgqDYIiqDQIiqDSICiCSoOgCCoNgiKoNAiKoNIgKIJKg6AIKg2CIqg0CIqg0iAogkqDoAgqDYIiqDSWoPtPbsXx4Y3lK3e6CiPoYCGgg0rQveWHt+LjmxvxziNdhRF0sBDQQSno7YfekYygh89vZSOpEwQdLAR00LjE71+7Ex8+dytLaD0upV/QuzM8hqZf0Hv+/BcRzuTMB0JD0L0rlqAtGEEHCwEd9I2gLRB0sBDQQUNQ5qAeBRB0QBqCHt+8zir+pAUQdEC4D4qg0vCbJASVBkERVBoERVBpEBRBpUFQBJUGQRFUGgRFUGkQFEGlQVAElQZBEVQaBEVQaRAUQaVBUASVBkERVBoERVBpEBRBpUFQBJUGQRFUGgRFUGkQFEGlQVAElQZBEVQaBEVQaRAUQaVBUASVBkERVBoERVBpEBRBpUFQBJUGQRFUGgRFUGkQFEGlQVAElaZP0NbjUvoFvctjaDy5Z2c7QBhBGUGlQVAElQZBEVQaBEVQaRAUQaVBUASVBkERVBoERVBpEBRBpUFQBJVGTdC39tJuEoKecxAUQaVBUASVBkERVBoERVBpEBRBpUFQBJUGQRFUGgRFUGkQFEGlQVAElQZBEVQaBEVQaRAUQaVBUASVBkERVBoERVBpEBRBpUFQBJUmOEHf1Eu7zQgaNgiKoNIgKIJKg6AIKg2CIqg050/Q1/fSPigElQZBEVSapqCHN5av3OkqjKCeJRDUm4agxzc34p1Hugoj6KwlXt3L1IBQ0hD08PmteP/JrY7CCDprCQQ9LRqC7l+7Ex8+dyt7c9aPD7ow3POzHhANQfeuWIJOQ+H34AoFmIMOSN8IOg0FORQKIOiAnGgO2kBBDoUCCDogrVX89Z5VfAMFORQKIOiAnOg+aAMFORQKIOiAnOg3SQ0U5FAogKADgqAIKg2CIqg0CIqg0iAogkqDoAgqDYIiqDQIiqDSICiCSoOgCCoNgiKoNAiKoNLMIyjA4CAoSIOgIA2CgjQICtIgKEiDoCANgoI0CArSDCfo/hPLyxtzxki/y2y++ssP3ZorQnIUD8/4NQFdEdKvGTjJf5YFm8EETb+fZP81t+YLsjOn4rc3zJf5+JMexc5cEfZSwfu/NBB6GEzQvfR83J7Pr/3XvnmuAOn3pMyH+SqgeaLcfugdyQh6oi9sAZtB56Azf8uTm+O3v3O+S/z+tX+f8xI//whqxDzRV16BzZCCpt+jMw871+ecg+4/sWHcmIP5J4+poCf60kCwGVDQwxvz+ZmoNa+gcw9c6Sx6b75VEiPoXAy5ip9zDb+znDKP5Ic/O68XpzD07TMHnYfBBJ3bz5R5bzPdnvcSf0oj6Im+NBBsBhM0G//mlHReQZMZ5Jx3MfeW576Tyn3QeeA3SSANgoI0CArSIChIg6AgDYKCNAgK0iAoSIOgIA2CgjTqgk5GUcJSI/HBl1rvD1ai6L4kOd826qVvV03mpe1ykyeCMvKCNlx0JibvD1YS1caXtoutKXLw6HpWIH0xeWD9aG01Hi/G+SZPvAcHAf6EImgy6KXj4uWnk0HPvM4TTHbysxCytk1NNOwuJj82Vw8eMzXyTZ54VkcGMxGKoJtL8W4yLo6yTZKYJIwXq0JHa+lFO3Uy25p6tfExtfbytrXJE+/l0cCJkRc0nUsml+Nk0MvHxWy4TM1KE7NCqY27UbSQ2pZtszmoNTwerRm30yj5Jk8EaeQFzUbQdHP0lC1oshbKhKwKlSNmsm1OUw9WEhWbI6hJBGkCEbQ9gj72Uq2QmVAmM8pi2xB0MlrNo1Rz0DwRpAlE0GIOWgqaJ5SFzOo9UbjY1gXNVUyv6GYVbzb4GQKhCFot2s2KyKzi06lmsYo39z8X1uNiW171zXYcZTPS2n3QIhGUURd0bv7DcR8VwuG8C3r0HWfdApiL8y4oBA6CgjQICtIgKEiDoCANgoI0CArS/D+bVM3tuWD4OQAAAABJRU5ErkJggg==" /><!-- --></p>
</div>
</div>
<div id="lugar-de-mulher-é-na-cozinha" class="section level3">
<h3>“Lugar de mulher é na cozinha”?</h3>
<div id="opiniões-sobre-os-pápeis-de-gênero" class="section level4">
<h4>Opiniões sobre os pápeis de gênero</h4>
<div class="sourceCode" id="cb12"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb12-1"><a href="#cb12-1" aria-hidden="true" tabindex="-1"></a><span class="co"># Distribuição relativa de brasileiros casados de acordo com o grau de concordância com a frase "Tudo bem trabalhar fora de casa, mas o que as mulheres realmente querem são um lar e filhos" por sexo</span></span>
<span id="cb12-2"><a href="#cb12-2" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb12-3"><a href="#cb12-3" aria-hidden="true" tabindex="-1"></a><span class="co"># Obs.: Antes de elaborar o gráfico, foi necessário criar o labeller "opiniao" para que pudéssemos traduzir as categorias desta variável.</span></span>
<span id="cb12-4"><a href="#cb12-4" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb12-5"><a href="#cb12-5" aria-hidden="true" tabindex="-1"></a>opiniao <span class="ot"><-</span> <span class="fu">list</span>(</span>
<span id="cb12-6"><a href="#cb12-6" aria-hidden="true" tabindex="-1"></a> <span class="st">"Strongly Agree"</span> <span class="ot">=</span> <span class="st">"Concordo totalmente"</span>,</span>
<span id="cb12-7"><a href="#cb12-7" aria-hidden="true" tabindex="-1"></a> <span class="st">"Agree"</span> <span class="ot">=</span> <span class="st">"Concordo"</span>,</span>
<span id="cb12-8"><a href="#cb12-8" aria-hidden="true" tabindex="-1"></a> <span class="st">"Neither agree nor disagree"</span> <span class="ot">=</span> <span class="st">"Não concordo nem discordo"</span>,</span>
<span id="cb12-9"><a href="#cb12-9" aria-hidden="true" tabindex="-1"></a> <span class="st">"Disagree"</span> <span class="ot">=</span> <span class="st">"Discordo"</span>,</span>
<span id="cb12-10"><a href="#cb12-10" aria-hidden="true" tabindex="-1"></a> <span class="st">"Strongly disagree"</span> <span class="ot">=</span> <span class="st">"Discordo totalmente"</span>)</span>
<span id="cb12-11"><a href="#cb12-11" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb12-12"><a href="#cb12-12" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb12-13"><a href="#cb12-13" aria-hidden="true" tabindex="-1"></a>opiniao_labeller <span class="ot"><-</span> <span class="cf">function</span>(variable, value){</span>
<span id="cb12-14"><a href="#cb12-14" aria-hidden="true" tabindex="-1"></a> <span class="fu">return</span>(opiniao[value])</span>
<span id="cb12-15"><a href="#cb12-15" aria-hidden="true" tabindex="-1"></a> }</span>
<span id="cb12-16"><a href="#cb12-16" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb12-17"><a href="#cb12-17" aria-hidden="true" tabindex="-1"></a>casa_filhos_sexo <span class="ot"><-</span> brasil_casados_vs <span class="sc">%>%</span> </span>
<span id="cb12-18"><a href="#cb12-18" aria-hidden="true" tabindex="-1"></a> <span class="fu">filter</span>(<span class="sc">!</span><span class="fu">is.na</span>(mulher_casa_filhos)) <span class="sc">%>%</span> </span>
<span id="cb12-19"><a href="#cb12-19" aria-hidden="true" tabindex="-1"></a> <span class="fu">group_by</span>(sexo, mulher_casa_filhos) <span class="sc">%>%</span> </span>
<span id="cb12-20"><a href="#cb12-20" aria-hidden="true" tabindex="-1"></a> <span class="fu">summarise</span>(<span class="at">n =</span> <span class="fu">n</span>()) <span class="sc">%>%</span> </span>
<span id="cb12-21"><a href="#cb12-21" aria-hidden="true" tabindex="-1"></a> <span class="fu">mutate</span>(<span class="at">freq_casa_filhos =</span> n<span class="sc">*</span><span class="dv">100</span><span class="sc">/</span><span class="fu">sum</span>(n)) <span class="sc">%>%</span> </span>
<span id="cb12-22"><a href="#cb12-22" aria-hidden="true" tabindex="-1"></a> <span class="fu">ggplot</span>(<span class="fu">aes</span>(<span class="at">x =</span> sexo, <span class="at">y =</span> freq_casa_filhos, <span class="at">fill =</span> sexo)) <span class="sc">+</span></span>
<span id="cb12-23"><a href="#cb12-23" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_bar</span>(<span class="at">stat =</span> <span class="st">"identity"</span>, <span class="at">show.legend =</span> <span class="cn">TRUE</span>) <span class="sc">+</span></span>
<span id="cb12-24"><a href="#cb12-24" aria-hidden="true" tabindex="-1"></a> <span class="fu">facet_grid</span>(mulher_casa_filhos <span class="sc">~</span>., <span class="at">labeller =</span> <span class="fu">as_labeller</span>(opiniao_labeller, <span class="fu">label_wrap_gen</span>(<span class="at">width =</span> <span class="dv">15</span>, )))<span class="sc">+</span></span>
<span id="cb12-25"><a href="#cb12-25" aria-hidden="true" tabindex="-1"></a> <span class="fu">coord_flip</span>() <span class="sc">+</span></span>
<span id="cb12-26"><a href="#cb12-26" aria-hidden="true" tabindex="-1"></a> <span class="fu">ylim</span>(<span class="fu">c</span>(<span class="dv">0</span>, <span class="dv">90</span>)) <span class="sc">+</span></span>
<span id="cb12-27"><a href="#cb12-27" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_text</span>(<span class="fu">aes</span>(<span class="at">label =</span> <span class="fu">round</span>(freq_casa_filhos, <span class="dv">2</span>)), <span class="at">hjust =</span> <span class="sc">-</span>.<span class="dv">1</span>) <span class="sc">+</span></span>
<span id="cb12-28"><a href="#cb12-28" aria-hidden="true" tabindex="-1"></a> <span class="fu">scale_fill_manual</span>(<span class="at">label =</span> <span class="fu">c</span>(<span class="st">"Masculino"</span>, <span class="st">"Feminino"</span>), <span class="at">values =</span> <span class="fu">c</span>(<span class="st">"lightblue3"</span>, <span class="st">"hotpink1"</span>)) <span class="sc">+</span></span>
<span id="cb12-29"><a href="#cb12-29" aria-hidden="true" tabindex="-1"></a> <span class="fu">theme</span>(<span class="at">strip.text =</span> <span class="fu">element_text</span>(<span class="at">size =</span> <span class="dv">12</span>)) <span class="sc">+</span></span>
<span id="cb12-30"><a href="#cb12-30" aria-hidden="true" tabindex="-1"></a> <span class="fu">labs</span>(<span class="at">title =</span> <span class="st">"O que as mulheres querem é casa e filhos"</span>,</span>
<span id="cb12-31"><a href="#cb12-31" aria-hidden="true" tabindex="-1"></a> <span class="at">caption =</span> <span class="st">"Fonte: ISSP, 2002."</span>)<span class="sc">+</span></span>
<span id="cb12-32"><a href="#cb12-32" aria-hidden="true" tabindex="-1"></a> <span class="fu">theme_minimal</span>() <span class="sc">+</span></span>
<span id="cb12-33"><a href="#cb12-33" aria-hidden="true" tabindex="-1"></a> <span class="fu">theme</span>(<span class="at">axis.title.y =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb12-34"><a href="#cb12-34" aria-hidden="true" tabindex="-1"></a> <span class="at">axis.ticks.y =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb12-35"><a href="#cb12-35" aria-hidden="true" tabindex="-1"></a> <span class="at">axis.text.y =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb12-36"><a href="#cb12-36" aria-hidden="true" tabindex="-1"></a> <span class="at">axis.title.x =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb12-37"><a href="#cb12-37" aria-hidden="true" tabindex="-1"></a> <span class="at">strip.text.y =</span> <span class="fu">element_text</span>(<span class="at">angle =</span> <span class="dv">0</span>),</span>
<span id="cb12-38"><a href="#cb12-38" aria-hidden="true" tabindex="-1"></a> <span class="at">plot.title =</span> <span class="fu">element_text</span>(<span class="at">hjust =</span> <span class="fl">0.5</span>),</span>
<span id="cb12-39"><a href="#cb12-39" aria-hidden="true" tabindex="-1"></a> <span class="at">plot.subtitle =</span> <span class="fu">element_text</span>(<span class="at">hjust =</span> <span class="dv">1</span>),</span>
<span id="cb12-40"><a href="#cb12-40" aria-hidden="true" tabindex="-1"></a> <span class="at">plot.caption =</span> <span class="fu">element_text</span>(<span class="at">hjust =</span> <span class="fl">0.5</span>))</span></code></pre></div>
<pre><code>## `summarise()` has grouped output by 'sexo'. You can override using the `.groups` argument.</code></pre>
<div class="sourceCode" id="cb14"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb14-1"><a href="#cb14-1" aria-hidden="true" tabindex="-1"></a><span class="fu">print</span>(casa_filhos_sexo)</span></code></pre></div>
<p><img 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PHZt2oegnjGaU6j+vDbBjWD2CZGVA76rgAd6PpfTkGIEtQHDQiqCQesDVcGZlhbOZ5BUB80LqgevjaIplGS4xkE9UEDgiZHVB6Ye06DU5hEob6IgmlA0OSIyqYJGhWtcjyDoD5oooq3IyrrUZb1S3xyBTmeQVAf4Fk8BGUNBIWgrIGgEJQ1EBSCsgaCQlDWQFAIyhoICkFZA0EhKGsgKARlDcYHbUMWBQNB25BFwUDQNmRRMBC0DVkUDARtQxYFM0lQABoFggLWQFDAGggKWANBAWsgKGANBAWswX3QNmRRMBC0DVkUDARtQxYFA0HbkEXBQNA2ZFEwkwT9II9JB5bz6UFQzkBQCMoaCApBWQNBIShrICgEZQ0EhaCl0VMGrtAgr3qaQJoF42B5UW/OT45dDAgKQcti52xZ0TNd0VDu/Xn6R5vR5FcnBYJC0LK4qYTMpAPLK8rYuypIb7q5MU4MBIWgpembqtyO375opxLS0w9Ekw6cEAgKQU/AwbJqfA7CyYH7JCwElR5xhgTVVfvQTnGl6vUfqYpeb/Ko4mMTv+vy3qyaKZDkfHoQtCRaQlVUjnrqg1daUjNUhTHqJMUnfqcpjPWE73bOODmfHgQty1CVT3P3zG0mtezruYXmGd1mik38bm45XLwXTgov59ODoJw5kaCxid/DwtRNCi/n04OgnJk0X3yuoDvJid9/8rlHbl1PCg8aoDmN6uMkJWh84vfoBkOAEpTbCSVz4ttMdl5t3T8y6xCU2wklU5Wgur8EQXmeUDInETQ+8XtsHYJyO6FkTiJofOJ3Pa32AG1QlieUzImq+OTE7+5JEgTldsKaOOmMQ4XAs/jZFXS7u7p9tey5CgBBZzRivSfcX1ql18ubR3//X2vnN8uc52httchuEHRGI9YtKFmpBC17FghaSzxBEWsW9PJ/XjCC7i91u8q0w5tdW5CqtXPrdnv/yqvu3SjsuTvnN9Xq43dWY7FygaAzGrFuQTc3Vun18Na69nTjarD7xMPAFIxqzWzvL+lFKkwZS6vK3DBWPhB0RiPWLujhnz60Vfzh7U31LyBXXbVvt3URe3nzWBitKmujWPlA0BmNWLugwfZVLd5GV1XTtHZ0Xwt65aF9X207QTPCVMTVKFY+EHRGI9Yv6NH9f1Dl6E1T0zdUgu4t0NPv/tiffuxdeuB+GpoHBJ1FQXVXXiv47HqyDUotVNPeNIIeC6usDbp38emt4OD3x/o3yc4A44M2EdGDoMG26oJvd1P98USP3Vbn6TClcTW9+L1Lf3Av2PtDpSD9dG1F/0DE/IC+M3ePzDTFJ/176qt6B/0T0fRJIGgbslgPkwT9t5Xg53cvPaCvECkND64/oO+80Rc4hmd/mRB0YVF/paO/mPiVmwGCtiGL9TBJ0DefGf3Vm6YSV3bar72ZWj1ZgpoNMtjuFGOSoNmJyEhPGjmfHgQtySRBf/w37/yR9rGvK3dV08+psvQp/Y23DEFpMXoFgjYfsS2CPvj+1xepZKRRm0xBqmpwlKD8IzYsqOq4T3hSX8mzeKXcUPeGtH8X71HzUv1RG3Tv0o+UiINTSUHLtUEhaPURmxf0xHtoJgpq5Rt0OmdurNiK3g6coMJ+83pK0FK9eAhafcSaTxj7Gsh5umf/Wrd7dVf96TfNV0GoBN3t6vtI0r8sAkGrj1i3oOZrIHSrffuCKg0vqJAL7vt35ja8fcCk3xb+ZREIWn3EugU1t+DpQaWykB6o0595bmkfZNq3g4zHn9K+LAJBq4/oSdCb3a6qvZOCxr4Ksr9Edbv4L4tA0OojehL0tq7T80pQes89fg/KlaBegKCzKqhtRSYFjdqg1MC0X1gu+2URL0DQmRXU9M9Tgpqvgmh/M3rx031ZpNzX3KakCkGHZhB9PQSO/n38YipsGuR4xlVQb4gRVNO3zwD683oyJ30x+8eeC0xGjmcQVJKgbiB9PawIDYGzE4VNhRzPIKggQZOD5htByw2kL8czCOpZ0MxBeycKanZ79FhsVOX3vnTtWBjwQMVuTEJSCdqPCkvVS6Km5048bArkFIQoQeUIakexddBgoTupsKLI8QyCyhE0Na8YublTcq4xOZ5B0LGC6lneOovHo0U/5Szwo86KBI1mawxnvt0ZlLjHFEjyDIKOF7SAfQWoRtCouRmOurxTrgkqyDMIWkhQ8zXk0StfV8XpkIrU6IfGk35yTFQiqB5iOUiOtPx+L6N0L4AczyBoIUH7i+bXxvN6rJHED40n/eSYwLN4CFqWAm3Qef0zuIPrD+jnmvSnNhO/4xz7gzkCgkLQshQqQWkeg87cvQmCZv/kmICgELQsxQS9rhcoQQVFbJWgtnU5QVC0QTlFbJeg5mfGkwSttxefhZxPD4KWZLygFQFBIWhZIOiMRoSgU4DhF9uQxXqAoDMacVYE9QIEbUMWBQNB25BFwUDQNmRRMBC0DVkUzCRBAWgUCApYA0EBayAoYA0EBayBoIA1EBSwBvdB25BFwUDQNmRRMBC0DVkUDARtQxYFA0HbkEXBTBI0+1vTBb5LLefTg6CcgaAQlDUQFIKyBoJCUNZAUAjKGggKQVkDQSEoayAoBGUNBIWgrIGgEJQ1EBSCsqZqQWlIcj29x0404UeQM7pzJnI8g6A+qFjQUe/slpmUZkev2ynj+8Un5pbjGQT1QcWC6ini9WxzO2bqeHoxg0AXRI5nENQHVQtKbmozY4IO5/VqMeR4BkF9MGm++GkE3bFzxD/q6Pni33/ps2/tvKH+dnbefRJTx3ugOY3qo+IS9GCZZr2jyRfpavVdJwklaKMnlEwNvfi5u6aKN7LqyUUgaKMnlEwd90FtGzRqj0LQZk8omYoF1SbqmeIhKJ8TSqby+6A067Jqgtoq3t4HhaCNnlAydTxJWiFRf92so5PE4ISSwbN4CMoaCApBWQNBIShrICgEZQ0EhaCsgaAQlDUQFIKyBoLOtqD7S13Fqlq5vDluv6O11bKpqhcMvzjbWdReHt6caB8ErTueoIjeBQ32rzykld1u97z2tXtunV7Vxv5zd85vqtXH76zaEGZA0NnOohH08Na6Wjm8vRlsX9CF5e4TDzeu0uv+kio5aVU1A0xI2cTVBASd7SwaQY/ua0FvrUdBZKvxVq8qa21I2cTVxCRBXx9PfkQJn15DEZsqQanHpOp2Vd/bN4y3Zp+NVRtSNnE1AUHbICjV5aYXH66hBC2ZIDmeichi2ItXK9TAVH/UBlVbtg2qS0/BbVAIWn3Exu6DbmT04knQozW5vXgIWn1EPEmaAggKQVkDQSEoayAoBGUNBIWgrIGgEJQ1EBSCsqYKQcMxwqJBlaPBladFjmcQ1AcVCNpfdAOIhIMqq+VbLmxK5HgGQX1wckHDcWpj6+rfzjTDicSQ4xkE9cHJBR3GCkoIyvKEkpk0wvIEQdUeP/nco07nM9/Re7tBlWODKwN/NKdRfZy8BO135mPFqOsw9dFJ4nNCyVQgKIl4sExDLoaDKqvljh1ceVrkeAZBfXByQQeqAHWCujFr1RJtUD4nlEwFnSSS0k4lB0FZnlAyJxdUTyw3sFMe2kGVqYrHfVA2J5RMBTfq7VMjLaobVDkaXHla5HgGQX2AZ/EQlDUQFIKyBoJCUNZAUAjKGggKQVkDQSEoayAoBGUNBIWgrMHwi23IomAgaBuyKBgI2oYsCgaCtiGLgoGgbciiYCYJCkCjQFDAGggKWANBAWsgKGANBAWsgaCANRAUsAY36tuQRcFA0DZkUTAQtA1ZFAwEbUMWBQNB25BFwUwS9IOTM12C5HgGQX0AQSEoayAoBGUNBIWgrIGgEJQ1EBSCsgaCQlDWQFAIyhoICkFZA0EhKGsgKARljTdB7UxK4cTIwbCjWdEzgkST0snxDIL6wJug/Tnj5ag3F5vfy8ypFMTmVJLjGQT1gSdBVSlpvRycjk1AN1SB9BeblU6OZxDUB54EHc5bBfcuvRkJOurN2zUIWmtEwUyaL74CQc2B3n3y5R2aUP6aWdE8esytYm75KmhOo/rw1gY1ZeRgPj7HbN8VoIOoXSqnIEQJ6gO/gu5dehAT1M7hrfzsrIQnlOMZBPWBX0EH7taSZmhvLvXj/Xo5nkFQH3iu4uMrbg7vQXQTNJDkGQT1QZOCmiZorE1KyPEMgvqgGUH13PL6JV3tC/IMgvoAz+IhKGsg6GwLur/UVayqlcub4/Y7Wlstm6p6gaAzLih5eXhzon0QtChyPJMjaLB/5SGt7Ha757Wv3XPr9Ko29p+7c35TrT5+Z9WGMAOCtkHQw1vrauXw9mawfUEXlrtPPNy4Sq/7S6rkpFXVDDAhZRNXExC0DYIe3deC3lqPgshW461eVdbakLKJqwkI2gZBrYmqx6TqdlXf2zeMt2afjVUbUjZxNQFB2yAo1eWmFx+uzUoJOtOfXkMRG+nFqxVqYKo/aoOqLdsG1aWn4DboTH96DUVs7D7oRkYvngQ9WpPbi5/pT6+hiHiSNAUQtA1ZFMwkQV8vA0WU8+lBUM5A0NkVNHr8nrU2bn9GQFAIenx/RkDQmRVUd8qjF+rP6/tLR/df63av7qq/wHXlr7yq3ot2LZu+OoCgMyuoubPk7nbSLXi1IEHXLgT7Sxfc29u0Fd4TNQGMgKAzLWjseVGgnx7pEnRdP9JU4WStCbTy2oCyCawBCDrTgsaeuJvb9ClBb3a73XPrMUFNQNkE1gAEnWlBoxLUPu5MCWoKy5igrEpPAoLOtKBRG1RL+Ox6UtDobVfcsnseD0FnV9CjNdcrp7XtLj1wTwlqHstbQe3+rGp4CDrDgs4EdQrqBlUOB1dODKq8mH1COZ5BUB/UKagbcykx9hINpjzq0V+2oXI8g6A+qE9QN6hyNLiyJhxUeZgYkilEjmcQ1Af1CeoGVQ4HV9boQZW1m6kxmRxyPIOgPpg0wnIpQW1cN5ZybExlM6iyeelcq3vE4bbRnEb1UWcb1JWR8bJSj2hHE3uMerFRa2PIKQhRgvrAs6B2UGVql95FFe8tomA8CxrrGaEN6i+iYDwLagZVNsOBh3N3JZDjGQT1gWdBzaDK1JXfW8hsggryDIL6wJug8UGV9ZOkbD8FeQZBfYBn8RCUNRAUgrIGgkJQ1kBQCMoaCApBWQNBIShrICgEZQ0EhaCswfCLbciiYCBoG7IoGAjahiwKBoK2IYuCgaBtyKJgJgkKQKNAUMAaCApYA0EBayAoYA0EBayBoIA1EBSwBoIC1owV9JNvPf+7v/KVkuDjP3v++W8Hwf89//zzv/MzL2e0p/KWTTof5dFjFsUzTtBPv6uu5e/5Ssknf/u94OM//17w02/7OqM9ld9sfqj+L3jMonjGCfrJ3/0s+PgvfP1P/5Ac+em3P/3H73k6YWBP5TWb9N/QYxblM07Qj//yV/qC+kOdTdW3uqb3cTZzKq/ZpKLaYxblM05Qqo28Cvrpd1/UtbynIsaeymc29Xk8ZlE+nErQT771ol3z2g71mc0Pw94Y2qHF4NMGVb348DPzKqjPbP70xXANghZifC/+RY/dW+snlTGf/pMXXeypPGbTVOwesygfPvdBYzcJf9tXj8Wcyl82bUvCYxbFgydJgDUQFLAGggLWQFDAGggKWANBAWsgKGANBAWsgaCANRAUsEasoHsLHcViKvDSg2PbNKsdTWFrl6l4tLmi36SpQ+3CBgIGyBU05WJmoNrWE4APzm65pd7l4AU7eyit7F28N+qtBAOaw14vbKCHTICJiBdUFXpULj71VVXo6XUboN9Wr07IxJJM1Axpctv+ysF1HcMubGBTOQNxxAvaXwyGqlxcMAsVqAIG89FOo56Z9tstdbxE+UjWPrUVW9hAn7kBecgVlNqSqjpWhZ4tF01xSWZRoNmJbBx2OnNkm1maNmiseKQZmJXbdBS7CKJpmUHTyBXUlKC0GL0SF1T1hYyQ0U7xicHTzdSDZaViugTVgYAD0gU9XoJef5DYSTcoVYvSLVOC7i2s2KNEbVAbCDggXVDXBg0FtQHhTrr3rhR2y6SgVkWq0XUvXi/gJyPECxp12nWPSPfiqanpevH6/ufcvcAtw1pfLwcd0yJN3Ae1gZk3soBnxAp6Yv4Z+kmgtYKOvtF0CkARWisokAEEBayBoIA1EBSwBoIC1kBQwBoICljz/+mDoyOKb4IPAAAAAElFTkSuQmCC" /><!-- --></p>
<div class="sourceCode" id="cb15"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb15-1"><a href="#cb15-1" aria-hidden="true" tabindex="-1"></a><span class="co"># Distribuição relativa dos brasileiros casados de acordo com o grau de concordância com a frase "Ser dona de casa é tão gratificante quanto ter um emprego" por sexo</span></span>
<span id="cb15-2"><a href="#cb15-2" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb15-3"><a href="#cb15-3" aria-hidden="true" tabindex="-1"></a>casa_realização_sexo <span class="ot"><-</span> brasil_casados_vs <span class="sc">%>%</span></span>
<span id="cb15-4"><a href="#cb15-4" aria-hidden="true" tabindex="-1"></a> <span class="fu">filter</span>(<span class="sc">!</span><span class="fu">is.na</span>(casa_realização)) <span class="sc">%>%</span> </span>
<span id="cb15-5"><a href="#cb15-5" aria-hidden="true" tabindex="-1"></a> <span class="fu">group_by</span>(sexo, casa_realização) <span class="sc">%>%</span> </span>
<span id="cb15-6"><a href="#cb15-6" aria-hidden="true" tabindex="-1"></a> <span class="fu">summarise</span>(<span class="at">n =</span> <span class="fu">n</span>()) <span class="sc">%>%</span> </span>
<span id="cb15-7"><a href="#cb15-7" aria-hidden="true" tabindex="-1"></a> <span class="fu">mutate</span>(freq_casa_realização <span class="ot">=</span> n<span class="sc">*</span><span class="dv">100</span><span class="sc">/</span><span class="fu">sum</span>(n)) <span class="sc">%>%</span> </span>
<span id="cb15-8"><a href="#cb15-8" aria-hidden="true" tabindex="-1"></a> <span class="fu">ggplot</span>(<span class="fu">aes</span>(<span class="at">x =</span> sexo, <span class="at">y =</span> freq_casa_realização, <span class="at">fill =</span> sexo)) <span class="sc">+</span></span>
<span id="cb15-9"><a href="#cb15-9" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_bar</span>(<span class="at">stat =</span> <span class="st">"identity"</span>, <span class="at">show.legend =</span> <span class="cn">TRUE</span>) <span class="sc">+</span></span>
<span id="cb15-10"><a href="#cb15-10" aria-hidden="true" tabindex="-1"></a> <span class="fu">facet_grid</span>(casa_realização <span class="sc">~</span>., <span class="at">labeller =</span> <span class="fu">as_labeller</span>(opiniao_labeller, <span class="fu">label_wrap_gen</span>(<span class="at">width =</span> <span class="dv">15</span>, )))<span class="sc">+</span></span>
<span id="cb15-11"><a href="#cb15-11" aria-hidden="true" tabindex="-1"></a> <span class="fu">coord_flip</span>() <span class="sc">+</span></span>
<span id="cb15-12"><a href="#cb15-12" aria-hidden="true" tabindex="-1"></a> <span class="fu">ylim</span>(<span class="fu">c</span>(<span class="dv">0</span>, <span class="dv">90</span>)) <span class="sc">+</span></span>
<span id="cb15-13"><a href="#cb15-13" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_text</span>(<span class="fu">aes</span>(<span class="at">label =</span> <span class="fu">round</span>(freq_casa_realização, <span class="dv">2</span>)), <span class="at">hjust =</span> <span class="dv">1</span>) <span class="sc">+</span></span>
<span id="cb15-14"><a href="#cb15-14" aria-hidden="true" tabindex="-1"></a> <span class="fu">scale_fill_manual</span>(<span class="at">label =</span> <span class="fu">c</span>(<span class="st">"Masculino"</span>, <span class="st">"Feminino"</span>), <span class="at">values =</span> <span class="fu">c</span>(<span class="st">"lightblue3"</span>, <span class="st">"hotpink1"</span>)) <span class="sc">+</span></span>
<span id="cb15-15"><a href="#cb15-15" aria-hidden="true" tabindex="-1"></a> <span class="fu">theme</span>(<span class="at">strip.text =</span> <span class="fu">element_text</span>(<span class="at">size =</span> <span class="dv">12</span>)) <span class="sc">+</span></span>
<span id="cb15-16"><a href="#cb15-16" aria-hidden="true" tabindex="-1"></a> <span class="fu">labs</span>(<span class="at">title =</span> <span class="st">"Ser dona de casa é tão gratificante quanto ter um emprego"</span>,</span>
<span id="cb15-17"><a href="#cb15-17" aria-hidden="true" tabindex="-1"></a> <span class="at">caption =</span> <span class="st">"Fonte: ISSP, 2002."</span>)<span class="sc">+</span></span>
<span id="cb15-18"><a href="#cb15-18" aria-hidden="true" tabindex="-1"></a> <span class="fu">theme_minimal</span>() <span class="sc">+</span></span>
<span id="cb15-19"><a href="#cb15-19" aria-hidden="true" tabindex="-1"></a> <span class="fu">theme</span>(<span class="at">axis.title.y =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb15-20"><a href="#cb15-20" aria-hidden="true" tabindex="-1"></a> <span class="at">axis.ticks.y =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb15-21"><a href="#cb15-21" aria-hidden="true" tabindex="-1"></a> <span class="at">axis.text.y =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb15-22"><a href="#cb15-22" aria-hidden="true" tabindex="-1"></a> <span class="at">axis.title.x =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb15-23"><a href="#cb15-23" aria-hidden="true" tabindex="-1"></a> <span class="at">strip.text.y =</span> <span class="fu">element_text</span>(<span class="at">angle =</span> <span class="dv">0</span>),</span>
<span id="cb15-24"><a href="#cb15-24" aria-hidden="true" tabindex="-1"></a> <span class="at">plot.title =</span> <span class="fu">element_text</span>(<span class="at">hjust =</span> <span class="fl">0.5</span>),</span>
<span id="cb15-25"><a href="#cb15-25" aria-hidden="true" tabindex="-1"></a> <span class="at">plot.subtitle =</span> <span class="fu">element_text</span>(<span class="at">hjust =</span> <span class="dv">1</span>),</span>
<span id="cb15-26"><a href="#cb15-26" aria-hidden="true" tabindex="-1"></a> <span class="at">plot.caption =</span> <span class="fu">element_text</span>(<span class="at">hjust =</span> <span class="fl">0.5</span>))</span></code></pre></div>
<pre><code>## `summarise()` has grouped output by 'sexo'. You can override using the `.groups` argument.</code></pre>
<div class="sourceCode" id="cb17"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb17-1"><a href="#cb17-1" aria-hidden="true" tabindex="-1"></a><span class="fu">print</span>(casa_realização_sexo)</span></code></pre></div>
<p><img 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" /><!-- --></p>
<div class="sourceCode" id="cb18"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb18-1"><a href="#cb18-1" aria-hidden="true" tabindex="-1"></a><span class="co"># Distribuição relativa de brasileiros casados de acordo com o grau de concordância com a frase "O dever do homem é ganhar dinheiro, o dever da mulher é cuidar da casa e da família" por sexo</span></span>
<span id="cb18-2"><a href="#cb18-2" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb18-3"><a href="#cb18-3" aria-hidden="true" tabindex="-1"></a>dever_sexo <span class="ot"><-</span> brasil_casados_vs <span class="sc">%>%</span> </span>
<span id="cb18-4"><a href="#cb18-4" aria-hidden="true" tabindex="-1"></a> <span class="fu">filter</span>(<span class="sc">!</span><span class="fu">is.na</span>(trab_homem_mulher)) <span class="sc">%>%</span> </span>
<span id="cb18-5"><a href="#cb18-5" aria-hidden="true" tabindex="-1"></a> <span class="fu">group_by</span>(sexo, trab_homem_mulher) <span class="sc">%>%</span> </span>
<span id="cb18-6"><a href="#cb18-6" aria-hidden="true" tabindex="-1"></a> <span class="fu">summarise</span>(<span class="at">n =</span> <span class="fu">n</span>()) <span class="sc">%>%</span> </span>
<span id="cb18-7"><a href="#cb18-7" aria-hidden="true" tabindex="-1"></a> <span class="fu">mutate</span>(<span class="at">freq_dever =</span> n<span class="sc">*</span><span class="dv">100</span><span class="sc">/</span><span class="fu">sum</span>(n)) <span class="sc">%>%</span> </span>
<span id="cb18-8"><a href="#cb18-8" aria-hidden="true" tabindex="-1"></a> <span class="fu">ggplot</span>(<span class="fu">aes</span>(<span class="at">x =</span> sexo, <span class="at">y =</span> freq_dever, <span class="at">fill =</span> sexo)) <span class="sc">+</span></span>
<span id="cb18-9"><a href="#cb18-9" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_bar</span>(<span class="at">stat =</span> <span class="st">"identity"</span>, <span class="at">show.legend =</span> <span class="cn">TRUE</span>) <span class="sc">+</span></span>
<span id="cb18-10"><a href="#cb18-10" aria-hidden="true" tabindex="-1"></a> <span class="fu">facet_grid</span>(trab_homem_mulher <span class="sc">~</span>., <span class="at">labeller =</span> <span class="fu">as_labeller</span>(opiniao_labeller, <span class="fu">label_wrap_gen</span>(<span class="at">width =</span> <span class="dv">15</span>, )))<span class="sc">+</span></span>
<span id="cb18-11"><a href="#cb18-11" aria-hidden="true" tabindex="-1"></a> <span class="fu">coord_flip</span>() <span class="sc">+</span></span>
<span id="cb18-12"><a href="#cb18-12" aria-hidden="true" tabindex="-1"></a> <span class="fu">ylim</span>(<span class="fu">c</span>(<span class="dv">0</span>, <span class="dv">90</span>)) <span class="sc">+</span></span>
<span id="cb18-13"><a href="#cb18-13" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_text</span>(<span class="fu">aes</span>(<span class="at">label =</span> <span class="fu">round</span>(freq_dever, <span class="dv">2</span>)), <span class="at">hjust =</span> <span class="sc">-</span>.<span class="dv">1</span>) <span class="sc">+</span></span>
<span id="cb18-14"><a href="#cb18-14" aria-hidden="true" tabindex="-1"></a> <span class="fu">scale_fill_manual</span>(<span class="at">label =</span> <span class="fu">c</span>(<span class="st">"Masculino"</span>, <span class="st">"Feminino"</span>), <span class="at">values =</span> <span class="fu">c</span>(<span class="st">"lightblue3"</span>, <span class="st">"hotpink1"</span>)) <span class="sc">+</span></span>
<span id="cb18-15"><a href="#cb18-15" aria-hidden="true" tabindex="-1"></a> <span class="fu">theme</span>(<span class="at">strip.text =</span> <span class="fu">element_text</span>(<span class="at">size =</span> <span class="dv">12</span>)) <span class="sc">+</span></span>
<span id="cb18-16"><a href="#cb18-16" aria-hidden="true" tabindex="-1"></a> <span class="fu">labs</span>(<span class="at">title =</span> <span class="st">"</span><span class="sc">\"</span><span class="st">O dever do homem é prover e o da mulher é cuidar"</span>,</span>
<span id="cb18-17"><a href="#cb18-17" aria-hidden="true" tabindex="-1"></a> <span class="at">fill =</span> <span class="st">"Sexo"</span>,</span>
<span id="cb18-18"><a href="#cb18-18" aria-hidden="true" tabindex="-1"></a> <span class="at">caption =</span> <span class="st">"Fonte: ISSP, 2002."</span>)<span class="sc">+</span></span>
<span id="cb18-19"><a href="#cb18-19" aria-hidden="true" tabindex="-1"></a> <span class="fu">theme_minimal</span>() <span class="sc">+</span></span>
<span id="cb18-20"><a href="#cb18-20" aria-hidden="true" tabindex="-1"></a> <span class="fu">theme</span>(<span class="at">axis.title.y =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb18-21"><a href="#cb18-21" aria-hidden="true" tabindex="-1"></a> <span class="at">axis.ticks.y =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb18-22"><a href="#cb18-22" aria-hidden="true" tabindex="-1"></a> <span class="at">axis.text.y =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb18-23"><a href="#cb18-23" aria-hidden="true" tabindex="-1"></a> <span class="at">axis.title.x =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb18-24"><a href="#cb18-24" aria-hidden="true" tabindex="-1"></a> <span class="at">strip.text.y =</span> <span class="fu">element_text</span>(<span class="at">angle =</span> <span class="dv">0</span>),</span>
<span id="cb18-25"><a href="#cb18-25" aria-hidden="true" tabindex="-1"></a> <span class="at">plot.title =</span> <span class="fu">element_text</span>(<span class="at">hjust =</span> <span class="fl">0.5</span>, <span class="at">size =</span> <span class="dv">12</span>, <span class="at">face =</span> <span class="st">"bold"</span>, ),</span>
<span id="cb18-26"><a href="#cb18-26" aria-hidden="true" tabindex="-1"></a> <span class="at">plot.subtitle =</span> <span class="fu">element_text</span>(<span class="at">hjust =</span> <span class="dv">1</span>, <span class="at">size =</span> <span class="dv">8</span>),</span>
<span id="cb18-27"><a href="#cb18-27" aria-hidden="true" tabindex="-1"></a> <span class="at">plot.caption =</span> <span class="fu">element_text</span>(<span class="at">hjust =</span> <span class="fl">0.5</span>))</span></code></pre></div>
<pre><code>## `summarise()` has grouped output by 'sexo'. You can override using the `.groups` argument.</code></pre>
<div class="sourceCode" id="cb20"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb20-1"><a href="#cb20-1" aria-hidden="true" tabindex="-1"></a><span class="fu">print</span>(dever_sexo)</span></code></pre></div>
<p><img 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" /><!-- --></p>
<div class="sourceCode" id="cb21"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb21-1"><a href="#cb21-1" aria-hidden="true" tabindex="-1"></a><span class="co"># Distribuição relativa de brasileiros casados de acordo com o grau de concordância com a frase "Homens devem participar mais das tarefas domésticas do que participam atualmente" por sexo</span></span>
<span id="cb21-2"><a href="#cb21-2" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb21-3"><a href="#cb21-3" aria-hidden="true" tabindex="-1"></a>homem_dom_sexo <span class="ot"><-</span> brasil_casados_vs <span class="sc">%>%</span> </span>
<span id="cb21-4"><a href="#cb21-4" aria-hidden="true" tabindex="-1"></a> <span class="fu">filter</span>(<span class="sc">!</span><span class="fu">is.na</span>(homem_domésticas)) <span class="sc">%>%</span> </span>
<span id="cb21-5"><a href="#cb21-5" aria-hidden="true" tabindex="-1"></a> <span class="fu">group_by</span>(sexo, homem_domésticas) <span class="sc">%>%</span> </span>
<span id="cb21-6"><a href="#cb21-6" aria-hidden="true" tabindex="-1"></a> <span class="fu">summarise</span>(<span class="at">n =</span> <span class="fu">n</span>()) <span class="sc">%>%</span> </span>
<span id="cb21-7"><a href="#cb21-7" aria-hidden="true" tabindex="-1"></a> <span class="fu">mutate</span>(<span class="at">freq_homem_dom =</span> n<span class="sc">*</span><span class="dv">100</span><span class="sc">/</span><span class="fu">sum</span>(n)) <span class="sc">%>%</span> </span>
<span id="cb21-8"><a href="#cb21-8" aria-hidden="true" tabindex="-1"></a> <span class="fu">ggplot</span>(<span class="fu">aes</span>(<span class="at">x =</span> sexo, <span class="at">y =</span> freq_homem_dom, <span class="at">fill =</span> sexo)) <span class="sc">+</span></span>
<span id="cb21-9"><a href="#cb21-9" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_bar</span>(<span class="at">stat =</span> <span class="st">"identity"</span>, <span class="at">show.legend =</span> <span class="cn">TRUE</span>) <span class="sc">+</span></span>
<span id="cb21-10"><a href="#cb21-10" aria-hidden="true" tabindex="-1"></a> <span class="fu">facet_grid</span>(homem_domésticas <span class="sc">~</span>., <span class="at">labeller =</span> <span class="fu">as_labeller</span>(opiniao_labeller, <span class="fu">label_wrap_gen</span>(<span class="at">width =</span> <span class="dv">12</span>)))<span class="sc">+</span></span>
<span id="cb21-11"><a href="#cb21-11" aria-hidden="true" tabindex="-1"></a> <span class="fu">coord_flip</span>() <span class="sc">+</span></span>
<span id="cb21-12"><a href="#cb21-12" aria-hidden="true" tabindex="-1"></a> <span class="fu">ylim</span>(<span class="fu">c</span>(<span class="dv">0</span>, <span class="dv">90</span>)) <span class="sc">+</span></span>
<span id="cb21-13"><a href="#cb21-13" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_text</span>(<span class="fu">aes</span>(<span class="at">label =</span> <span class="fu">round</span>(freq_homem_dom, <span class="dv">2</span>)), <span class="at">hjust =</span> <span class="sc">-</span>.<span class="dv">1</span>, <span class="at">size =</span> <span class="fl">3.5</span>) <span class="sc">+</span></span>
<span id="cb21-14"><a href="#cb21-14" aria-hidden="true" tabindex="-1"></a> <span class="fu">scale_fill_manual</span>(<span class="at">label =</span> <span class="fu">c</span>(<span class="st">"Masculino"</span>, <span class="st">"Feminino"</span>), <span class="at">values =</span> <span class="fu">c</span>(<span class="st">"lightblue3"</span>, <span class="st">"hotpink1"</span>)) <span class="sc">+</span></span>
<span id="cb21-15"><a href="#cb21-15" aria-hidden="true" tabindex="-1"></a> <span class="fu">labs</span>(<span class="at">title =</span> <span class="st">"</span><span class="sc">\"</span><span class="st">Homens deveriam fazer mais tarefas domésticas</span><span class="sc">\"</span><span class="st">?"</span>,</span>
<span id="cb21-16"><a href="#cb21-16" aria-hidden="true" tabindex="-1"></a> <span class="at">fill =</span> <span class="st">"Sexo"</span>,</span>
<span id="cb21-17"><a href="#cb21-17" aria-hidden="true" tabindex="-1"></a> <span class="at">caption =</span> <span class="st">"Fonte: ISSP, 2002."</span>)<span class="sc">+</span></span>
<span id="cb21-18"><a href="#cb21-18" aria-hidden="true" tabindex="-1"></a> <span class="fu">theme_minimal</span>() <span class="sc">+</span></span>
<span id="cb21-19"><a href="#cb21-19" aria-hidden="true" tabindex="-1"></a> <span class="fu">theme</span>(<span class="at">axis.title.y =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb21-20"><a href="#cb21-20" aria-hidden="true" tabindex="-1"></a> <span class="at">axis.ticks.y =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb21-21"><a href="#cb21-21" aria-hidden="true" tabindex="-1"></a> <span class="at">axis.text.y =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb21-22"><a href="#cb21-22" aria-hidden="true" tabindex="-1"></a> <span class="at">axis.title.x =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb21-23"><a href="#cb21-23" aria-hidden="true" tabindex="-1"></a> <span class="at">strip.text.y =</span> <span class="fu">element_text</span>(<span class="at">angle =</span> <span class="dv">0</span>, <span class="at">size =</span> <span class="dv">10</span>),</span>
<span id="cb21-24"><a href="#cb21-24" aria-hidden="true" tabindex="-1"></a> <span class="at">plot.title =</span> <span class="fu">element_text</span>(<span class="at">hjust =</span> <span class="fl">0.5</span>, <span class="at">size =</span> <span class="dv">12</span>, <span class="at">face =</span> <span class="st">"bold"</span>),</span>
<span id="cb21-25"><a href="#cb21-25" aria-hidden="true" tabindex="-1"></a> <span class="at">plot.subtitle =</span> <span class="fu">element_text</span>(<span class="at">hjust =</span> <span class="dv">1</span>, <span class="at">size =</span> <span class="dv">8</span>),</span>
<span id="cb21-26"><a href="#cb21-26" aria-hidden="true" tabindex="-1"></a> <span class="at">plot.caption =</span> <span class="fu">element_text</span>(<span class="at">hjust =</span> <span class="fl">0.5</span>))</span></code></pre></div>
<pre><code>## `summarise()` has grouped output by 'sexo'. You can override using the `.groups` argument.</code></pre>
<div class="sourceCode" id="cb23"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb23-1"><a href="#cb23-1" aria-hidden="true" tabindex="-1"></a><span class="fu">print</span>(homem_dom_sexo)</span></code></pre></div>
<p><img 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" /><!-- --></p>
<div class="sourceCode" id="cb24"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb24-1"><a href="#cb24-1" aria-hidden="true" tabindex="-1"></a><span class="co"># Distribuição relativa de brasileiros casados de acordo com a grau de concordância com a frase "Homens deveriam participar mais do cuidado com as crianças" por sexo</span></span>
<span id="cb24-2"><a href="#cb24-2" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb24-3"><a href="#cb24-3" aria-hidden="true" tabindex="-1"></a>homem_cuidado_sexo <span class="ot"><-</span> brasil_casados_vs <span class="sc">%>%</span> </span>
<span id="cb24-4"><a href="#cb24-4" aria-hidden="true" tabindex="-1"></a> <span class="fu">filter</span>(<span class="sc">!</span><span class="fu">is.na</span>(homem_cuidado)) <span class="sc">%>%</span> </span>
<span id="cb24-5"><a href="#cb24-5" aria-hidden="true" tabindex="-1"></a> <span class="fu">group_by</span>(sexo, homem_cuidado) <span class="sc">%>%</span> </span>
<span id="cb24-6"><a href="#cb24-6" aria-hidden="true" tabindex="-1"></a> <span class="fu">summarise</span>(<span class="at">n =</span> <span class="fu">n</span>()) <span class="sc">%>%</span> </span>
<span id="cb24-7"><a href="#cb24-7" aria-hidden="true" tabindex="-1"></a> <span class="fu">mutate</span>(<span class="at">freq_homem_cuidado =</span> n<span class="sc">*</span><span class="dv">100</span><span class="sc">/</span><span class="fu">sum</span>(n)) <span class="sc">%>%</span> </span>
<span id="cb24-8"><a href="#cb24-8" aria-hidden="true" tabindex="-1"></a> <span class="fu">ggplot</span>(<span class="fu">aes</span>(<span class="at">x =</span> sexo, <span class="at">y =</span> freq_homem_cuidado, <span class="at">fill =</span> sexo)) <span class="sc">+</span></span>
<span id="cb24-9"><a href="#cb24-9" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_bar</span>(<span class="at">stat =</span> <span class="st">"identity"</span>, <span class="at">show.legend =</span> <span class="cn">TRUE</span>) <span class="sc">+</span></span>
<span id="cb24-10"><a href="#cb24-10" aria-hidden="true" tabindex="-1"></a> <span class="fu">facet_grid</span>(homem_cuidado <span class="sc">~</span>., <span class="at">labeller =</span> <span class="fu">as_labeller</span>(opiniao_labeller, <span class="fu">label_wrap_gen</span>(<span class="at">width =</span> <span class="dv">15</span>, )))<span class="sc">+</span></span>
<span id="cb24-11"><a href="#cb24-11" aria-hidden="true" tabindex="-1"></a> <span class="fu">coord_flip</span>() <span class="sc">+</span></span>
<span id="cb24-12"><a href="#cb24-12" aria-hidden="true" tabindex="-1"></a> <span class="fu">ylim</span>(<span class="fu">c</span>(<span class="dv">0</span>, <span class="dv">90</span>)) <span class="sc">+</span></span>
<span id="cb24-13"><a href="#cb24-13" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_text</span>(<span class="fu">aes</span>(<span class="at">label =</span> <span class="fu">round</span>(freq_homem_cuidado, <span class="dv">2</span>)), <span class="at">hjust =</span> <span class="sc">-</span>.<span class="dv">1</span>) <span class="sc">+</span></span>
<span id="cb24-14"><a href="#cb24-14" aria-hidden="true" tabindex="-1"></a> <span class="fu">scale_fill_manual</span>(<span class="at">label =</span> <span class="fu">c</span>(<span class="st">"Masculino"</span>, <span class="st">"Feminino"</span>), <span class="at">values =</span> <span class="fu">c</span>(<span class="st">"lightblue3"</span>, <span class="st">"hotpink1"</span>)) <span class="sc">+</span></span>
<span id="cb24-15"><a href="#cb24-15" aria-hidden="true" tabindex="-1"></a> <span class="fu">theme</span>(<span class="at">strip.text =</span> <span class="fu">element_text</span>(<span class="at">size =</span> <span class="dv">12</span>)) <span class="sc">+</span></span>
<span id="cb24-16"><a href="#cb24-16" aria-hidden="true" tabindex="-1"></a> <span class="fu">labs</span>(<span class="at">title =</span> <span class="st">"Homens deveriam cuidar mais de seus filhos"</span>,</span>
<span id="cb24-17"><a href="#cb24-17" aria-hidden="true" tabindex="-1"></a> <span class="at">caption =</span> <span class="st">"Fonte: ISSP, 2002."</span>)<span class="sc">+</span></span>
<span id="cb24-18"><a href="#cb24-18" aria-hidden="true" tabindex="-1"></a> <span class="fu">theme</span>(<span class="at">plot.background =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb24-19"><a href="#cb24-19" aria-hidden="true" tabindex="-1"></a> <span class="at">axis.title.y =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb24-20"><a href="#cb24-20" aria-hidden="true" tabindex="-1"></a> <span class="at">axis.ticks.y =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb24-21"><a href="#cb24-21" aria-hidden="true" tabindex="-1"></a> <span class="at">axis.text.y =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb24-22"><a href="#cb24-22" aria-hidden="true" tabindex="-1"></a> <span class="at">axis.title.x =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb24-23"><a href="#cb24-23" aria-hidden="true" tabindex="-1"></a> <span class="at">strip.text.y =</span> <span class="fu">element_text</span>(<span class="at">angle =</span> <span class="dv">0</span>),</span>
<span id="cb24-24"><a href="#cb24-24" aria-hidden="true" tabindex="-1"></a> <span class="at">plot.title =</span> <span class="fu">element_text</span>(<span class="at">hjust =</span> <span class="fl">0.5</span>),</span>
<span id="cb24-25"><a href="#cb24-25" aria-hidden="true" tabindex="-1"></a> <span class="at">plot.subtitle =</span> <span class="fu">element_text</span>(<span class="at">hjust =</span> <span class="dv">1</span>),</span>
<span id="cb24-26"><a href="#cb24-26" aria-hidden="true" tabindex="-1"></a> <span class="at">plot.caption =</span> <span class="fu">element_text</span>(<span class="at">hjust =</span> <span class="fl">0.5</span>))</span></code></pre></div>
<pre><code>## `summarise()` has grouped output by 'sexo'. You can override using the `.groups` argument.</code></pre>
<div class="sourceCode" id="cb26"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb26-1"><a href="#cb26-1" aria-hidden="true" tabindex="-1"></a><span class="fu">print</span>(homem_cuidado_sexo)</span></code></pre></div>
<p><img 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" /><!-- --></p>
</div>
<div id="horas-de-trabalho-fora-e-dentro-do-domicílio" class="section level4">
<h4>Horas de trabalho fora e dentro do domicílio</h4>
<div class="sourceCode" id="cb27"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb27-1"><a href="#cb27-1" aria-hidden="true" tabindex="-1"></a><span class="co"># Distribuição de brasileiros casados por horas semanais de trabalho remunerado, de acordo com seu sexo</span></span>
<span id="cb27-2"><a href="#cb27-2" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb27-3"><a href="#cb27-3" aria-hidden="true" tabindex="-1"></a>horas_trab_sexo <span class="ot"><-</span> brasil_casados_vs <span class="sc">%>%</span> </span>
<span id="cb27-4"><a href="#cb27-4" aria-hidden="true" tabindex="-1"></a> <span class="fu">filter</span>(<span class="sc">!</span><span class="fu">is.na</span>(horas_trab)) <span class="sc">%>%</span> </span>
<span id="cb27-5"><a href="#cb27-5" aria-hidden="true" tabindex="-1"></a> <span class="fu">group_by</span>(sexo) <span class="sc">%>%</span> </span>
<span id="cb27-6"><a href="#cb27-6" aria-hidden="true" tabindex="-1"></a> <span class="fu">ggplot</span>() <span class="sc">+</span></span>
<span id="cb27-7"><a href="#cb27-7" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_boxplot</span>(<span class="fu">aes</span>(<span class="at">x =</span> sexo, <span class="at">y =</span> horas_trab, <span class="at">fill =</span> sexo)) <span class="sc">+</span></span>
<span id="cb27-8"><a href="#cb27-8" aria-hidden="true" tabindex="-1"></a> <span class="fu">scale_y_continuous</span>(<span class="at">breaks =</span> <span class="fu">c</span>(<span class="dv">0</span>, <span class="dv">10</span>, <span class="dv">20</span>, <span class="dv">30</span>, <span class="dv">40</span>, <span class="dv">50</span>, <span class="dv">60</span>, <span class="dv">70</span>, <span class="dv">80</span>, <span class="dv">90</span>, <span class="dv">100</span>)) <span class="sc">+</span></span>
<span id="cb27-9"><a href="#cb27-9" aria-hidden="true" tabindex="-1"></a> <span class="fu">scale_fill_manual</span>(<span class="at">labels =</span> <span class="fu">c</span>(<span class="st">"Masculino"</span>, <span class="st">"Femino"</span>),</span>
<span id="cb27-10"><a href="#cb27-10" aria-hidden="true" tabindex="-1"></a> <span class="at">values =</span> <span class="fu">c</span>(<span class="st">"lightblue3"</span>, <span class="st">"hotpink1"</span>)) <span class="sc">+</span></span>
<span id="cb27-11"><a href="#cb27-11" aria-hidden="true" tabindex="-1"></a> <span class="fu">labs</span>(<span class="at">y =</span> <span class="st">"Horas trabalhadas"</span>, <span class="at">fill =</span> <span class="st">"Sexo"</span>,</span>
<span id="cb27-12"><a href="#cb27-12" aria-hidden="true" tabindex="-1"></a> <span class="at">title =</span> <span class="st">"Horas trabalhadas por sexo"</span>,</span>
<span id="cb27-13"><a href="#cb27-13" aria-hidden="true" tabindex="-1"></a> <span class="at">caption =</span> <span class="st">"Fonte: ISSP, 2002."</span>)<span class="sc">+</span></span>
<span id="cb27-14"><a href="#cb27-14" aria-hidden="true" tabindex="-1"></a> <span class="fu">theme</span>(<span class="at">plot.background =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb27-15"><a href="#cb27-15" aria-hidden="true" tabindex="-1"></a> <span class="at">axis.title.x =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb27-16"><a href="#cb27-16" aria-hidden="true" tabindex="-1"></a> <span class="at">axis.ticks.x =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb27-17"><a href="#cb27-17" aria-hidden="true" tabindex="-1"></a> <span class="at">axis.text.x =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb27-18"><a href="#cb27-18" aria-hidden="true" tabindex="-1"></a> <span class="at">plot.title =</span> <span class="fu">element_text</span>(<span class="at">hjust =</span> <span class="fl">0.5</span>),</span>
<span id="cb27-19"><a href="#cb27-19" aria-hidden="true" tabindex="-1"></a> <span class="at">plot.caption =</span> <span class="fu">element_text</span>(<span class="at">hjust =</span> <span class="fl">0.5</span>))</span>
<span id="cb27-20"><a href="#cb27-20" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb27-21"><a href="#cb27-21" aria-hidden="true" tabindex="-1"></a><span class="fu">print</span>(horas_trab_sexo)</span></code></pre></div>
<p><img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAqAAAAHgCAMAAABNUi8GAAABTVBMVEUAAAAAACsAAFUAKysAK1UAK4AAVaorAAArACsrAFUrKwArK1UrK4ArVVUrVYArVaorgIArgKorgNQzMzNNTU1NTWtNTYhNa6ZNiMRVAABVACtVAFVVKwBVKytVK1VVVStVVVVVVapVgIBVgNRVqtRVqv9rTU1rTWtrTYhra4hra6ZrpsRrpuGAKwCAKyuAK1WAVQCAVSuAVVWAVYCAgFWAgKqAqoCAqtSA1P+ITU2ITWuITYiIa02Ia6aIxP+awM2ma02ma2uma4imiE2mxKam4eGm4f+qVQCqVSuqVVWqgCuqqlWqqoCqqtSq1ICq1NSq1P+q/6qq/9Sq///EiE3E///UgCvUgFXUqlXUqoDU1IDU1KrU1NTU/6rU/9TU///hpmvh///r6+vy8vL/brT/qlX/xIj/1ID/1Kr/4ab//6r//8T//9T//+H///96+qZXAAAACXBIWXMAAA7DAAAOwwHHb6hkAAAZ9ElEQVR4nO2d/3/bxnnHKceW7C1tNol2qtpbty5Kts7Ksq1tlH1Rk621tmxr3cpm222ZnGW0KprG///j7gDwC0gQdw/4PLgPqM/7ZRsSBFL3Ad4+3B0B3CAjBJhB6gIQ0gQFJdBQUAINBSXQUFACDQUl0FBQAg0FJdD0XtDRnct8OTk+jH/R9R9frq2bHO+vrZue3rvyf+vfZXq6/gqizO0UdPaiZSgoJBR0BgWFZMcE/d2TweDu89yd0eDO8+w3vzcY7P2Z+8H0r90XHxQvmZ4OBoPD1U2coOOD/MXZfF0p6FdPijdZvF32G7fpL3JBa3+FL45/t7OsplBZZWP/0993K0cDF2Ds/5ltT7JdE9Q54dg7cy68czC4dzUa5JwUTvovPDNBq5tMjt85KF6cLb3MC3r3Sfna+friq7tP9ivbLv0K927fmr3baqHmRcg3vl789M7l5NilmW9Psl0QdDDj0B/2D/wab5Wvitwxf+4V2Hd/37vKvyhf5DxY3WRyPPjDq+mXg/2ldYWgXqpfV9ZPjvc+zX53WllX/RXu3fZn71YtVM584+mpr0d/6182HrgK9mRp+xS7E46dErTU42LvzFdH+Y//+9//5mDg7Xnn+79YelEuaHWTybFXolxbrisE9WvKFur87bxp5a+r/RXFu2UXdy5rCpUtNi7eqTgPXAzc2yyFMNpj/aL/gi6d4q8P8hPs2LuQ+1GcP/1hv/DLbz9fetHqJmUva+TEmK9bdJLyDtF8/Tg/k1fXVX9FKbR7t7VC5cw2Hpf/u7yO1wfFv7PtO9h7+Oy0oO48+60f/cdXuSu/9Q3JWQ22EHSxyULQxbqqoIv1C0E3/YqQoLONlwUdl41SCrrEjgm6OJt6F4pjPW8X/tcnsy7MQtDFJoVS/jS8WFcVdLG+ODH7V2z6FYsGw2qhFviNSx2Ll9x94srFU3yFnRJ0uT9S2Ld/5Qdt7l2NXQcom345O+ijvNdc3cTVhe4dvsxbk7N1q4IutnVdm+lpZdvqr1juclULlTPf2HWSPs1cf8ulcIUaV3p6CfYmHjsl6PKITmFVcf7MO9DFF+WL8mGm6iblwFDRv5+/bFnQxfqi6eiHmTb9inLQyhdupVA5i43Hyz28vBvFYaZldkvQ7Ho+Jp67kA95f3rhpfMD4+/N/Jg8Gez/z8omxdD6u8+X1610khZv55uQd39VXVf5FcWwf9FlWilUzmJj/9N3PijP6fn5/ZoD9Qt6LygodR+ckhZQUBsoqBIU1AYKqgQFtYGCKkFBCTQUlEBDQQk0FJRAQ0EJNBSUQNMo6M2fv8yyN58N3/96vij4XwxQymEGSkB7DzfSJOjr4aOX2dvPz7NX35ktSlLvsBKUcpiBErADETfRIOiLhz91Neibv3/pa9JyUf4o9Q4rQSmHGSgBO1GxnuAp/uYHX2dv/u5ZuXArjxwdFY6QoKCv38/NLBflD1L/jy5BKYcZKAE7EHET8hrUk3qHlaCUwwyUgB2IuImgoGyDJgQlYAcibiIo6NvPnxa9+KfsxXcOSkB7DzfCcVBkUALae7iRdp8kpd5hJSjlMAMloLJ0EigoMigBlaWTQEGRQQmoLJ0ECooMSkBl6SRQUGRQAipLJ4GCIoMSUFk6CRQUGZSAytJJoKDIoARUlk5CnwU9OjpKXQRbYAIqSyehx4L66/5ADqANOAGVpZNAQXHBCagsnQQKigtOQGXpJPRYUJwmmhUwAZWlk9BnQWE6uWagBFSWTgLviyfQsAZFBiWgsnQSKCgyKAGVpZNAQZFBCagsnQQKigxKQGXpJFBQZFACKksngYIigxJQWToJFBQZlIDK0kmgoMigBFSWTgIFRQYloLJ0EigoMigBlaWTQEGRQQmoLJ0ECooMSkBl6SRQUGRQAipLJ4GCIoMSUFk6CRQUGZSAytJJoKDIoARUlk5CWNCbD/1sNHw+aApQApoq2ExQ0DefnWev3v8acZ4kmFt2rIAJaOtgI0FBy9kTAJ9Rj3PToxE4AY0lbCJWUMB5ko5gSmLEzgeMIe4U/xBxniScCsYInIDGEjYR1Un6yy8g50lCOXxmwAS0dbCRqGEm1wAFbIPidHLNQAloKGCI8CneVZucJykRKAFtHWwkXIO+HnKepFSgBDRVsBl+koQMSkBl6SRQUGRQAipLJ4GCIoMSUFk6CRQUGZSAytJJoKDIoARUlk4CBUUGJaCydBIoKDIoAZWlk0BBkUEJqCydhD4LCvNRtRkgO5qCtgLnYh8zMHY0BW0HBe0MZekkUFBkMHY0BW3JzvtJQfstKMzxMwMloLJ0EjhPEoGGNSgyKAGVpZPQZ0HZBu0KZekk9FhQ9uI7Q1k6CRQUGYwdTUHbQUE7Q1k6CT0WlG3QzlCWTkKfBYU5fmagBFSWTgIFRQYloLJ0EigoMigBlaWTQEGRQQmoLJ0ECooMSkBl6SRQUGRQAipLJ4GCIoMSUFk6CRQUGZSAytJJoKDIoARUlk4CBUUGJaCydBI4TxIyKAFNFWwm7gnLnCcpCTABbR1sJG4aGshn1O/81Uw4AY0lbCK2BuU8Sd2z8wFjCLdBi8Yn50nqHpyAtg42Ej7Ff/Qse/3oJedJSgBMQGMJmwgKWladbIOmAGNHYwta1qCA8yRR0M6wdbCRqHmSHj5DHAeloJ1hqmAzff4kaef9pKD9FhTm+JmBElBZOgkUFBmUgMrSSaCgyKAEVJZOQp8FZRu0K5Slk9BjQdmL7wxl6SRQUGQwdjQFbQcF7Qxl6ST0WFC2QTtDWToJfRYU5viZgRJQWToJFBQZlIDK0kmgoMigBFSWTgIFRQYloLJ0EigoMigBlaWTwHmSCDSsQZFBCagsnQQKigxKQGXpJFBQZFACKksngYIigxJQWToJFBQZlIDK0kmgoMigBFSWTgIFRQYloLJ0EigoMigBlaWTQEGRQQmoLJ2EPgu689eDwgRUlk5CjwXd+SvqcQIqSyeBguKCE1BZOgkUFBecgMrSSeixoDhNNCtgAipLJ6HPgsJ0cs1ACagsnQQKigxKQGXpJAQFfTX0nAM+HxTn+JmBEtDWwUaiatDXnCcpCTAB7fwLEiOonzyBz6jvHpyAlgYGiBHU15ycJ6l7dj5gDBGC5l5ynqTuwQloqmAzEYJ6NzPOk5QAmICmCjYTIeiLp+4fwDYoTifXDJSAlgYGCAv69gtfbwLOk4Rz/MxACWhpYICIuTqLEzvHQROAEtBQwBD8JAkZlIDK0kmgoMigBFSWTgIFRQYloLJ0EigoMigBlaWTQEGRQQmoLJ0ECooMSkBl6SRQUGRQAipLJ4GCIoMSUFk6CRQUGZSAytJJoKDIoARUlk4CBUUGJaCydBIoKDIoAZWlk0BBkUEJqCydBAqKDEpAZekk9HqepFt/w84toNc1KMgNEXag7Ghl6SRQUGRQdrSydBIoKDIoO1pZOgkUFBmUHa0snQQKigzKjlaWTgIFRQZlRytLJ6Ei6OT4ZHI8uHMZfFXqHVZCQTvCTL8wFUEv9rPRncvRfvBVqXdYyc4LihLQTL8wy4K6CnR6up+Nw1Vo6h1WgnL8zEAJaChgiBVBJ8eHFBQHlICGAoZYFnR6ejjeO/Mn+hCpd1gJyvEzAyWgnX9BKm3Q64PBfnZx7yr4qtQ7rATl+JmBEtBMvzAcZkIGJaCydBIoKDIoAZWlk7B6ivewk4QCSkA7/4KsdJKmp64jfxJ8VeodVoJy/MxACWjnX5CVYabs4jAbV3tJbz8fPnyG+XxQlONnBkrAznRcZ1XQ0dpA/Ytz1HmSYI6fGSgBO9NxndWPOp2do0oN6h9On4E+ox7l+JmBErArG2uoCOoaodnFYO9sed3ND/7Zn+IB50m6Bfck7XzAMMFhppsPz72dgPMk4VQwZqAENJawibCgRdWJOE8SzPEzAyWgsYRNzAWdHA9mVDpJb/4xN5Nt0BSgBOzWyQqVGnTk1VwdB32Rn+Ih50lCOX5moATsSMY6VoeZHCvDTG8+Gz56yXHQJKAE7EjGOsKC1pF6h5WgHD8zUAKa6Rem7hR/GHxV6h1WgnL8zEAJaKZfmGovfuz7SOGP4iloR6AENJIvBl5uhwxKQGXpJFBQZFACKksngdeDIoMS0M6/ILweFBmUgHb+BQlfD1pH6h1WgnL8zEAJaChgiPD1oHWk3mElKMfPDJSAhgKGCF4PWkvqHVaCcvzMQAm4yYOR67FUr85UJ3g9aC2pd1gJyvEzAyXgBg3yD3bGMQPn7eEwEzIoAestcD1qv4h50kd7KCgyKAHrLfAn3PmX+ejkyJ19/Ufl/tvwA5Si4DgoMigBN2gwHgwKRf1DETPfd3G9GPfHf5uvUqA6DqpkfVfs/C078AF9L2m/vADODwJd3//xg8vi24jBoBhqLreLIPX/6BKUCsYMlIBNLkyO712NilsxDr2xzqF8JP36vkr3vlqDUlAsUAI2yuBMXIxMXuQVqpGg8bVy6h1WgnL8zEAJWG9BqaBbjGdDk+M7v3Sn4fxb7VP8ppvmKGhCUAJu0ODCi1j0iFyd6bT0jUQnplUnKZ7UO6wE5fiZgRJwkwejsuWZjyv5h3M7Tws7bYaZokm9w0pQjp8ZKAF1XGsFT/HIoAS0dbAR1qDIoARUlk4CBUUGJaCydBL4UScyKAHt/AvCWz6QQQlo518Q3vKBDEpAQwFD8JYPZFACGgoYgrd8IIMSsN6Cb+rREXMGb/lABiVgvQXdCxpN6h1WgnL8zEAJWG/BkpRHCQV9NRz6B4Ty+aAJQAlYb0YCQeuebvfi3P/LeZJSgBIQRdC654O+/SKfOYHPqE8BSkAQQWufsOxO7cPh+fbzJB31hm12pzJIZVnHeblO54LefPTM16Jbz5N09JOegFJreVDKslHQ9b1neoof183y4XlxvvU8SRS0BShlaSPo9YG/ZPmi8VOf6weX7k+coI3Xg74437oNSkFbgFKWVoLe//ZVNvmjRv9CdmYRw0z+3P72n15uPU8SBW0BSllaCfrge2fZ9Z84Bf1Fcif5EFFxhh7snXkzi+rT/3n3k3wD95P1ujFqHFRjvngK2gKUsmwUtKGTdP3g306yX//4weXku2dexsnjS3+lh7+3fXzvPyuCHhRXKNVeqNTZ9aAUtAUoZdko6PreWxL05+9N/+rnxUnc2ek9zWZn9WoNWnzjDS432iCo6fWgFLQFKGVpJ+iv/varP819vMgrPVf97bm69N2rDYL6xfTjJkFNrweloC1AKUs7QS//5YeHvmb0z2wqKlKn1jY1qOn1oBS0BShlaSnoOO8N5f7dP/P1nvvr26DXD37pRBzdqQoa0Qa1vB6UgrYApSwtBS3lGw0Gd5+clCf6ohfv1/3B4xVBw714y+tBKWgLUMqyUdBuP+qMp0VGCtoClLLUW9D5xSKmj1+koC1AKUu9BamuZoqgRUYK2gKUstRbkOB60Nj5GlpkpKAtQClLvQUJalDDh4dR0BaglKXegm/qUTKzhJ2kVVCk8KCUpd6CzgWtvWC5lhYZKWgLUMpSbwEFTQKKFB6UstRb0HEbdDS/YNlktqT+CGqRviVIZVknQSeJw0ysQeuot6BzQeNpkZGCtgClLPUW7JigvUH98LYHpSz1FuzYZ/G9oeVBTF3seOTZ6i1wgv7fKj0WNPWpO5bWgq4dLFA6ErS4f+hw/WURt3IuQUFXoaDr1FsQEFTk4UYqgrpufO1Fo2u0OX6pxYuFgq5Tb0GcoIVR049/6KrTfIL50I3GDYJe7Pvr8EfhcdA2xy+1eLFQ0HU2CrrOmqAXh8Xdxvv5s0YibjTeLKirQP378JOkVtxKQdffvNoG3c9vg5s8vvS3a/q/7tvQbXKNgvpnL1LQVlDQ/M1Xa9D8Erm9s1pB62803izo9PTQz/R9wVN8Gyho/uZrgj7OFyo1qK+V9/MplSloi4AJXGtFx52kop1ZK6i0DRpPm+OXWrxYKOg62wha3GZcL6i0F09Bf0JB69goaEMvXgk+PGwVCrpOvQWdXyzCh4d5KOg69RYkuR60rtnqp6Dh80GDAVOLF0u/Ba17eNir4fn28yRRUBT6K+iGh4fd/MU/nG8/T9LuC9ob5NmCgn7TjaC1Dw97+8XPPuc8SQyYiIhn1D/1p/et50myAOWC85zbd4rvhODDw1zV+bZSg3r0D28rKGgb+ito7QCTn+x4OHzKuTpDUFATYh4e5mvQredJsoCCtqG/gm56eJjKOKgFFLQN/RU0Hv3D2woK2gYK2hkUtA19FnS04U7RVfQPbysoaBt6LOiomCYkbKj+4W0FBW1DfwU1ffyiBRS0DRS0MyhoG/orKE/x20BBTWAnSQsKagKHmbSgoCZQUC0oqAlzQWefc1rdNGcBBW1DTwXNiZ1qTv/wtoKCtoGCdgYFbQMF7QwK2obbICgIUHfX9EfQ1HtKBGtQLfojqDybhXmRUFAtKKgJFFQLCmoCx0G1oKAm8JMkLSioCRRUCwpqAgXVgoKaQEG1oKAmUFAtKKgJFFQLCmoCBdWCgppAQbWgoCZQUC0oqAkUVAsKagIF1YKCmkBBtaCgJoQFfT0cPnrJ54MGoaAmBAX1z/1+9Z3t50mygIK2YccE9ThJ+Yz6EBTUhChBXdW59TxJFqCUIyf17EfxpN5TIiIEvfnw4TPOk5QElICmCjYTVYM6MzlPUgpQAhoKGCJumOnFOdugKUAJaOdfkKCg5bmd8ySlACWgrYONRMzVORy6NijHQVOAEtBUwWb4SRIyKAGVpZNAQZFBCagsnQQKigxKQGXpJFBQZFACKksngYIigxJQWToJFBQZlIDK0kmgoMigBFSWTgIFRQYloLJ0EigoMigBlaWTQEGRQQmoLJ0ECooMSkBl6SRQUGRQAipLJ4GCIoMSUFk6Ce0EJd3Qr7szTOh1DYpSDjNYg/Za0KMjlANoBUo+Zekk9FjQ/A7F1IWwBSWesnQSKCgyKPGUpZNAQZFBiacsnYQeC8o2aGcoSyehz4KyF98VytJJoKDIUFAKCg0FpaDQUFAKCg0FpaDQUFAKCg0FpaDQUFAKCg0FpaDQUNAIQW8+HA7PMR+/iFIOMyhoWFD/3O+bj54hTkPDz+K7wtbBRsJPWPZWQj4CnFczdYatg43IJ1GAmcikf1OqiNnxeDHECOqfTw84DQ1r0M6wNDBAhKBvPnuaZYjT0Oy8nxQ0rhfv+vAZYBuUvfjOMFWwmfBksrmfGeQ0NCjlMIOChgV9NfSccxw0BRSUnyRBQ0EpKDQUlIJCQ0EpKDQUlIJCQ0EpKDQUlIJCQ0EpKDQUlIJCQ0EpKDQUlIJCQ0EpKDQUtNeC8nrQrlCWTkKPBeUV9Z2hLJ2EHs+TxHuSbgOsQZFBiacsnYQeC8o2aGcoSyehz4KyF98VytJJoKDIUFAKCg0FpaDQUFAKCg0FpaDQUFAKCg0F7bWgHAftCmXpJPRYUH6S1BnK0kmgoMigxFOWTgIFRQYlnrJ0EnosKNugnaEsnYQeC8oatDOUpZNAQZFBiacsnYQYQfMnK+M9H5SCdoahgCEiBH09fPQy4zxJKUDJZ2lggLCgLx7+1NWggM+oZw3aGbYONhJ7iuc8SSnY8XgxxArKeZJSgBLP0sAA8hrUk3qHFey8nxQ0XlC2QVOAEs/SwACxggLOk3QLBMXY0b0QlOOgKcDY0fCCrpN6hxXsvJ8UtNeCsgbtDGXpJFBQZDB2NAVtBwXtDGXpJPRYULZBO0NZOgl9FhTm+JmBElBZOgkUFBmUgMrSSaCgyKAEVJZOQp8F3fk2KExAZekk9FjQne/F4wRUlk4CBcUFJ6CydBIoKC44AZWlk9BjQXGaaFbABFSWTkKfBYXp5BrBGjTr9TxJO88tuOkqDGtQXFiDZhQUGhQ/KWhLUMphBGvQjIIiQ0EzCooMBc0oKDQoflLQlqCUwwyUgMrSSaCgyKAEVJZOAgVFBiWgsnQSKCgyKAGVpZNAQZFBCagsnQQKigxKQGXpJFBQZFACKksnoc+CwgwTmgGyoyloK3A+aDEDY0dT0HZQ0M5Qlk5CtKB8PmgCMHZ0LwTlPEkpANnRfRAU8Bn1OMfPDJSAVvZFECso4DxJ5DYQKyjgPEk4FYwZKAGt7ItAXoN6Uu+wEpRymIES0Mq+CNgGRQYloJV9EcT34uHmScI5fmagBDSSL4Yej4PiHD8zUALauBdFjz9Jwjl+ZqAEVJZOAgVFBiWgsnQSKCgyKAGVpZNAQZFBCagsnQQKigxKQGXpJFBQZFACKksngYIigxJQWToJFBQZlIDK0kmgoMigBFSWTgIfAU6goaAEGgpKoKGgBBoKSqChoAQaCkqgoaAEGgpKoKGgBBoKSqChoAQaCkqgucWCXh8MHIcrKx9crn0/OR4M7rjV5XLldf7bk/yH967mi3Il2ZrbLOiKi7Ur3feTY6fa6N7VbJlvMvnuWbGB/+L6/tn09CQb7WflolzZQYidh4L6Ss/Xi+9+4iq9/OtyRf5j9+9MyMrSm5gz3nf/XJxMHuevKBflylTJdgkKml0cZmNXLx4UC7fSrRjtLzaanvqTtneyWOavq9SP3tp3r5YW5cou0+wqt1lQ35Z0p2NX6ZX1YlFderP8ymIjb+N4MNjzthXLog26VD1OT3O3/buUi3Il2Z7bLGhRg/rF9ONlQV1fqBBysdG8xnTL1Wbq5NipuFqD5ivJ9lDQ9Rr08WVlo7xB6VqUs+WKoNcHJ+W7LNqg5UqyPRR01gadC1qumG+U996dwrNlVdBSRX9Gz3vx+YJ+qkFBs0WnPe8R5b1439Sc9eLz8c+9s2y2nJ/18+VoULRIK+Og5cragSwi4hYLujX/Sv3soaCtmf4odQluAxSUQENBCTQUlEBDQQk0FJRAQ0EJNBSUQPP/flb+/pkf0jQAAAAASUVORK5CYII=" /><!-- --></p>
<div class="sourceCode" id="cb28"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb28-1"><a href="#cb28-1" aria-hidden="true" tabindex="-1"></a><span class="co"># Distribuição de brasileiros casados por horas semanais de trabalho doméstico não remunerado, de acordo com seu sexo</span></span>
<span id="cb28-2"><a href="#cb28-2" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb28-3"><a href="#cb28-3" aria-hidden="true" tabindex="-1"></a>horas_trab_dom_sexo <span class="ot"><-</span> brasil_casados_vs <span class="sc">%>%</span> </span>
<span id="cb28-4"><a href="#cb28-4" aria-hidden="true" tabindex="-1"></a> <span class="fu">mutate</span>(<span class="at">horas_trab_dom =</span> <span class="fu">replace</span>(horas_trab_dom, horas_trab_dom <span class="sc">==</span> <span class="dv">96</span>, <span class="dv">0</span>)) <span class="sc">%>%</span> </span>
<span id="cb28-5"><a href="#cb28-5" aria-hidden="true" tabindex="-1"></a> <span class="fu">filter</span>(<span class="sc">!</span><span class="fu">is.na</span>(horas_trab_dom)) <span class="sc">%>%</span> </span>
<span id="cb28-6"><a href="#cb28-6" aria-hidden="true" tabindex="-1"></a> <span class="fu">group_by</span>(sexo) <span class="sc">%>%</span> </span>
<span id="cb28-7"><a href="#cb28-7" aria-hidden="true" tabindex="-1"></a> <span class="fu">ggplot</span>() <span class="sc">+</span></span>
<span id="cb28-8"><a href="#cb28-8" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_boxplot</span>(<span class="fu">aes</span>(<span class="at">x =</span> sexo, <span class="at">y =</span> horas_trab_dom, <span class="at">fill =</span> sexo)) <span class="sc">+</span></span>
<span id="cb28-9"><a href="#cb28-9" aria-hidden="true" tabindex="-1"></a> <span class="fu">scale_y_continuous</span>(<span class="at">breaks =</span> <span class="fu">c</span>(<span class="dv">0</span>, <span class="dv">10</span>, <span class="dv">20</span>, <span class="dv">30</span>, <span class="dv">40</span>, <span class="dv">50</span>, <span class="dv">60</span>, <span class="dv">70</span>, <span class="dv">80</span>, <span class="dv">90</span>, <span class="dv">100</span>)) <span class="sc">+</span></span>
<span id="cb28-10"><a href="#cb28-10" aria-hidden="true" tabindex="-1"></a> <span class="fu">scale_fill_manual</span>(<span class="at">labels =</span> <span class="fu">c</span>(<span class="st">"Masculino"</span>, <span class="st">"Femino"</span>),</span>
<span id="cb28-11"><a href="#cb28-11" aria-hidden="true" tabindex="-1"></a> <span class="at">values =</span> <span class="fu">c</span>(<span class="st">"lightblue3"</span>, <span class="st">"hotpink1"</span>)) <span class="sc">+</span></span>
<span id="cb28-12"><a href="#cb28-12" aria-hidden="true" tabindex="-1"></a> <span class="fu">labs</span>(<span class="at">y =</span> <span class="st">"Horas de trabalho doméstico"</span>, <span class="at">fill =</span> <span class="st">"Sexo"</span>,</span>
<span id="cb28-13"><a href="#cb28-13" aria-hidden="true" tabindex="-1"></a> <span class="at">title =</span> <span class="st">"Horas de trabalho doméstico por sexo"</span>,</span>
<span id="cb28-14"><a href="#cb28-14" aria-hidden="true" tabindex="-1"></a> <span class="at">caption =</span> <span class="st">"Fonte: ISSP, 2002."</span>)<span class="sc">+</span></span>
<span id="cb28-15"><a href="#cb28-15" aria-hidden="true" tabindex="-1"></a> <span class="fu">theme_minimal</span>()</span>
<span id="cb28-16"><a href="#cb28-16" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb28-17"><a href="#cb28-17" aria-hidden="true" tabindex="-1"></a>horas_trab_dom_sexo <span class="ot"><-</span> horas_trab_dom_sexo <span class="sc">+</span></span>
<span id="cb28-18"><a href="#cb28-18" aria-hidden="true" tabindex="-1"></a> <span class="fu">theme</span>(<span class="at">axis.title.x =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb28-19"><a href="#cb28-19" aria-hidden="true" tabindex="-1"></a> <span class="at">axis.ticks.x =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb28-20"><a href="#cb28-20" aria-hidden="true" tabindex="-1"></a> <span class="at">axis.text.x =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb28-21"><a href="#cb28-21" aria-hidden="true" tabindex="-1"></a> <span class="at">plot.title =</span> <span class="fu">element_text</span>(<span class="at">hjust =</span> <span class="fl">0.5</span>),</span>
<span id="cb28-22"><a href="#cb28-22" aria-hidden="true" tabindex="-1"></a> <span class="at">plot.caption =</span> <span class="fu">element_text</span>(<span class="at">hjust =</span> <span class="fl">0.5</span>))</span>
<span id="cb28-23"><a href="#cb28-23" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb28-24"><a href="#cb28-24" aria-hidden="true" tabindex="-1"></a><span class="fu">print</span>(horas_trab_dom_sexo)</span></code></pre></div>
<p><img src="data:image/png;base64,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" /><!-- --></p>
</div>
<div id="divisão-das-tarefas-domésticas-e-de-cuidados" class="section level4">
<h4>Divisão das tarefas domésticas e de cuidados</h4>
<div class="sourceCode" id="cb29"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb29-1"><a href="#cb29-1" aria-hidden="true" tabindex="-1"></a><span class="co"># Distribuição relativa de brasileiros casados de acordo com o responsável pela lavagem das roupas por sexo</span></span>
<span id="cb29-2"><a href="#cb29-2" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb29-3"><a href="#cb29-3" aria-hidden="true" tabindex="-1"></a>lava_roupa_sexo <span class="ot"><-</span> brasil_casados_vs <span class="sc">%>%</span></span>
<span id="cb29-4"><a href="#cb29-4" aria-hidden="true" tabindex="-1"></a> <span class="fu">mutate</span>(<span class="at">lavar_roupa1 =</span> <span class="fu">case_when</span>(</span>
<span id="cb29-5"><a href="#cb29-5" aria-hidden="true" tabindex="-1"></a> lavar_roupa <span class="sc">==</span> <span class="st">"Always my spouse,partner,PL:the man"</span> <span class="sc">~</span> <span class="st">"Sempre o cônjuge"</span>,</span>
<span id="cb29-6"><a href="#cb29-6" aria-hidden="true" tabindex="-1"></a> lavar_roupa <span class="sc">==</span> <span class="st">"Always my spouse,partner,PL:the woman"</span> <span class="sc">~</span> <span class="st">"Sempre o cônjuge"</span>,</span>
<span id="cb29-7"><a href="#cb29-7" aria-hidden="true" tabindex="-1"></a> lavar_roupa <span class="sc">==</span> <span class="st">"Always me,PL:the man"</span> <span class="sc">~</span> <span class="st">"Sempre eu"</span>,</span>
<span id="cb29-8"><a href="#cb29-8" aria-hidden="true" tabindex="-1"></a> lavar_roupa <span class="sc">==</span> <span class="st">"Always me,PL:the woman"</span> <span class="sc">~</span> <span class="st">"Sempre eu"</span>,</span>
<span id="cb29-9"><a href="#cb29-9" aria-hidden="true" tabindex="-1"></a> lavar_roupa <span class="sc">==</span> <span class="st">"Usually me,PL:the woman"</span> <span class="sc">~</span> <span class="st">"Geralmente eu"</span>,</span>
<span id="cb29-10"><a href="#cb29-10" aria-hidden="true" tabindex="-1"></a> lavar_roupa <span class="sc">==</span> <span class="st">"Usually me,PL:the man"</span> <span class="sc">~</span> <span class="st">"Geralmente eu"</span>,</span>
<span id="cb29-11"><a href="#cb29-11" aria-hidden="true" tabindex="-1"></a> lavar_roupa <span class="sc">==</span> <span class="st">"Done by a third person"</span> <span class="sc">~</span> <span class="st">"Feita por um terceiro"</span>,</span>
<span id="cb29-12"><a href="#cb29-12" aria-hidden="true" tabindex="-1"></a> lavar_roupa <span class="sc">==</span> <span class="st">"About equal o both together"</span> <span class="sc">~</span> <span class="st">"Tarefa feita pelos dois"</span>)) <span class="sc">%>%</span> </span>
<span id="cb29-13"><a href="#cb29-13" aria-hidden="true" tabindex="-1"></a> <span class="fu">filter</span>(<span class="sc">!</span><span class="fu">is.na</span>(lavar_roupa1)) <span class="sc">%>%</span> </span>
<span id="cb29-14"><a href="#cb29-14" aria-hidden="true" tabindex="-1"></a> <span class="fu">group_by</span>(sexo, lavar_roupa1) <span class="sc">%>%</span> </span>
<span id="cb29-15"><a href="#cb29-15" aria-hidden="true" tabindex="-1"></a> <span class="fu">summarise</span>(<span class="at">n =</span> <span class="fu">n</span>()) <span class="sc">%>%</span> </span>
<span id="cb29-16"><a href="#cb29-16" aria-hidden="true" tabindex="-1"></a> <span class="fu">mutate</span>(<span class="at">freq_lavar_roupa1 =</span> n<span class="sc">*</span><span class="dv">100</span><span class="sc">/</span><span class="fu">sum</span>(n)) <span class="sc">%>%</span> </span>
<span id="cb29-17"><a href="#cb29-17" aria-hidden="true" tabindex="-1"></a> <span class="fu">ggplot</span>(<span class="fu">aes</span>(<span class="at">x =</span> sexo, <span class="at">y =</span> freq_lavar_roupa1, <span class="at">fill =</span> sexo)) <span class="sc">+</span></span>
<span id="cb29-18"><a href="#cb29-18" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_bar</span>(<span class="at">stat =</span> <span class="st">"identity"</span>, <span class="at">show.legend =</span> <span class="cn">TRUE</span>) <span class="sc">+</span> <span class="fu">facet_grid</span>(lavar_roupa1 <span class="sc">~</span>.) <span class="sc">+</span></span>
<span id="cb29-19"><a href="#cb29-19" aria-hidden="true" tabindex="-1"></a> <span class="fu">coord_flip</span>() <span class="sc">+</span></span>
<span id="cb29-20"><a href="#cb29-20" aria-hidden="true" tabindex="-1"></a> <span class="fu">ylim</span>(<span class="fu">c</span>(<span class="dv">0</span>, <span class="dv">90</span>)) <span class="sc">+</span></span>
<span id="cb29-21"><a href="#cb29-21" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_text</span>(<span class="fu">aes</span>(<span class="at">label =</span> <span class="fu">round</span>(freq_lavar_roupa1, <span class="dv">2</span>)), <span class="at">hjust =</span> <span class="sc">-</span>.<span class="dv">1</span>) <span class="sc">+</span></span>
<span id="cb29-22"><a href="#cb29-22" aria-hidden="true" tabindex="-1"></a> <span class="fu">scale_fill_manual</span>(<span class="at">label =</span> <span class="fu">c</span>(<span class="st">"Masculino"</span>, <span class="st">"Feminino"</span>), <span class="at">values =</span> <span class="fu">c</span>(<span class="st">"lightblue3"</span>, <span class="st">"hotpink1"</span>)) <span class="sc">+</span></span>
<span id="cb29-23"><a href="#cb29-23" aria-hidden="true" tabindex="-1"></a> <span class="fu">theme</span>(<span class="at">strip.text =</span> <span class="fu">element_text</span>(<span class="at">size =</span> <span class="dv">12</span>)) <span class="sc">+</span></span>
<span id="cb29-24"><a href="#cb29-24" aria-hidden="true" tabindex="-1"></a> <span class="fu">labs</span>(<span class="at">title =</span> <span class="st">"Quem lava a roupa?"</span>,</span>
<span id="cb29-25"><a href="#cb29-25" aria-hidden="true" tabindex="-1"></a> <span class="at">caption =</span> <span class="st">"Fonte: ISSP, 2002."</span>) <span class="sc">+</span></span>
<span id="cb29-26"><a href="#cb29-26" aria-hidden="true" tabindex="-1"></a> <span class="fu">theme_minimal</span>() <span class="sc">+</span></span>
<span id="cb29-27"><a href="#cb29-27" aria-hidden="true" tabindex="-1"></a> <span class="fu">theme</span>(<span class="at">axis.title.y =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb29-28"><a href="#cb29-28" aria-hidden="true" tabindex="-1"></a> <span class="at">axis.ticks.y =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb29-29"><a href="#cb29-29" aria-hidden="true" tabindex="-1"></a> <span class="at">axis.text.y =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb29-30"><a href="#cb29-30" aria-hidden="true" tabindex="-1"></a> <span class="at">axis.title.x =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb29-31"><a href="#cb29-31" aria-hidden="true" tabindex="-1"></a> <span class="at">strip.text.y =</span> <span class="fu">element_text</span>(<span class="at">angle =</span> <span class="dv">0</span>),</span>
<span id="cb29-32"><a href="#cb29-32" aria-hidden="true" tabindex="-1"></a> <span class="at">plot.title =</span> <span class="fu">element_text</span>(<span class="at">hjust =</span> <span class="fl">0.5</span>),</span>
<span id="cb29-33"><a href="#cb29-33" aria-hidden="true" tabindex="-1"></a> <span class="at">plot.subtitle =</span> <span class="fu">element_text</span>(<span class="at">hjust =</span> <span class="dv">1</span>),</span>
<span id="cb29-34"><a href="#cb29-34" aria-hidden="true" tabindex="-1"></a> <span class="at">plot.caption =</span> <span class="fu">element_text</span>(<span class="at">hjust =</span> <span class="fl">0.5</span>))</span></code></pre></div>
<pre><code>## `summarise()` has grouped output by 'sexo'. You can override using the `.groups` argument.</code></pre>
<div class="sourceCode" id="cb31"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb31-1"><a href="#cb31-1" aria-hidden="true" tabindex="-1"></a><span class="fu">print</span>(lava_roupa_sexo)</span></code></pre></div>
<p><img src="data:image/png;base64,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" /><!-- --></p>
<div class="sourceCode" id="cb32"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb32-1"><a href="#cb32-1" aria-hidden="true" tabindex="-1"></a><span class="co"># Distribuição relativa de brasileiros casados de acordo com o responsável pela limpeza da casa por sexo</span></span>
<span id="cb32-2"><a href="#cb32-2" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb32-3"><a href="#cb32-3" aria-hidden="true" tabindex="-1"></a>limpeza_sexo <span class="ot"><-</span> brasil_casados_vs <span class="sc">%>%</span></span>
<span id="cb32-4"><a href="#cb32-4" aria-hidden="true" tabindex="-1"></a> <span class="fu">mutate</span>(<span class="at">limpeza1 =</span> <span class="fu">case_when</span>(</span>
<span id="cb32-5"><a href="#cb32-5" aria-hidden="true" tabindex="-1"></a> limpeza <span class="sc">==</span> <span class="st">"Always my spouse,partner,PL:the man"</span> <span class="sc">~</span> <span class="st">"Sempre o cônjuge"</span>,</span>
<span id="cb32-6"><a href="#cb32-6" aria-hidden="true" tabindex="-1"></a> limpeza <span class="sc">==</span> <span class="st">"Always my spouse,partner,PL:the woman"</span> <span class="sc">~</span> <span class="st">"Sempre o cônjuge"</span>,</span>
<span id="cb32-7"><a href="#cb32-7" aria-hidden="true" tabindex="-1"></a> limpeza <span class="sc">==</span> <span class="st">"Always me,PL:the man"</span> <span class="sc">~</span> <span class="st">"Sempre eu"</span>,</span>
<span id="cb32-8"><a href="#cb32-8" aria-hidden="true" tabindex="-1"></a> limpeza <span class="sc">==</span> <span class="st">"Always me,PL:the woman"</span> <span class="sc">~</span> <span class="st">"Sempre eu"</span>,</span>
<span id="cb32-9"><a href="#cb32-9" aria-hidden="true" tabindex="-1"></a> limpeza <span class="sc">==</span> <span class="st">"Usually me,PL:the woman"</span> <span class="sc">~</span> <span class="st">"Geralmente eu"</span>,</span>
<span id="cb32-10"><a href="#cb32-10" aria-hidden="true" tabindex="-1"></a> limpeza <span class="sc">==</span> <span class="st">"Usually me,PL:the man"</span> <span class="sc">~</span> <span class="st">"Geralmente eu"</span>,</span>
<span id="cb32-11"><a href="#cb32-11" aria-hidden="true" tabindex="-1"></a> limpeza <span class="sc">==</span> <span class="st">"Done by a third person"</span> <span class="sc">~</span> <span class="st">"Feita por um terceiro"</span>,</span>
<span id="cb32-12"><a href="#cb32-12" aria-hidden="true" tabindex="-1"></a> limpeza <span class="sc">==</span> <span class="st">"About equal o both together"</span> <span class="sc">~</span> <span class="st">"Tarefa feita pelos dois"</span>)) <span class="sc">%>%</span> </span>
<span id="cb32-13"><a href="#cb32-13" aria-hidden="true" tabindex="-1"></a> <span class="fu">filter</span>(<span class="sc">!</span><span class="fu">is.na</span>(limpeza1)) <span class="sc">%>%</span> </span>
<span id="cb32-14"><a href="#cb32-14" aria-hidden="true" tabindex="-1"></a> <span class="fu">group_by</span>(sexo, limpeza1) <span class="sc">%>%</span> </span>
<span id="cb32-15"><a href="#cb32-15" aria-hidden="true" tabindex="-1"></a> <span class="fu">summarise</span>(<span class="at">n =</span> <span class="fu">n</span>()) <span class="sc">%>%</span> </span>
<span id="cb32-16"><a href="#cb32-16" aria-hidden="true" tabindex="-1"></a> <span class="fu">mutate</span>(<span class="at">freq_limpeza1 =</span> n<span class="sc">*</span><span class="dv">100</span><span class="sc">/</span><span class="fu">sum</span>(n)) <span class="sc">%>%</span> </span>
<span id="cb32-17"><a href="#cb32-17" aria-hidden="true" tabindex="-1"></a> <span class="fu">ggplot</span>(<span class="fu">aes</span>(<span class="at">x =</span> sexo, <span class="at">y =</span> freq_limpeza1, <span class="at">fill =</span> sexo)) <span class="sc">+</span></span>
<span id="cb32-18"><a href="#cb32-18" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_bar</span>(<span class="at">stat =</span> <span class="st">"identity"</span>, <span class="at">show.legend =</span> <span class="cn">TRUE</span>) <span class="sc">+</span> <span class="fu">facet_grid</span>(limpeza1 <span class="sc">~</span>.) <span class="sc">+</span></span>
<span id="cb32-19"><a href="#cb32-19" aria-hidden="true" tabindex="-1"></a> <span class="fu">coord_flip</span>() <span class="sc">+</span></span>
<span id="cb32-20"><a href="#cb32-20" aria-hidden="true" tabindex="-1"></a> <span class="fu">ylim</span>(<span class="fu">c</span>(<span class="dv">0</span>, <span class="dv">90</span>)) <span class="sc">+</span></span>
<span id="cb32-21"><a href="#cb32-21" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_text</span>(<span class="fu">aes</span>(<span class="at">label =</span> <span class="fu">round</span>(freq_limpeza1, <span class="dv">2</span>)), <span class="at">hjust =</span> <span class="sc">-</span>.<span class="dv">1</span>) <span class="sc">+</span></span>
<span id="cb32-22"><a href="#cb32-22" aria-hidden="true" tabindex="-1"></a> <span class="fu">scale_fill_manual</span>(<span class="at">label =</span> <span class="fu">c</span>(<span class="st">"Masculino"</span>, <span class="st">"Feminino"</span>), <span class="at">values =</span> <span class="fu">c</span>(<span class="st">"lightblue3"</span>, <span class="st">"hotpink1"</span>)) <span class="sc">+</span></span>
<span id="cb32-23"><a href="#cb32-23" aria-hidden="true" tabindex="-1"></a> <span class="fu">theme</span>(<span class="at">strip.text =</span> <span class="fu">element_text</span>(<span class="at">size =</span> <span class="dv">12</span>)) <span class="sc">+</span></span>
<span id="cb32-24"><a href="#cb32-24" aria-hidden="true" tabindex="-1"></a> <span class="fu">labs</span>(<span class="at">title =</span> <span class="st">"Quem limpa?"</span>,</span>
<span id="cb32-25"><a href="#cb32-25" aria-hidden="true" tabindex="-1"></a> <span class="at">caption =</span> <span class="st">"Fonte: ISSP, 2002."</span>) <span class="sc">+</span></span>
<span id="cb32-26"><a href="#cb32-26" aria-hidden="true" tabindex="-1"></a> <span class="fu">theme_minimal</span>() <span class="sc">+</span></span>
<span id="cb32-27"><a href="#cb32-27" aria-hidden="true" tabindex="-1"></a> <span class="fu">theme</span>(<span class="at">axis.title.y =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb32-28"><a href="#cb32-28" aria-hidden="true" tabindex="-1"></a> <span class="at">axis.ticks.y =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb32-29"><a href="#cb32-29" aria-hidden="true" tabindex="-1"></a> <span class="at">axis.text.y =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb32-30"><a href="#cb32-30" aria-hidden="true" tabindex="-1"></a> <span class="at">axis.title.x =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb32-31"><a href="#cb32-31" aria-hidden="true" tabindex="-1"></a> <span class="at">strip.text.y =</span> <span class="fu">element_text</span>(<span class="at">angle =</span> <span class="dv">0</span>),</span>
<span id="cb32-32"><a href="#cb32-32" aria-hidden="true" tabindex="-1"></a> <span class="at">plot.title =</span> <span class="fu">element_text</span>(<span class="at">hjust =</span> <span class="fl">0.5</span>),</span>
<span id="cb32-33"><a href="#cb32-33" aria-hidden="true" tabindex="-1"></a> <span class="at">plot.subtitle =</span> <span class="fu">element_text</span>(<span class="at">hjust =</span> <span class="dv">1</span>),</span>
<span id="cb32-34"><a href="#cb32-34" aria-hidden="true" tabindex="-1"></a> <span class="at">plot.caption =</span> <span class="fu">element_text</span>(<span class="at">hjust =</span> <span class="fl">0.5</span>))</span></code></pre></div>
<pre><code>## `summarise()` has grouped output by 'sexo'. You can override using the `.groups` argument.</code></pre>
<div class="sourceCode" id="cb34"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb34-1"><a href="#cb34-1" aria-hidden="true" tabindex="-1"></a><span class="fu">print</span>(limpeza_sexo)</span></code></pre></div>
<p><img src="data:image/png;base64,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" /><!-- --></p>
<div class="sourceCode" id="cb35"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb35-1"><a href="#cb35-1" aria-hidden="true" tabindex="-1"></a><span class="co"># Distribuição relativa de brasileiros casados de acordo com os responsáveis pelo preparo das refeições por sexo</span></span>
<span id="cb35-2"><a href="#cb35-2" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb35-3"><a href="#cb35-3" aria-hidden="true" tabindex="-1"></a>comida_sexo <span class="ot"><-</span> brasil_casados_vs <span class="sc">%>%</span></span>
<span id="cb35-4"><a href="#cb35-4" aria-hidden="true" tabindex="-1"></a> <span class="fu">mutate</span>(<span class="at">comida1 =</span> <span class="fu">case_when</span>(</span>
<span id="cb35-5"><a href="#cb35-5" aria-hidden="true" tabindex="-1"></a> comida <span class="sc">==</span> <span class="st">"Always my spouse,partner,PL:the man"</span> <span class="sc">~</span> <span class="st">"Sempre o cônjuge"</span>,</span>
<span id="cb35-6"><a href="#cb35-6" aria-hidden="true" tabindex="-1"></a> comida <span class="sc">==</span> <span class="st">"Always my spouse,partner,PL:the woman"</span> <span class="sc">~</span> <span class="st">"Sempre o cônjuge"</span>,</span>
<span id="cb35-7"><a href="#cb35-7" aria-hidden="true" tabindex="-1"></a> comida <span class="sc">==</span> <span class="st">"Always me,PL:the man"</span> <span class="sc">~</span> <span class="st">"Sempre eu"</span>,</span>
<span id="cb35-8"><a href="#cb35-8" aria-hidden="true" tabindex="-1"></a> comida <span class="sc">==</span> <span class="st">"Always me,PL:the woman"</span> <span class="sc">~</span> <span class="st">"Sempre eu"</span>,</span>
<span id="cb35-9"><a href="#cb35-9" aria-hidden="true" tabindex="-1"></a> comida <span class="sc">==</span> <span class="st">"Usually me,PL:the woman"</span> <span class="sc">~</span> <span class="st">"Geralmente eu"</span>,</span>
<span id="cb35-10"><a href="#cb35-10" aria-hidden="true" tabindex="-1"></a> comida <span class="sc">==</span> <span class="st">"Usually me,PL:the man"</span> <span class="sc">~</span> <span class="st">"Geralmente eu"</span>,</span>
<span id="cb35-11"><a href="#cb35-11" aria-hidden="true" tabindex="-1"></a> comida <span class="sc">==</span> <span class="st">"Done by a third person"</span> <span class="sc">~</span> <span class="st">"Feita por um terceiro"</span>,</span>
<span id="cb35-12"><a href="#cb35-12" aria-hidden="true" tabindex="-1"></a> comida <span class="sc">==</span> <span class="st">"About equal o both together"</span> <span class="sc">~</span> <span class="st">"Tarefa feita pelos dois"</span>)) <span class="sc">%>%</span> </span>
<span id="cb35-13"><a href="#cb35-13" aria-hidden="true" tabindex="-1"></a> <span class="fu">filter</span>(<span class="sc">!</span><span class="fu">is.na</span>(comida1)) <span class="sc">%>%</span> </span>
<span id="cb35-14"><a href="#cb35-14" aria-hidden="true" tabindex="-1"></a> <span class="fu">group_by</span>(sexo, comida1) <span class="sc">%>%</span> </span>
<span id="cb35-15"><a href="#cb35-15" aria-hidden="true" tabindex="-1"></a> <span class="fu">summarise</span>(<span class="at">n =</span> <span class="fu">n</span>()) <span class="sc">%>%</span> </span>
<span id="cb35-16"><a href="#cb35-16" aria-hidden="true" tabindex="-1"></a> <span class="fu">mutate</span>(<span class="at">freq_comida1 =</span> n<span class="sc">*</span><span class="dv">100</span><span class="sc">/</span><span class="fu">sum</span>(n)) <span class="sc">%>%</span> </span>
<span id="cb35-17"><a href="#cb35-17" aria-hidden="true" tabindex="-1"></a> <span class="fu">ggplot</span>(<span class="fu">aes</span>(<span class="at">x =</span> sexo, <span class="at">y =</span> freq_comida1, <span class="at">fill =</span> sexo)) <span class="sc">+</span></span>
<span id="cb35-18"><a href="#cb35-18" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_bar</span>(<span class="at">stat =</span> <span class="st">"identity"</span>, <span class="at">show.legend =</span> <span class="cn">TRUE</span>) <span class="sc">+</span> <span class="fu">facet_grid</span>(comida1 <span class="sc">~</span>.) <span class="sc">+</span></span>
<span id="cb35-19"><a href="#cb35-19" aria-hidden="true" tabindex="-1"></a> <span class="fu">coord_flip</span>() <span class="sc">+</span></span>
<span id="cb35-20"><a href="#cb35-20" aria-hidden="true" tabindex="-1"></a> <span class="fu">ylim</span>(<span class="fu">c</span>(<span class="dv">0</span>, <span class="dv">90</span>)) <span class="sc">+</span></span>
<span id="cb35-21"><a href="#cb35-21" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_text</span>(<span class="fu">aes</span>(<span class="at">label =</span> <span class="fu">round</span>(freq_comida1, <span class="dv">2</span>)), <span class="at">hjust =</span> <span class="sc">-</span>.<span class="dv">1</span>) <span class="sc">+</span></span>
<span id="cb35-22"><a href="#cb35-22" aria-hidden="true" tabindex="-1"></a> <span class="fu">scale_fill_manual</span>(<span class="at">label =</span> <span class="fu">c</span>(<span class="st">"Masculino"</span>, <span class="st">"Feminino"</span>), <span class="at">values =</span> <span class="fu">c</span>(<span class="st">"lightblue3"</span>, <span class="st">"hotpink1"</span>)) <span class="sc">+</span></span>
<span id="cb35-23"><a href="#cb35-23" aria-hidden="true" tabindex="-1"></a> <span class="fu">theme</span>(<span class="at">strip.text =</span> <span class="fu">element_text</span>(<span class="at">size =</span> <span class="dv">12</span>)) <span class="sc">+</span></span>
<span id="cb35-24"><a href="#cb35-24" aria-hidden="true" tabindex="-1"></a> <span class="fu">labs</span>(<span class="at">title =</span> <span class="st">"Quem cozinha?"</span>,</span>
<span id="cb35-25"><a href="#cb35-25" aria-hidden="true" tabindex="-1"></a> <span class="at">caption =</span> <span class="st">"Fonte: ISSP, 2002."</span>) <span class="sc">+</span></span>
<span id="cb35-26"><a href="#cb35-26" aria-hidden="true" tabindex="-1"></a> <span class="fu">theme_minimal</span>() <span class="sc">+</span></span>
<span id="cb35-27"><a href="#cb35-27" aria-hidden="true" tabindex="-1"></a> <span class="fu">theme</span>(<span class="at">axis.title.y =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb35-28"><a href="#cb35-28" aria-hidden="true" tabindex="-1"></a> <span class="at">axis.ticks.y =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb35-29"><a href="#cb35-29" aria-hidden="true" tabindex="-1"></a> <span class="at">axis.text.y =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb35-30"><a href="#cb35-30" aria-hidden="true" tabindex="-1"></a> <span class="at">axis.title.x =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb35-31"><a href="#cb35-31" aria-hidden="true" tabindex="-1"></a> <span class="at">strip.text.y =</span> <span class="fu">element_text</span>(<span class="at">angle =</span> <span class="dv">0</span>),</span>
<span id="cb35-32"><a href="#cb35-32" aria-hidden="true" tabindex="-1"></a> <span class="at">plot.title =</span> <span class="fu">element_text</span>(<span class="at">hjust =</span> <span class="fl">0.5</span>),</span>
<span id="cb35-33"><a href="#cb35-33" aria-hidden="true" tabindex="-1"></a> <span class="at">plot.subtitle =</span> <span class="fu">element_text</span>(<span class="at">hjust =</span> <span class="dv">1</span>),</span>
<span id="cb35-34"><a href="#cb35-34" aria-hidden="true" tabindex="-1"></a> <span class="at">plot.caption =</span> <span class="fu">element_text</span>(<span class="at">hjust =</span> <span class="fl">0.5</span>))</span></code></pre></div>
<pre><code>## `summarise()` has grouped output by 'sexo'. You can override using the `.groups` argument.</code></pre>
<div class="sourceCode" id="cb37"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb37-1"><a href="#cb37-1" aria-hidden="true" tabindex="-1"></a><span class="fu">print</span>(comida_sexo)</span></code></pre></div>
<p><img src="data:image/png;base64,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" /><!-- --></p>
<div class="sourceCode" id="cb38"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb38-1"><a href="#cb38-1" aria-hidden="true" tabindex="-1"></a><span class="co"># Distribuição relativa de brasileiros casados de acordo com o responsável pela realização de pequenos reparos por sexo</span></span>
<span id="cb38-2"><a href="#cb38-2" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb38-3"><a href="#cb38-3" aria-hidden="true" tabindex="-1"></a>pequenos_reparos_sexo <span class="ot"><-</span> brasil_casados_vs <span class="sc">%>%</span></span>
<span id="cb38-4"><a href="#cb38-4" aria-hidden="true" tabindex="-1"></a> <span class="fu">mutate</span>(<span class="at">pequenos_reparos1 =</span> <span class="fu">case_when</span>(</span>
<span id="cb38-5"><a href="#cb38-5" aria-hidden="true" tabindex="-1"></a> pequenos_reparos <span class="sc">==</span> <span class="st">"Always my spouse,partner,PL:the man"</span> <span class="sc">~</span> <span class="st">"Sempre o cônjuge"</span>,</span>
<span id="cb38-6"><a href="#cb38-6" aria-hidden="true" tabindex="-1"></a> pequenos_reparos <span class="sc">==</span> <span class="st">"Always my spouse,partner,PL:the woman"</span> <span class="sc">~</span> <span class="st">"Sempre o cônjuge"</span>,</span>
<span id="cb38-7"><a href="#cb38-7" aria-hidden="true" tabindex="-1"></a> pequenos_reparos <span class="sc">==</span> <span class="st">"Always me,PL:the man"</span> <span class="sc">~</span> <span class="st">"Sempre eu"</span>,</span>
<span id="cb38-8"><a href="#cb38-8" aria-hidden="true" tabindex="-1"></a> pequenos_reparos <span class="sc">==</span> <span class="st">"Always me,PL:the woman"</span> <span class="sc">~</span> <span class="st">"Sempre eu"</span>,</span>
<span id="cb38-9"><a href="#cb38-9" aria-hidden="true" tabindex="-1"></a> pequenos_reparos <span class="sc">==</span> <span class="st">"Usually me,PL:the woman"</span> <span class="sc">~</span> <span class="st">"Geralmente eu"</span>,</span>
<span id="cb38-10"><a href="#cb38-10" aria-hidden="true" tabindex="-1"></a> pequenos_reparos <span class="sc">==</span> <span class="st">"Usually me,PL:the man"</span> <span class="sc">~</span> <span class="st">"Geralmente eu"</span>,</span>
<span id="cb38-11"><a href="#cb38-11" aria-hidden="true" tabindex="-1"></a> pequenos_reparos <span class="sc">==</span> <span class="st">"Done by a third person"</span> <span class="sc">~</span> <span class="st">"Feita por um terceiro"</span>,</span>
<span id="cb38-12"><a href="#cb38-12" aria-hidden="true" tabindex="-1"></a> pequenos_reparos <span class="sc">==</span> <span class="st">"About equal o both together"</span> <span class="sc">~</span> <span class="st">"Tarefa feita pelos dois"</span>)) <span class="sc">%>%</span> </span>
<span id="cb38-13"><a href="#cb38-13" aria-hidden="true" tabindex="-1"></a> <span class="fu">filter</span>(<span class="sc">!</span><span class="fu">is.na</span>(pequenos_reparos1)) <span class="sc">%>%</span> </span>
<span id="cb38-14"><a href="#cb38-14" aria-hidden="true" tabindex="-1"></a> <span class="fu">group_by</span>(sexo, pequenos_reparos1) <span class="sc">%>%</span> </span>
<span id="cb38-15"><a href="#cb38-15" aria-hidden="true" tabindex="-1"></a> <span class="fu">summarise</span>(<span class="at">n =</span> <span class="fu">n</span>()) <span class="sc">%>%</span> </span>
<span id="cb38-16"><a href="#cb38-16" aria-hidden="true" tabindex="-1"></a> <span class="fu">mutate</span>(<span class="at">freq_pequenos_reparos1 =</span> n<span class="sc">*</span><span class="dv">100</span><span class="sc">/</span><span class="fu">sum</span>(n)) <span class="sc">%>%</span> </span>
<span id="cb38-17"><a href="#cb38-17" aria-hidden="true" tabindex="-1"></a> <span class="fu">ggplot</span>(<span class="fu">aes</span>(<span class="at">x =</span> sexo, <span class="at">y =</span> freq_pequenos_reparos1, <span class="at">fill =</span> sexo)) <span class="sc">+</span></span>
<span id="cb38-18"><a href="#cb38-18" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_bar</span>(<span class="at">stat =</span> <span class="st">"identity"</span>, <span class="at">show.legend =</span> <span class="cn">TRUE</span>) <span class="sc">+</span> <span class="fu">facet_grid</span>(pequenos_reparos1 <span class="sc">~</span>.) <span class="sc">+</span></span>
<span id="cb38-19"><a href="#cb38-19" aria-hidden="true" tabindex="-1"></a> <span class="fu">coord_flip</span>() <span class="sc">+</span></span>
<span id="cb38-20"><a href="#cb38-20" aria-hidden="true" tabindex="-1"></a> <span class="fu">ylim</span>(<span class="fu">c</span>(<span class="dv">0</span>, <span class="dv">90</span>)) <span class="sc">+</span></span>
<span id="cb38-21"><a href="#cb38-21" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_text</span>(<span class="fu">aes</span>(<span class="at">label =</span> <span class="fu">round</span>(freq_pequenos_reparos1, <span class="dv">2</span>)), <span class="at">hjust =</span> <span class="sc">-</span>.<span class="dv">1</span>) <span class="sc">+</span></span>
<span id="cb38-22"><a href="#cb38-22" aria-hidden="true" tabindex="-1"></a> <span class="fu">scale_fill_manual</span>(<span class="at">label =</span> <span class="fu">c</span>(<span class="st">"Masculino"</span>, <span class="st">"Feminino"</span>), <span class="at">values =</span> <span class="fu">c</span>(<span class="st">"lightblue3"</span>, <span class="st">"hotpink1"</span>)) <span class="sc">+</span></span>
<span id="cb38-23"><a href="#cb38-23" aria-hidden="true" tabindex="-1"></a> <span class="fu">theme</span>(<span class="at">strip.text =</span> <span class="fu">element_text</span>(<span class="at">size =</span> <span class="dv">12</span>)) <span class="sc">+</span></span>
<span id="cb38-24"><a href="#cb38-24" aria-hidden="true" tabindex="-1"></a> <span class="fu">labs</span>(<span class="at">title =</span> <span class="st">"Quem faz pequenos reparos?"</span>,</span>
<span id="cb38-25"><a href="#cb38-25" aria-hidden="true" tabindex="-1"></a> <span class="at">caption =</span> <span class="st">"Fonte: ISSP, 2002."</span>) <span class="sc">+</span></span>
<span id="cb38-26"><a href="#cb38-26" aria-hidden="true" tabindex="-1"></a> <span class="fu">theme_minimal</span>() <span class="sc">+</span></span>
<span id="cb38-27"><a href="#cb38-27" aria-hidden="true" tabindex="-1"></a> <span class="fu">theme</span>(<span class="at">axis.title.y =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb38-28"><a href="#cb38-28" aria-hidden="true" tabindex="-1"></a> <span class="at">axis.ticks.y =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb38-29"><a href="#cb38-29" aria-hidden="true" tabindex="-1"></a> <span class="at">axis.text.y =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb38-30"><a href="#cb38-30" aria-hidden="true" tabindex="-1"></a> <span class="at">axis.title.x =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb38-31"><a href="#cb38-31" aria-hidden="true" tabindex="-1"></a> <span class="at">strip.text.y =</span> <span class="fu">element_text</span>(<span class="at">angle =</span> <span class="dv">0</span>),</span>
<span id="cb38-32"><a href="#cb38-32" aria-hidden="true" tabindex="-1"></a> <span class="at">plot.title =</span> <span class="fu">element_text</span>(<span class="at">hjust =</span> <span class="fl">0.5</span>),</span>
<span id="cb38-33"><a href="#cb38-33" aria-hidden="true" tabindex="-1"></a> <span class="at">plot.subtitle =</span> <span class="fu">element_text</span>(<span class="at">hjust =</span> <span class="dv">1</span>),</span>
<span id="cb38-34"><a href="#cb38-34" aria-hidden="true" tabindex="-1"></a> <span class="at">plot.caption =</span> <span class="fu">element_text</span>(<span class="at">hjust =</span> <span class="fl">0.5</span>))</span></code></pre></div>
<pre><code>## `summarise()` has grouped output by 'sexo'. You can override using the `.groups` argument.</code></pre>
<div class="sourceCode" id="cb40"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb40-1"><a href="#cb40-1" aria-hidden="true" tabindex="-1"></a><span class="fu">print</span>(pequenos_reparos_sexo)</span></code></pre></div>
<p><img src="data:image/png;base64,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" /><!-- --></p>
<div class="sourceCode" id="cb41"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb41-1"><a href="#cb41-1" aria-hidden="true" tabindex="-1"></a><span class="co"># Distribuição relativa de brasileiros casados de acordo com o responsável por cuidar de parentes doentes por sexo</span></span>
<span id="cb41-2"><a href="#cb41-2" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb41-3"><a href="#cb41-3" aria-hidden="true" tabindex="-1"></a>doença_parentes_sexo <span class="ot"><-</span> brasil_casados_vs <span class="sc">%>%</span></span>
<span id="cb41-4"><a href="#cb41-4" aria-hidden="true" tabindex="-1"></a> <span class="fu">mutate</span>(doença<span class="at">_parentes1 =</span> <span class="fu">case_when</span>(</span>
<span id="cb41-5"><a href="#cb41-5" aria-hidden="true" tabindex="-1"></a> doença_parentes <span class="sc">==</span> <span class="st">"Always my spouse,partner,PL:the man"</span> <span class="sc">~</span> <span class="st">"Sempre o cônjuge"</span>,</span>
<span id="cb41-6"><a href="#cb41-6" aria-hidden="true" tabindex="-1"></a> doença_parentes <span class="sc">==</span> <span class="st">"Always my spouse,partner,PL:the woman"</span> <span class="sc">~</span> <span class="st">"Sempre o cônjuge"</span>,</span>
<span id="cb41-7"><a href="#cb41-7" aria-hidden="true" tabindex="-1"></a> doença_parentes <span class="sc">==</span> <span class="st">"Always me,PL:the man"</span> <span class="sc">~</span> <span class="st">"Sempre eu"</span>,</span>
<span id="cb41-8"><a href="#cb41-8" aria-hidden="true" tabindex="-1"></a> doença_parentes <span class="sc">==</span> <span class="st">"Always me,PL:the woman"</span> <span class="sc">~</span> <span class="st">"Sempre eu"</span>,</span>
<span id="cb41-9"><a href="#cb41-9" aria-hidden="true" tabindex="-1"></a> doença_parentes <span class="sc">==</span> <span class="st">"Usually me,PL:the woman"</span> <span class="sc">~</span> <span class="st">"Geralmente eu"</span>,</span>
<span id="cb41-10"><a href="#cb41-10" aria-hidden="true" tabindex="-1"></a> doença_parentes <span class="sc">==</span> <span class="st">"Usually me,PL:the man"</span> <span class="sc">~</span> <span class="st">"Geralmente eu"</span>,</span>
<span id="cb41-11"><a href="#cb41-11" aria-hidden="true" tabindex="-1"></a> doença_parentes <span class="sc">==</span> <span class="st">"Done by a third person"</span> <span class="sc">~</span> <span class="st">"Feita por um terceiro"</span>,</span>
<span id="cb41-12"><a href="#cb41-12" aria-hidden="true" tabindex="-1"></a> doença_parentes <span class="sc">==</span> <span class="st">"About equal o both together"</span> <span class="sc">~</span> <span class="st">"Tarefa feita pelos dois"</span>)) <span class="sc">%>%</span> </span>
<span id="cb41-13"><a href="#cb41-13" aria-hidden="true" tabindex="-1"></a> <span class="fu">filter</span>(<span class="sc">!</span><span class="fu">is.na</span>(doença_parentes1)) <span class="sc">%>%</span> </span>
<span id="cb41-14"><a href="#cb41-14" aria-hidden="true" tabindex="-1"></a> <span class="fu">group_by</span>(sexo, doença_parentes1) <span class="sc">%>%</span> </span>
<span id="cb41-15"><a href="#cb41-15" aria-hidden="true" tabindex="-1"></a> <span class="fu">summarise</span>(<span class="at">n =</span> <span class="fu">n</span>()) <span class="sc">%>%</span> </span>
<span id="cb41-16"><a href="#cb41-16" aria-hidden="true" tabindex="-1"></a> <span class="fu">mutate</span>(freq_doença<span class="at">_parentes1 =</span> n<span class="sc">*</span><span class="dv">100</span><span class="sc">/</span><span class="fu">sum</span>(n)) <span class="sc">%>%</span> </span>
<span id="cb41-17"><a href="#cb41-17" aria-hidden="true" tabindex="-1"></a> <span class="fu">ggplot</span>(<span class="fu">aes</span>(<span class="at">x =</span> sexo, <span class="at">y =</span> freq_doença_parentes1, <span class="at">fill =</span> sexo)) <span class="sc">+</span></span>
<span id="cb41-18"><a href="#cb41-18" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_bar</span>(<span class="at">stat =</span> <span class="st">"identity"</span>, <span class="at">show.legend =</span> <span class="cn">TRUE</span>) <span class="sc">+</span> <span class="fu">facet_grid</span>(doença_parentes1 <span class="sc">~</span>.) <span class="sc">+</span></span>
<span id="cb41-19"><a href="#cb41-19" aria-hidden="true" tabindex="-1"></a> <span class="fu">coord_flip</span>() <span class="sc">+</span></span>
<span id="cb41-20"><a href="#cb41-20" aria-hidden="true" tabindex="-1"></a> <span class="fu">ylim</span>(<span class="fu">c</span>(<span class="dv">0</span>, <span class="dv">90</span>)) <span class="sc">+</span></span>
<span id="cb41-21"><a href="#cb41-21" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_text</span>(<span class="fu">aes</span>(<span class="at">label =</span> <span class="fu">round</span>(freq_doença_parentes1, <span class="dv">2</span>)), <span class="at">hjust =</span> <span class="sc">-</span>.<span class="dv">1</span>) <span class="sc">+</span></span>
<span id="cb41-22"><a href="#cb41-22" aria-hidden="true" tabindex="-1"></a> <span class="fu">scale_fill_manual</span>(<span class="at">label =</span> <span class="fu">c</span>(<span class="st">"Masculino"</span>, <span class="st">"Feminino"</span>), <span class="at">values =</span> <span class="fu">c</span>(<span class="st">"lightblue3"</span>, <span class="st">"hotpink1"</span>)) <span class="sc">+</span></span>
<span id="cb41-23"><a href="#cb41-23" aria-hidden="true" tabindex="-1"></a> <span class="fu">theme</span>(<span class="at">strip.text =</span> <span class="fu">element_text</span>(<span class="at">size =</span> <span class="dv">12</span>)) <span class="sc">+</span></span>
<span id="cb41-24"><a href="#cb41-24" aria-hidden="true" tabindex="-1"></a> <span class="fu">labs</span>(<span class="at">title =</span> <span class="st">"Quem cuida de parentes doentes?"</span>,</span>
<span id="cb41-25"><a href="#cb41-25" aria-hidden="true" tabindex="-1"></a> <span class="at">caption =</span> <span class="st">"Fonte: ISSP, 2002."</span>) <span class="sc">+</span></span>
<span id="cb41-26"><a href="#cb41-26" aria-hidden="true" tabindex="-1"></a> <span class="fu">theme_minimal</span>() <span class="sc">+</span></span>
<span id="cb41-27"><a href="#cb41-27" aria-hidden="true" tabindex="-1"></a> <span class="fu">theme</span>(<span class="at">axis.title.y =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb41-28"><a href="#cb41-28" aria-hidden="true" tabindex="-1"></a> <span class="at">axis.ticks.y =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb41-29"><a href="#cb41-29" aria-hidden="true" tabindex="-1"></a> <span class="at">axis.text.y =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb41-30"><a href="#cb41-30" aria-hidden="true" tabindex="-1"></a> <span class="at">axis.title.x =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb41-31"><a href="#cb41-31" aria-hidden="true" tabindex="-1"></a> <span class="at">strip.text.y =</span> <span class="fu">element_text</span>(<span class="at">angle =</span> <span class="dv">0</span>),</span>
<span id="cb41-32"><a href="#cb41-32" aria-hidden="true" tabindex="-1"></a> <span class="at">plot.title =</span> <span class="fu">element_text</span>(<span class="at">hjust =</span> <span class="fl">0.5</span>),</span>
<span id="cb41-33"><a href="#cb41-33" aria-hidden="true" tabindex="-1"></a> <span class="at">plot.subtitle =</span> <span class="fu">element_text</span>(<span class="at">hjust =</span> <span class="dv">1</span>),</span>
<span id="cb41-34"><a href="#cb41-34" aria-hidden="true" tabindex="-1"></a> <span class="at">plot.caption =</span> <span class="fu">element_text</span>(<span class="at">hjust =</span> <span class="fl">0.5</span>))</span></code></pre></div>
<pre><code>## `summarise()` has grouped output by 'sexo'. You can override using the `.groups` argument.</code></pre>
<div class="sourceCode" id="cb43"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb43-1"><a href="#cb43-1" aria-hidden="true" tabindex="-1"></a><span class="fu">print</span>(doença_parentes_sexo)</span></code></pre></div>
<p><img src="data:image/png;base64,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" /><!-- --></p>
<div id="percepção-a-respeito-da-divisão" class="section level5">
<h5>Percepção a respeito da divisão</h5>
<div class="sourceCode" id="cb44"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb44-1"><a href="#cb44-1" aria-hidden="true" tabindex="-1"></a><span class="co"># Distribuição relativa dos brasileiros casados de acordo com a percepção que tem a respeito de sua participação na realização dos afazeres domésticos por sexo</span></span>
<span id="cb44-2"><a href="#cb44-2" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb44-3"><a href="#cb44-3" aria-hidden="true" tabindex="-1"></a>divisão_dom_sexo <span class="ot"><-</span> brasil_casados_vs <span class="sc">%>%</span> </span>
<span id="cb44-4"><a href="#cb44-4" aria-hidden="true" tabindex="-1"></a> <span class="fu">mutate</span>(divisão<span class="at">_tar_dom1 =</span> <span class="fu">case_when</span>(</span>
<span id="cb44-5"><a href="#cb44-5" aria-hidden="true" tabindex="-1"></a> divisão_tar_dom <span class="sc">==</span> <span class="st">"I do much more than my fair share"</span> <span class="sc">~</span> <span class="st">"Eu faço muito mais do que seria justo"</span>,</span>
<span id="cb44-6"><a href="#cb44-6" aria-hidden="true" tabindex="-1"></a> divisão_tar_dom <span class="sc">==</span> <span class="st">"I do much less than my fair share"</span> <span class="sc">~</span> <span class="st">"Eu faço muito menos do que seria justo"</span>,</span>
<span id="cb44-7"><a href="#cb44-7" aria-hidden="true" tabindex="-1"></a> divisão_tar_dom <span class="sc">==</span> <span class="st">"I do a bit more than my fair share"</span> <span class="sc">~</span> <span class="st">"Eu faço um pouco mais do que seria justo"</span>,</span>
<span id="cb44-8"><a href="#cb44-8" aria-hidden="true" tabindex="-1"></a> divisão_tar_dom <span class="sc">==</span> <span class="st">"I do roughly my fair shar"</span> <span class="sc">~</span> <span class="st">"Eu faço aproximadamente o que seria justo"</span>,</span>
<span id="cb44-9"><a href="#cb44-9" aria-hidden="true" tabindex="-1"></a> divisão_tar_dom <span class="sc">==</span> <span class="st">"I do a bit less than my fair share"</span> <span class="sc">~</span> <span class="st">"Eu faço um pouco menos do que seria justo"</span>)) <span class="sc">%>%</span> </span>
<span id="cb44-10"><a href="#cb44-10" aria-hidden="true" tabindex="-1"></a> <span class="fu">filter</span>(<span class="sc">!</span><span class="fu">is.na</span>(divisão_tar_dom1)) <span class="sc">%>%</span> </span>
<span id="cb44-11"><a href="#cb44-11" aria-hidden="true" tabindex="-1"></a> <span class="fu">group_by</span>(sexo, divisão_tar_dom1) <span class="sc">%>%</span> </span>
<span id="cb44-12"><a href="#cb44-12" aria-hidden="true" tabindex="-1"></a> <span class="fu">summarize</span>(<span class="at">n =</span> <span class="fu">n</span>()) <span class="sc">%>%</span> </span>
<span id="cb44-13"><a href="#cb44-13" aria-hidden="true" tabindex="-1"></a> <span class="fu">mutate</span>(freq_divisão <span class="ot">=</span> n<span class="sc">*</span><span class="dv">100</span><span class="sc">/</span><span class="fu">sum</span>(n)) <span class="sc">%>%</span> </span>
<span id="cb44-14"><a href="#cb44-14" aria-hidden="true" tabindex="-1"></a> <span class="fu">mutate</span>(freq_divisão <span class="ot">=</span> <span class="fu">round</span>(freq_divisão, <span class="dv">2</span>)) <span class="sc">%>%</span> </span>
<span id="cb44-15"><a href="#cb44-15" aria-hidden="true" tabindex="-1"></a> <span class="fu">ggplot</span>(<span class="fu">aes</span>(<span class="at">x =</span> sexo, <span class="at">y =</span> freq_divisão, <span class="at">fill =</span> sexo)) <span class="sc">+</span></span>
<span id="cb44-16"><a href="#cb44-16" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_bar</span>(<span class="at">stat =</span> <span class="st">"identity"</span>, <span class="at">show.legend =</span> <span class="cn">TRUE</span>) <span class="sc">+</span> <span class="fu">facet_grid</span>(divisão_tar_dom1 <span class="sc">~</span>., <span class="at">labeller =</span> <span class="fu">label_wrap_gen</span>(<span class="at">width =</span> <span class="dv">15</span>)) <span class="sc">+</span></span>
<span id="cb44-17"><a href="#cb44-17" aria-hidden="true" tabindex="-1"></a> <span class="fu">coord_flip</span>() <span class="sc">+</span></span>
<span id="cb44-18"><a href="#cb44-18" aria-hidden="true" tabindex="-1"></a> <span class="fu">ylim</span>(<span class="fu">c</span>(<span class="dv">0</span>, <span class="dv">90</span>)) <span class="sc">+</span></span>
<span id="cb44-19"><a href="#cb44-19" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_text</span>(<span class="fu">aes</span>(<span class="at">label =</span> <span class="fu">round</span>(freq_divisão, <span class="dv">2</span>)), <span class="at">hjust =</span> <span class="dv">1</span>) <span class="sc">+</span></span>
<span id="cb44-20"><a href="#cb44-20" aria-hidden="true" tabindex="-1"></a> <span class="fu">scale_fill_manual</span>(<span class="at">label =</span> <span class="fu">c</span>(<span class="st">"Masculino"</span>, <span class="st">"Feminino"</span>), <span class="at">values =</span> <span class="fu">c</span>(<span class="st">"lightblue3"</span>, <span class="st">"hotpink1"</span>)) <span class="sc">+</span></span>
<span id="cb44-21"><a href="#cb44-21" aria-hidden="true" tabindex="-1"></a> <span class="fu">theme</span>(<span class="at">strip.text =</span> <span class="fu">element_text</span>(<span class="at">size =</span> <span class="dv">12</span>)) <span class="sc">+</span></span>
<span id="cb44-22"><a href="#cb44-22" aria-hidden="true" tabindex="-1"></a> <span class="fu">labs</span>(<span class="at">title =</span> <span class="st">"Divisão das tarefas domésticas"</span>,</span>
<span id="cb44-23"><a href="#cb44-23" aria-hidden="true" tabindex="-1"></a> <span class="at">caption =</span> <span class="st">"Fonte: ISSP, 2002."</span>) <span class="sc">+</span></span>
<span id="cb44-24"><a href="#cb44-24" aria-hidden="true" tabindex="-1"></a> <span class="fu">theme_minimal</span>() <span class="sc">+</span></span>
<span id="cb44-25"><a href="#cb44-25" aria-hidden="true" tabindex="-1"></a> <span class="fu">theme</span>(<span class="at">axis.title.y =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb44-26"><a href="#cb44-26" aria-hidden="true" tabindex="-1"></a> <span class="at">axis.ticks.y =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb44-27"><a href="#cb44-27" aria-hidden="true" tabindex="-1"></a> <span class="at">axis.text.y =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb44-28"><a href="#cb44-28" aria-hidden="true" tabindex="-1"></a> <span class="at">axis.title.x =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb44-29"><a href="#cb44-29" aria-hidden="true" tabindex="-1"></a> <span class="at">strip.text.y =</span> <span class="fu">element_text</span>(<span class="at">angle =</span> <span class="dv">0</span>),</span>
<span id="cb44-30"><a href="#cb44-30" aria-hidden="true" tabindex="-1"></a> <span class="at">plot.title =</span> <span class="fu">element_text</span>(<span class="at">hjust =</span> <span class="fl">0.5</span>),</span>
<span id="cb44-31"><a href="#cb44-31" aria-hidden="true" tabindex="-1"></a> <span class="at">plot.subtitle =</span> <span class="fu">element_text</span>(<span class="at">hjust =</span> <span class="dv">1</span>),</span>