Amend sections

README.md

@@ -1,6 +1,6 @@
 # Geospatial Assessment of Women Employment and Business Opportunities in the Renewable Energy Sector
 
-With support from the Canada Clean Energy and Forest Climate Facility (CCEFCFy), the Geospatial Operational Support Team (GOST, DECSC) launched the project "Geospatial Assessment of Women Employment and Business Opportunities in the Renewable Energy Sector." The project aims to propose a novel methodology and generate a geospatial open-source tool for mapping the enabling environments for women in a country that can inform new energy projects to support the advancement of women's economic empowerment in SIDS while contributing to closing gender gaps in employment in the RE sector. 
+With support from the [Canada Clean Energy and Forest Climate Facility (CCEFCFy)](https://www.worldbank.org/en/topic/climatechange/brief/canada-world-bank-clean-energy-and-forests-climate-facility), the [Geospatial Operational Support Team (GOST, DECSC)](https://worldbank.github.io/GOST) launched the project "Geospatial Assessment of Women Employment and Business Opportunities in the Renewable Energy Sector." The project aims to propose a novel methodology and generate a geospatial open-source tool for mapping the enabling environments for women in a country that can inform new energy projects to support the advancement of women's economic empowerment in SIDS while contributing to closing gender gaps in employment in the RE sector.
 
 ![image](docs/images/img01.png)
 
@@ -15,67 +15,70 @@ Countries included in the project:
 | Cabo Verde | Antigua and Barbuda | Federated States of Micronesia | Maldives |
 | Comoros | Belize | Fiji  | |
 | Guinea-Bissau | Dominica | Kiribati | |
-| Mauritius | Dominican Republic | Marshall Islands | | 
+| Mauritius | Dominican Republic | Marshall Islands | |
 | São Tomé and Príncipe | Grenada | Nauru | |  
 | | Guyana | Niue | |  
 | | Haiti | Palau | |  
 | | Jamaica | Papua New Guinea | |  
 | | St. Lucia | Samoa | |  
-| | St. Vincent and Grenadines | Solomon Islands | | 
+| | St. Vincent and Grenadines | Solomon Islands | |
 | | Suriname | Timor-Leste | |  
 | | | Tonga | |  
 | | | Tuvalu | |  
-| | | Vanuatu | | 
+| | | Vanuatu | |
 
 </font>
 
-## Project Components
+**Project Components**
 
 The project is divided into six main components:
 
-  1. [Gender Spatial Data Gap Assessment](#gender-spatial-data-gap-assessment)
-  2. [Geospatial Databases](#geospatial-databases)
-  3. [Novel Analytical Framework](#novel-analytical-framework)
-  4. [Gender Enabling Environments Tool (GEEST)](#gender-enabling-environments-tool-geest)
-  5. [Implementation](#implementation)
-  6. [GEEST Main Limitations](#geest-main-limitations)
+  1. [Gender Spatial Data Gap Assessment](gender-spatial-data-gap-assessment)
+  2. [Geospatial Databases](geospatial-databases)
+  3. [Novel Analytical Framework](novel-analytical-framework)
+  4. [Gender Enabling Environments Tool (GEEST)](gender-enabling-environments-tool-geest)
+  5. [Implementation](implementation)
+  6. [GEEST Main Limitations](geest-main-limitations)
+
+(gender-spatial-data-gap-assessment)=
+
+## 1. Gender Spatial Data Gap Assessment
 
-### 1. Gender Spatial Data Gap Assessment:
 This undertaking involved the identification and compilation of essential open-source geospatial information layers that are crucial for assessing women's development, employment, and business prospects within the Renewable Energy (RE) sector. A thorough research was conducted for 59 data layers within each country, organized into 12 thematic categories. The table below presents the 59 layers identified during the desk research,  grouped into 12 categories, as outlined below
 
 <br>
 
-This effort resulted in a Data Gap Analysis Report for each of the 31 SIDS included in the project. The report for each country provides a comprehensive overview of the findings derived from an extensive data gap analysis, specifically centered on women in SIDS and their access (or lack thereof) to employment opportunities within the RE sector. This endeavor entailed thorough desk-based research, necessitating a detailed exploration of both spatial and non-spatial data sources that are publicly available. The focus was on identifying critical open sources, evaluating the resolution and quality of the data, and specifying any pertinent gaps or missing information in each country. The reports are available here: https://datacatalog.worldbank.org/search/collections/genderspatial
+This effort resulted in a Data Gap Analysis Report for each of the 31 SIDS included in the project. The report for each country provides a comprehensive overview of the findings derived from an extensive data gap analysis, specifically centered on women in SIDS and their access (or lack thereof) to employment opportunities within the RE sector. This endeavor entailed thorough desk-based research, necessitating a detailed exploration of both spatial and non-spatial data sources that are publicly available. The focus was on identifying critical open sources, evaluating the resolution and quality of the data, and specifying any pertinent gaps or missing information in each country. The reports are available here: <https://datacatalog.worldbank.org/search/collections/genderspatial>
 
 <font size="2">
 
 | **Reference Data** |
 | --- |
-| Administrative boundaries | 
+| Administrative boundaries |
 | Location and outline of cities/villages |
 | Building footprints |  
 | **Demographics and Population** |
 | Population Density |  
 | Level of Education |  
-| Age | 
-| Wealth Index | 
+| Age |
+| Wealth Index |
 | Female-Headed Households |  
 | Average Number of Children |  
 | Adolescent Fertility Rate |  
-| Share of Female University Graduates, STEM | 
+| Share of Female University Graduates, STEM |
 | Tertiary -Post Secondary- Education Attainment |  
-| Secondary Education Attainment | 
+| Secondary Education Attainment |
 | Agency of Women: Sexual Relations, Contraception, Reproductive Care |  
 | **Renewable Energy** |
-| Existing RE: Solar Plants | 
-| Potential RE Project Sites: Solar | 
-| Potential RE Project Sites: Wind | 
-| Potential RE Project Sites: Wind Offshore | 
+| Existing RE: Solar Plants |
+| Potential RE Project Sites: Solar |
+| Potential RE Project Sites: Wind |
+| Potential RE Project Sites: Wind Offshore |
 | **Energy Access** |
 | Location of Power Plants |  
 | Location of Stations and Substations |  
 | Grid Network: Transmission + Distribution |  
-| Prevalence of Energy Source | 
+| Prevalence of Energy Source |
 | Measure of Visible Light at Nighttime |  
 | Electrification Rates |  
 | Access to Electricity/Community |  
@@ -84,27 +87,27 @@ This effort resulted in a Data Gap Analysis Report for each of the 31 SIDS inclu
 | Location Universities |  
 | Location Technical Schools |  
 | **Jobs and Finance** |
-| Financial Facilities | 
+| Financial Facilities |
 | Labor in Industry Sector, Gender-Disaggregated |  
-| % Female Managers/Entrepreneurship | 
-| % Women in Middle/High Management Positions | 
-| Economic Participation and Opportunities Gap Score | 
-| Unpaid Domestic Work (% of day) | 
+| % Female Managers/Entrepreneurship |
+| % Women in Middle/High Management Positions |
+| Economic Participation and Opportunities Gap Score |
+| Unpaid Domestic Work (% of day) |
 | **Digital Inclusion** |
 | Access to Broadband Rates |  
 | Digital Literacy Rates |  
 | **Transportation** |
-| Road Network | 
+| Road Network |
 | Public Transportation Networks |  
 | Public Transportation Stops |  
-| Ports | 
-| Airports | 
-| Mobility Dataset | 
+| Ports |
+| Airports |
+| Mobility Dataset |
 | Commuting Zones |
 | **Safety** |
-| Crime Incidence: Serious Assaults | 
-| Crime Incidence: Sexual Violence | 
-| Prevalence of Domestic Violence | 
+| Crime Incidence: Serious Assaults |
+| Crime Incidence: Sexual Violence |
+| Prevalence of Domestic Violence |
 | Trust in the Police |  
 | **Amenities** |
 | Location of Hospitals |  
@@ -114,30 +117,32 @@ This effort resulted in a Data Gap Analysis Report for each of the 31 SIDS inclu
 | **Climate/Earth (5 datasets, four in GDB)** |
 | Average Rainfall |  
 | Coastal Flood Risk |  
-| Vegetation Areas | 
-| Waterways | 
+| Vegetation Areas |
+| Waterways |
 | **Law/Policy/Government** |
-| Sexual and Reproductive Health and Rights (% developed) | 
-| Length of Paid Maternity Leave (days) | 
-| Legislation Against Domestic Violence | 
-| Non-Discrimination Employment Legislation: Gender-Based | 
+| Sexual and Reproductive Health and Rights (% developed) |
+| Length of Paid Maternity Leave (days) |
+| Legislation Against Domestic Violence |
+| Non-Discrimination Employment Legislation: Gender-Based |
 | Legislation Against Sexual Harassment in Employment |  
-| National Parliament Seats Held by Women (%) | 
-| Missing Data from SDGs | 
+| National Parliament Seats Held by Women (%) |
+| Missing Data from SDGs |
 
 </font>
 
 The following figure summarizes the data availability concerning the 59 datasets examined for each country:
 
-
 :::{figure-md} markdown-fig
 <img src="docs/images/img03.png" alt="Proportion of data availability for the 59 datasets, by country">
 
-Proportion of data availability for the 59 datasets, by country 
+Proportion of data availability for the 59 datasets, by country
 :::
 
-### 2. Geospatial Databases
-In parallel with the Gender Data Gap Assessment, a comprehensive geospatial database was compiled for each of the 31 Small Island Developing States (SIDS) Targeted in the project.  The repository containing the geospatial databases can be found in the following link: https://datacatalog.worldbank.org/search/collections/genderspatial
+(geospatial-databases)=
+
+## 2. Geospatial Databases
+
+In parallel with the Gender Data Gap Assessment, a comprehensive geospatial database was compiled for each of the 31 Small Island Developing States (SIDS) Targeted in the project.  The repository containing the geospatial databases can be found in the following link: <https://datacatalog.worldbank.org/search/collections/genderspatial>
 
 Examples of data layers present in the GDB for select countries:
 
@@ -147,12 +152,18 @@ Examples of data layers present in the GDB for select countries:
 
 ![image](docs/images/img06.jpg)
 
-### 3. Novel Analytical Framework
-An extensive literature review, focusing on the barriers women face in securing jobs, particularly within SIDS, was conducted. This comprehensive review resulted in the formulation of a Multicriteria Evaluation (MCE) framework comprising 23 key factors, both spatial and non-spatial, that affect women’s job opportunities, categorized into four dimensions: Individual, Contextual, Accessibility, and Place Characterization. The latter two dimensions concentrate on geographical factors. For a comprehensive understanding of the Analytical Framework and the associated methodology employed to evaluate women's spatial access to employment opportunities, please refer to the Methodology Report available at the following link: https://documents.worldbank.org/en/publication/documents-reports/documentdetail/099121123091527675/p1792120dc820d04409928040a279022b42
+(novel-analytical-framework)=
+
+## 3. Novel Analytical Framework
+
+An extensive literature review, focusing on the barriers women face in securing jobs, particularly within SIDS, was conducted. This comprehensive review resulted in the formulation of a Multicriteria Evaluation (MCE) framework comprising 23 key factors, both spatial and non-spatial, that affect women’s job opportunities, categorized into four dimensions: Individual, Contextual, Accessibility, and Place Characterization. The latter two dimensions concentrate on geographical factors. For a comprehensive understanding of the Analytical Framework and the associated methodology employed to evaluate women's spatial access to employment opportunities, please refer to the Methodology Report available at the following link: <https://documents.worldbank.org/en/publication/documents-reports/documentdetail/099121123091527675/p1792120dc820d04409928040a279022b42>
 
 ![image](docs/images/img07.png)
 
-### 4. Gender Enabling Environments Tool (GEEST)
+(gender-enabling-environments-tool-geest)=
+
+## 4. Gender Enabling Environments Tool (GEEST)
+
 Based on the Methodological Framework, the GEEST, an open-source plugin in QGIS, was developed for the automatic computation of the factors and dimensions. The GEEST characterizes communities based on women's prospects to secure jobs or establish their own businesses within the RE sector. It aims to assist decision-makers in selecting optimal locations for RE projects, ensuring the maximum positive impact on communities and addressing gender disparities. Additionally, it provides insights for building the necessary infrastructure around RE projects to create enabling environments that enhance women's participation in the RE sector in SIDS.
 
 The table below outlines the dimensions, factors, and recommended indicators for computing the GEEST, derived from the Methodological Framework:
@@ -165,7 +176,7 @@ Dimensions, Factors and indicators included in the Analytical Framework
 
 The GEEST generates raw score outputs for 21 of the 23 factors outlined in the Analytical Framework. The factors (i) Water and Sanitation and (ii) Fragility, Conflict, and Violence are absent due to lack of data availability. Each of the 21 factors, dimensions, and overall aggregate scores are assessed on a scale ranging from 0 to 5.
 
-The interpretation of these scores is thoroughly detailed in the Methodology Report: https://documents.worldbank.org/en/publication/documents-reports/documentdetail/099121123091527675/p1792120dc820d04409928040a279022b42. Higher scores signify a more conducive environment for women to access job opportunities. Conversely, scores of 0 indicate a lack of supportive conditions for women to access employment opportunities. To enhance comprehension, the methodology further categorizes these scores into distinct 'classes,' offering a simplified approach to their interpretation, as shown in the following table:
+The interpretation of these scores is thoroughly detailed in the Methodology Report: <https://documents.worldbank.org/en/publication/documents-reports/documentdetail/099121123091527675/p1792120dc820d04409928040a279022b42>. Higher scores signify a more conducive environment for women to access job opportunities. Conversely, scores of 0 indicate a lack of supportive conditions for women to access employment opportunities. To enhance comprehension, the methodology further categorizes these scores into distinct 'classes,' offering a simplified approach to their interpretation, as shown in the following table:
 
 ```{list-table} Proposed discrete score classes to enable simpler visual interpretation of raw score outputs and enable intersection with other layers of information (reproduced from the Methodology Report).
 :header-rows: 1
@@ -194,9 +205,11 @@ The interpretation of these scores is thoroughly detailed in the Methodology Rep
    - Highly enabling
 ```
 
-To access the User Manual for GEEST and the necessary installation files for QGIS, please visit the GitHub repository via the following link: https://github.com/worldbank/GEEST.
+To access the User Manual for GEEST and the necessary installation files for QGIS, please visit the [User Guide](docs/user_guide.md) or the [GitHub repository](https://github.com/worldbank/GEEST).
 
-### 5. Implementation
+(implementation)=
+
+## 5. Implementation
 
 The GEEST was tested in three pilot countries – Comoros, Dominican Republic, and Papua New Guinea (PNG) – to assess its functionality. The selection of these countries was strategic, considering their varied geographic regions, income levels, sizes, population densities, and data availability. Testing the GEEST across such a broad range of conditions ensured that its usefulness, applicability, and functionality in different contexts could be accurately tested. The findings and insights derived from the GEEST implementation are documented in the Implementation Report, accessible through the following link: [insert link].
 
@@ -214,7 +227,7 @@ The Contextual dimension encompasses factors that provide information concerning
 
 #### ACCESIBILITY DIMENSION RESULTS IN PILOT COUNTRIES
 
-The Accessibility dimension includes factors that relate to the ease with which women can reach specific services or destinations and are often determined by proximity. These factors affect the day-	to-day mobility of women. Accessibility factors found to be most relevant to women in SIDS include 	(i) women's travel patterns, (ii) access to public transport, (iii) access to education facilities, (iv) access to RE jobs, (v) access to health facilities, and (vi) access to financial facilities.
+The Accessibility dimension includes factors that relate to the ease with which women can reach specific services or destinations and are often determined by proximity. These factors affect the day- to-day mobility of women. Accessibility factors found to be most relevant to women in SIDS include  (i) women's travel patterns, (ii) access to public transport, (iii) access to education facilities, (iv) access to RE jobs, (v) access to health facilities, and (vi) access to financial facilities.
 
 ![image](docs/images/img11.png)
 
@@ -268,7 +281,9 @@ Likewise, the GEEST has the capability to aggregate results solely within the ad
 Aggregate results concerning enabling environments near RE sites with respect to women’s population for the DR
 :::
 
-### 6. GEEST Main Limitations
+(geest-main-limitations)=
+
+## 6. GEEST Main Limitations
 
 #### Data Availability and Granularity