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.
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Countries included in the project:
@@ -728,47 +728,47 @@The Contextual dimension encompasses factors that provide information concerning the laws and policies in place, influencing workplace gender discrimination, financial autonomy, and overall gender empowerment.
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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 health facilities, (v) access to financial facilities.
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Accessibility factors
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Accessibility factors aggregated
The Place-Characterization dimension contains factors that refer to attributes that are used to define a specific geographical location or environment and do not include a mobility component. Those deemed to be most important place-characterization factors concerning women’s access to jobs include (i) walkability, (ii) safety, (iii) digital inclusion, (iv) environmental hazards, (v) education , (vi) fragility, conflict, and violence, and (vii) water sanitation.
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Place characterization factors
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Place characterization factors aggregated
Below are some of the overall insights derived from the GEEST for Saint Lucia. The first map illustrates the degree of enablement within environments; the second map shows the level of enablement concerning the female population on a raster 100x100m format. The third map shows the results for the level of enablement concerning female population, aggregated at the administrative subdivisions of the island.
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Raster results concerning enabling environments for Saint Lucia
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Raster results concerning enabling environments with respect to women’s population for Saint Lucia
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Aggregate results concerning enabling environments with respect to women’s population for Saint Lucia at administrative subdivision level
If the job opportunities’ location layer is presented in raster format, the GEEST can generate scores specifically for the regions where employment prospects exist, emphasizing opportunities exclusively within those areas.
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Raster results concerning enabling environments in RE sites with respect to women’s population for Saint Lucia
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Accessibility factors
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Accessibility factors aggregated
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Place characterization factors
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Place characterization factors aggregated
@@ -244,7 +244,7 @@ Below are some of the overall insights derived from the GEEST for Saint Lucia. T
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