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Home»Data»Can geospatial data help close the gender employment gap? Yes, it can!
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Can geospatial data help close the gender employment gap? Yes, it can!

5gantennas.orgBy 5gantennas.orgFebruary 8, 2024No Comments5 Mins Read
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Blog series on spatial insights into the gender employment gap

In recent decades, a confluence of factors has led to a global push for women’s economic empowerment, creating more opportunities for women and girls around the world. Despite significant improvements in social attitudes and policies in many countries, some opportunities remain difficult to achieve in certain sectors and regions. why?

Let’s consider the following case Maria, high school students living in Small Island Developing States (SIDS). Passionate about making a meaningful impact, Maria aims to pursue a STEM degree and contribute to the renewable energy (RE) field. Despite ample opportunities for women in this sector and efforts by renewable energy companies in the country to promote gender equality, Maria faces formidable barriers. First, no local university offers a STEM program, and that’s not the only challenge.

What hidden hurdles will stand in the way of Maria landing her dream job in the remanufacturing sector?

4th dimension perspective

Unraveling the complex factors affecting employment opportunities for women, a new World Bank report states:A methodological framework for the geospatial assessment of women’s employment and business opportunities in the renewable energy sector – Methodology Report” thoroughly investigates the key spatial and non-spatial aspects that influence women’s access to employment opportunities.

especially, This report introduces an innovative multi-criteria evaluation (MCE) framework that encompasses 23 key influencing factors that shape women’s occupational trajectories. These factors are categorized into four dimensions: personal, situational, accessibility, and place characterization, with the last two focusing on geographic (spatial) considerations. What are the main findings? Simply put, it’s not only about the women’s skills, but also where they live.

  • Individual factors This includes women’s unique personal characteristics across the spectrum of physical, psychological, and sociocultural factors. Aspects such as caregiving responsibilities, sexual orientation, exposure to domestic violence, and educational attainment complexly shape women’s experiences and perspectives. Take Maria, for example. As the eldest of her siblings, she is expected to devote some of her time to caring for her younger brothers. Adding to the complexity, Maria comes from a religious family that traditionally assigns women roles within the home and prevents them from pursuing employment outside the home. is. Moreover, Maria faces further challenges. She is deaf and requires the use of hearing aids.
  • contextual factors Provides a window into each country’s legal and policy framework. These factors have a major impact on issues such as gender discrimination in the workplace, women’s economic independence, and broader women’s empowerment. In Maria’s country, prevailing policies and regulations actively promote women’s economic empowerment, ensure fair treatment, and prohibit discrimination against women.
  • Dimensions of accessibility The focus is on women having easy access to services and destinations. These factors depend on proximity and influence women’s mobility. Maria must consider the remote location of her local RE company. The lack of public transport alternatives between Maria’s potential job and her home means she must travel several kilometers on foot, limiting her time for other important activities. means to be Additionally, even if Maria decides to start her own family, there are no childcare services near where she lives or potential employment opportunities, further complicating the balance between the two. Professional Pursuits and family life.
  • finally, Place characterizing elements Describe the attributes of a particular geographic location or environment. These factors do not include mobility considerations, but include aspects such as location security, fragility, and vulnerability to conflict, violence, and natural disasters. With public transport limited and unreliable, Maria has to consider walking several kilometers in poor lighting to reach a public transport stop. Women often complain of harassment while waiting for the bus. Additionally, the threat of flooding along these routes from rainfall and tropical storms adds an additional hurdle that could prevent Maria from traveling to work.

Quality data is most important

In Maria’s story, and the experiences of countless other women, we see how personal and situational factors, as well as geographic challenges, severely limit women’s ability to hold jobs. Masu. The need for a holistic approach to address the spatial aspects of gender disparities.

Many countries are taking steps to improve the status of women. These efforts range from advocating for legislation to address gender disparities and implementing health programs for children with disabilities to developing educational programs that emphasize the importance of girls’ education. These efforts played a pivotal role in motivating Maria to pursue a career in STEM. However, despite this progress, the needle has not moved significantly in many sectors and regions. This is primarily because geographic considerations have been largely overlooked.

The question arises: What does it take to integrate spatial analysis into equations? The answer is simple. More, higher quality spatial data.

Recent initiatives led by the World Bank “Geospatial assessment of women’s employment and business opportunities in the energy sector;” aimed to identify important spatial datasets related to women’s employment in SIDS, and the results highlighted critical gaps in data availability. Of the 59 gender-related datasets examined, on average only 63% were available, ranging from 86% in the Dominican Republic to 86% in the Dominican Republic. Cape Verde is 41% of Nauru.

Low availability of open spatial data means missed opportunities for informed policy making, scientific progress, and improved economic and social conditions. Accurate and reliable information helps governments design effective policies, allocate resources appropriately, and address pressing issues such as gender inequality in the face of climate change and economic uncertainty. It is extremely important to have up-to-date spatial data. A nuanced understanding of the challenges women face in securing employment therefore requires a solid foundation of comprehensive spatial data.

reliable, Leveraging up-to-date spatial data for analysis will be paramount, allowing us to paint a complete and accurate picture of the barriers women pass through when pursuing employment opportunities.


Related books:”A methodological framework for the geospatial assessment of women’s employment and business opportunities in the renewable energy sector – Methodology report”



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