We Need More Women in Data!
As Nepal passes the one-year anniversary of its Covid-19 lockdown, we finally have the data to confirm what we witnessed over the past 12 months: tragic loss of life, economic disruption, and wide-ranging social dislocation. We knew that women were being affected differently than men; that they faced the double burden of job and household; that they, the heart of the informal economy, were first to lose their jobs. Now, a report by The Asia Foundation lets us put numbers to the hardships of women during this difficult year, and to consider how valuable it is to have data on women, and to have women working on that data.
The study, Covid-19 and the New Normal for Women in the Economy in South Asia, includes individual country reports on Bangladesh, India, Nepal, and Pakistan that shed light on the economic and social repercussions of the pandemic, particularly for women. The report makes two important things clear. First, there is a story to tell about the foundational role that women have already played in Nepal’s confrontation with the coronavirus. This role has been largely invisible, but no longer. Second, until we see women explicitly reflected in our pandemic data, that data will be incomplete. The new report’s evidence of different effects on women and men gives a more accurate picture of reality, one that policymakers, community leaders, and women themselves can use to make decisions that will shape Nepal’s recovery from the Covid-19 recession.
Until now, none of us had this data to verify our assumptions. This created a gender data gap that hindered government recovery efforts. Without this vital information on gendered impacts, relief efforts were ineffective and unaccountable. In Nepal, 65% of women respondents were aware of official relief services, but only 31% said they had received support. For women in business, the lack of information on eligibility and application criteria became an obstacle to effective relief. Targeted policies like subsidized or collateral-free loans for women, included in the 50-billion-rupee refinancing fund in the government’s latest budget, haven’t taken off.
Information like this certainly contributes to a better understanding of women in the pandemic economy, but The Asia Foundation also believes that we need more women participating in the data and technology sector to fully appreciate women’s contributions to the economy, governance, and social life and the effects that policies have on them. This March 20, champions of women in data in Nepal came together for the second Women in Data conference. The virtual conference drew women from academia, civil society, and the private sector to discuss this year’s theme, “Leveraging the Power of Women, Data, and Technology.” The conference featured two panel discussions with women prominent in Nepal’s expanding data and tech sectors, and a presentation covering the state of science, technology, engineering, and math (STEM) for females in Nepal. One of the key points of discussion over the course of the afternoon was how to encourage girls and women to stay engaged with data and technology.
The labor force participation rate of women in Nepal is stunningly high, but the proportion of these women who have careers in data and tech is very small. According to Nepal’s 2017–18 Labor Force Survey, 81% of the female population over 15 years old is economically active, but just 0.5% of these women and girls work in the ICT sector. Apart from ICT, UNESCO estimates that just 7.8% of researchers of all kinds in Nepal are female. While this gap between male and female participation in data, technology, or STEM in general is not unique to Nepal, the reasons for women’s underrepresentation in these sectors are social and cultural.
“We see no difference between boys and girls in their abilities in the classroom,” said panelist Jyoti U. Devkota, based on her years as a professor of mathematics at Kathmandu University. She and panelists agreed that when it comes to learning math and engaging with data, there are no inherent differences between boys and girls, but social and cultural pressures, she argued, push girls out of STEM and into other fields. Panelists offered a long list of social factors that affect the chances a girl will stay with STEM and forge a career in data or technology. Whether it’s being the only girl in a senior seminar, being the female professor who has to publish more than the men to get ahead, being an aspiring engineer who is told her career is unsafe for women, or just the pervasive cultural emphasis on marriage and childrearing and how this interrupts a woman’s career, women certainly are not welcomed into STEM fields in Nepal.
Math and science are equally important for girls and boys because they teach important analytical thinking skills. Their young minds should be exposed early to STEM toys and learning toolkits to help them develop the foundation of a scientific approach: try, fail, learn, and try again to achieve one’s goals. Most importantly, they will develop the confidence to hypothesize and experiment by themselves, and the self-assurance that they can excel in technical careers.
Panelists and speakers at the conference also offered a number of recommendations to encourage girls and women to get involved in data and STEM:
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- Girls need female mentors and role models. Seeing a woman leading work in data or technology makes that role seem attainable to girls. Each panelist noted several mentors and role models who had guided them, and they are themselves role models: one panelist, Sumana Shrestha from Kosi Collaborative, has employed all female coders in her business.
- Consider all types of girls. Like any other group of people, girls come from a variety of backgrounds, and there is no one-size-fits-all approach to bringing girls into STEM and keeping them there. Girls in urban settings have access to resources (the internet, television, technical schools) that girls in rural settings may not. Making STEM available to all types of girls should be at the forefront of a strategy to increase their representation in STEM.
- Push girls to persevere and succeed at math. It’s not just the arithmetic but the concepts and logic that math teaches girls and boys that set them up to succeed in STEM fields. Starting from a young age, and particularly through eighth and ninth grades, encourage girls to stay in STEM.
- Among the STEM subjects, math is affordable for most families. No lab equipment is required for math, even at the upper levels. Girls can use pencil and paper.
- It’s never too late to become a woman in data and a data enthusiast. Just because you didn’t study math doesn’t mean there’s no place for you in data or STEM. Women of all backgrounds can work on data-driven initiatives or support women in STEM with programs, jobs, or fellowships. Panelist Jamie Holton has a social science background but supports data-driven research in her position as the project management and research officer at Publish What You Fund.
The Women in Data Conference is one of The Asia Foundation’s flagship activities in its Data for Development (D4D) program, funded by UKAid and implemented in partnership with Development Initiatives. In its second phase (2020–2024), the D4D program has assembled a Women in Data Steering Committee, comprising representatives from four important partner organizations: Women Leaders in Technology, Girls in Tech Nepal, Women in STEM, and Open Knowledge Nepal. The steering committee focuses on bringing more women into the data and tech sectors by identifying and removing the barriers to entry. It provides guidance on ways to ensure women’s participation in D4D’s work to encourage evidence-based policymaking in Nepal.
Ashray B. Pande is a senior program officer and Carolyn O’Donnell is the MERL director for The Asia Foundation in Nepal. Binita Shrestha is an IT engineer and managing director of Women in STEM. They can be reached at as[email protected], [email protected], and [email protected], respectively. The views and opinions expressed here are those of the authors, not those of The Asia Foundation.
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