It’s time to zero in on the gender gap in livestock data

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Vanessa Meadu
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On International Women’s Day we call for gender equality in livestock data, and outline key actions to close the gap

By Vanessa Meadu and Isla MacVicar, SEBI

Livestock farming offer a ‘pathway out of poverty’ for hundreds of millions of people in low and middle-income countries, but the lack of data about this sector is preventing governments and funders from making evidence-based policies and investments, explained Bill Gates at an event in Edinburgh in 2018. This livestock data gap is slowly narrowing, thanks in part to initiatives supported by the Bill and Melinda Gates Foundation (BMGF), but an enormous chasm still exists for data around women in livestock. This missing data around women in livestock is hindering essential progress.

Missing gender data is everybody’s problem

Insufficient data about women and livestock is a problem for everybody. Without the right data about the different roles played by men and women in the livestock sector, and the power dynamics that shape and sustain these roles, there is a risk that livestock interventions fail or even make things worse for women.

If a livestock initiative is “gender blind”, that is, ignoring any gender considerations, it risks further exclusion of women, reinforcing harmful inequalities, and potentially failing. The Interagency Gender Working Group (IGWG) calls for initiatives to become more gender aware, and at least acknowledge and work around gender differences. The ultimate goal, however,  is to “transform gender relations to promote equality and achieve project objectives” (source).

To achieve this in the livestock sector, we need a much better understanding of current gender dynamics and women’s empowerment, and for that we need data.

If you work with data on gender and livestock we want to hear from you! Leave your comments at the end of this post.

Understanding the limitations of our knowledge

The best available data on rural livelihoods do not distinguish livestock-related activities from other (usually crop-based) agricultural practices. A number of major surveys track changes over time in the agricultural sector, for example the World Bank’s Living Standards Measurement Study (LSMS). This socioeconomic survey has generated plenty of data about women’s activities, but does not include specific information about women and livestock.

Some funders have recognised the need to measure gender in livestock development. In 2016, the BMGF set up SEBI (Supporting Evidence Based Interventions) to help close livestock data gaps. The Foundation recently asked us to help measure and track gender impacts of their livestock development projects as one of ten key performance indicators. They want to know whether their portfolio of livestock investments is helping to increase in women’s control of livestock assets and/or income from livestock.

As a first step to answering this question, SEBI researchers are digging into the knowledge base for gender and livestock by undertaking a systematic scoping study of existing scholarly literature. We are trying to understand what kind of livestock and gender indicators and data are already out there for target countries in Africa and South Asia. The search has so far uncovered a fair number of studies on women’s empowerment in crop production and nutrition, but we have found that these do not usually hold enough conclusive or numerical data to provide an accurate representation of women’s empowerment and livestock in the target countries.

This research is systematically revealing the huge evidence gap for women’s empowerment and the livestock sector, and an even greater gap in terms of quantitative data on this topic.


In short, we don’t know almost anything about women’s empowerment in the livestock sector. Though frustrating, “knowing what you don’t know” is an important first step towards an eventual solution.


Who is working on solutions?

Research and development organisations have already identified the gender data gap in agriculture and made important progress towards closing it. A notable development is the Women’s Empowerment in Agriculture Index (or WEAI), the first-ever measure to directly capture women’s empowerment and inclusion levels in the production of crops and livestock. Developed by USAID, the International Food Policy Research Institute, and the Oxford Poverty and Human Development Initiative, this innovative tool tracks women’s engagement in agriculture. While WEAI may broadly help inform the design and implementation of gender-transformative livestock interventions, only about 30 percent of the questions relate to livestock.

Responding to the need for a livestock-specific tool for measuring women’s empowerment, the Women’s Empowerment in Livestock Index (WELI) was developed by the International Livestock Research Institute (ILRI) in collaboration with Emory University in 2015, with funding from USAID and Irish Aid.

“Quantifying a phenomenon allows scientists to measure its changes over time,” said WELI co-author Alessandra Galiè in a 2019 interview. “An index provides a common framework or reference point to determine the effectiveness of various interventions. […] The challenge we are still facing, however, is to develop a methodology that measures empowerment while taking into account the complexity of empowerment processes,” she explained. WELI measures women’s empowerment across six dimensions related to decision-making and access to and control over resources in livestock production.

Gender data “essential” for project success

As funders put more emphasis on gender tracking, projects are changing how they collect data on the ground. One organisation that has recognised the power of tracking gender data is Land O’Lakes Venture 37. They collect gender-disaggregated data as part of their dairy and livestock development projects in low and middle-income countries and see this as central element of achieving local, scalable and long-lasting solutions.

SEBI is working closely with them to help track the performance of BMGF-funded livestock initiatives, looking at indicators such as the increase in women’s ownership of improved cattle breeds and the number of women farmers and technicians trained in better management practices. “Gender inclusion is essential to our projects,” explains David Harvey, Program Director with Land O’Lakes Venture37. “The success of our projects depends on improving the lives of both women and men. Excluding women is bad for business, and bad for society. We track gender impacts so we can continually do better,” he said.

What needs to happen next?

While there are promising data collection tools such as WELI and organisations like Land O’Lakes Venture37 are using data to transform gender equality in the livestock sector, a great deal more needs to be done to close the gender gap in livestock data.

Project funders can promote the need for livestock projects to collect gender-disaggregated data and report on key gender indicators for example using WELI. They could require that projects track performance in terms of gender equality and empowerment as part of tracking the project’s impact.

National governments can work to systematically collect livestock-specific census data, and ensure that this data is gender-disaggregated. This could help them track progress towards achieving the Sustainable Development Goals, and be part of attracting more funding and investment in the livestock sector.

Livestock development project implementers can start thinking in terms of collecting gender disaggregated data, and look at it as a benefit to the project’s bottom line, and as crucial for ultimate impact.

Now is the time to tackle the livestock gender data gap. To achieve the Sustainable Development Goals by 2030, we need evidence-based actions and investments that benefit rural people around the world, in the livestock sector and beyond.


The authors are staff members of Supporting Evidence Based Interventions, based at the University of Edinburgh’s Royal (Dick) School of Veterinary Studies. SEBI facilitates the Livestock Data for Decisions (LD4D) community of practice.

Header photo: A Peterson, Land O’Lakes Venture37 (link to source)

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