Mapping Gender Data in the SDG Era

Kathleen Grantham March 05, 2020

Gender equality is multi-dimensional. That women and girls experience overlapping deprivations in health, education, economic opportunities, and more are generally understood by those working in global development advocacy and programming.

Yet when it comes to gender data, we often continue to talk about these interrelated aspects of women’s and girl’s lives as if they are siloed from one another.

Data2X’s new report, Mapping Gender Data Gaps: An SDG Era Update, released today, highlights gender data gaps across six key domains of women’s empowerment: (1) health, (2) education, (3) economic opportunities, (4) public participation, (5) human security, and (6) environment. It emphasizes the fact that in order to fill gender data gaps are to be filled, we need investment across all parts of the data collection system.

Mapping Gender Data Gaps in 2014 versus Today

This new report builds on Data2X’s 2014 mapping exercise, which provided a roadmap for actors working to address the challenge of missing and incomplete data on women and girls, and where to focus critical resources and investment. While this work remains relevant and foundational in many respects, so much has changed in the gender data landscape since 2014. For starters, the international development agenda shifted during this period from the Millennium Development Goals (MDGs) to the Sustainable Development Goals (SDGs) and brought with it a renewed focus and commitment to tracking data across different areas of development, as well as increased demand for disaggregated and nuanced data.

International attention has also shifted in the past five years to address issues that previously weren’t on our radar in the same way. In 2014, there wasn’t a global recognition that gender equality and the environment are profoundly interlinked, or that women are disproportionately impacted by environmental issues like climate change and food security.

This is a relatively recent shift and as a result, there is still very little sex-disaggregation or gender analysis of most environmental data, just as the environment continues to be on the periphery of much gender equality work. To bring attention to the severity of gender data gaps in this area, and to the nascent field studying the interplay of environmental issues and gender equality, the environment is included as a domain for the first time in this new report.

But despite increased attention to a greater number of gender issues under the SDGs, and the best efforts of custodian agencies, civil society, and expert groups to achieve “gender data equality,” we know that many of the data gaps identified in the original exercise remain, new ones have emerged, and there is still much work to be done to make women’s and girls’ lives visible in data systems and in policymaking.

This new report takes strides toward creating this visibility by outlining how much progress has been made since 2014, where major gaps remain, what are the sources of gender data available, and what are the key efforts underway to improve gender data across different domains of women’s empowerment.

Mapping the Status of Gender Data Gaps

To update the original exercise and map the status of gender data gaps in 2019, we reviewed relevant research, scholarship, and other online materials to identify what progress has been made in the past five years to close gender data gaps. We also had the opportunity to interview around twenty gender experts working across civil society, academia, research institutes, think tanks, and standard-setting agencies to identify emerging gender data gaps, and the key actors and initiatives working to resolve them. The resulting list of gender data gaps in the report is not exhaustive—it represents the views of individuals and organizations working and advocating in this field on the most pressing gender data gaps in 2019 and in relation to the SDG monitoring framework in particular.

The research process highlighted the interlinked nature of different topics and the challenge of classifying data gaps within one domain or another. For example, gender data gaps on women’s safety in public spaces and on transit is a matter of human security, but it also has implications for women’s economic opportunities and public participation. Similarly, gender data gaps on women’s health—such as women’s and girls’ unmet needs for menstrual hygiene management —can affect their ability to obtain an education, work, and feel safe within their communities.

The research process also emphasized how data systems are complex and that there is no one data source that can provide insight into every facet of gendered experience. For instance, censuses and sample surveys provide crucial snapshots of population wellbeing and progress, while quality administrative data—including from civil registration and vital statistics (CRSVS) systems—contributes essential sub-national and dynamic information on basic topics such as births and deaths, school enrolment and immunization. Big data sources are also increasingly being used to provide granular information about women’s and girls’ lives, even in the most remote and isolated places.

Barriers to Filling Gender Data Gaps Across the Entire Global Development Agenda

The source and nature of gender data gaps across domains vary and because of this the barriers to closing gender data gaps also vary. In some areas, such as the environment, appropriate measures are still being conceptualized. In others where the approach to collecting gender data is agreed and established, gaps can arise because of a lack of prioritization, resources, or capacity for gender data collection.

Across domains, a common theme is that basic sex-disaggregation remains an issue, and data that has multiple disaggregations—to account for differences based on income, age, race, ethnicity, location (urban/rural), indigenous status, migration status, and disability—is relatively non-existent because of how challenging and resource-intensive this data is to collect. Yet this type of intersectional analysis is crucial to ensure that the world delivers on its commitments under the SDGs.

There’s no getting around the fact that greater investment needs to be made across all parts of the data collection system. Investment in gender data should target national statistics offices to first, demonstrate its value, and second, improve their capacity to both collect gender data and communicate it to decision-makers in an accessible and timely manner. The ultimate value of gender data is not in its production, but rather in its use.

But reinventing the wheel is not necessary in every case. Existing international databases often have data that could be disaggregated by sex or analyzed to address gender data gaps. These sources should be mined before investing in new data collection efforts. Similarly, existing data collection efforts (like household or enterprise surveys) should be revised where possible to include additional questions and expanded to a greater number of countries above advocating for entirely new collection efforts.

2020 is an important year for gender equality in the context of the 25th anniversary of the Beijing Declaration and Platform for Action. Yet the lack of gender data persists as both a cause and consequence of gender inequality. Filling gender data gaps with regularly collected, high-quality data on women and girls is crucial to make progress across the global development agenda —in 2020 and beyond.

Kate Grantham is an international development researcher and consultant specializing in feminist approaches.

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