Overview
Data is essential to achieving the goals expressed by advocates and policymakers around International Women’s Day. Yet we are still grappling to collect and use data that highlights the unique experiences of women and girls, reveals barriers to gender equality, and illustrates what works to improve the lives of women and girls. This lack of data not only restricts effective programming but masks and at times even perpetuates gender inequalities. (GWPIS, 2023)
We know that environmental change has differentiated impacts on different genders, and there is increasing evidence that women, girls, and other marginalized communities disproportionately suffer from climate change and environmental disasters. We also know that women and girls have unique solutions for adapting to changing environmental conditions and moving toward sustainability. Existing data and methodologies fail to reflect this reality. (GEDA, 2023)
Key Questions
- What is gender data? How can we collect it?
- Why is gender data essential for changing the lives of women and LGBTIQ+ individuals, and how can it help leaders create policies to address gender disparities?
- What are gender statistics and indicators? What can we do with them?
- How does the underrepresentation of women and diverse voices in the data production and technology sector contribute to the gender data gap?
- How does intersectionality relate to assessing the success of initiatives in targeting and benefiting diverse gender identities?
- What steps should be taken to build better gender data?
What is Gender Data?
Gender data is any type of data that can at least be disaggregated by male/female. This term began to gain more currency as it was included by the UN in several recommendations. In fact, the most exhaustive and referenced definition that currently exists is the UN’s gender statistics, which contains gender data.
Gender Statistics and Indicators
Gender statistics are defined by the UN as the sum of the following characteristics:
Sex-Disaggregated Data | Gender-Inclusive Data | Diverse and Comprehensive Data | Gender-Balanced Data Collection |
---|---|---|---|
Data are collected and presented by sex* as a primary and overall classification | Data reflect gender issues | Data are based on concepts and definitions that adequately reflect the diversity of women and men and capture all aspects of their lives | Data collection methods take into account stereotypes and social and cultural factors that may induce gender bias in the data |
Sources
-
Georgetown Institute for Women, Peace and Security. (n.d.). The Need for Gender Data. Retrieved from https://giwps.georgetown.edu/the-need-for-gender-data
-
Data2X. (n.d.). What is Gender Data? Retrieved from https://data2x.org/what-is-gender-data
-
Gender and Environment. (n.d.). Gender and Environment Data Platform. Retrieved from https://genderenvironmentdata.org
-
UN Women. (n.d.). Data. Retrieved from https://wrd.unwomen.org/practice/topics/data
-
Onuoha, M. (n.d.). The Library of Missing Datasets. Retrieved from https://mimionuoha.com/the-library-of-missing-datasets
-
D’ignazio, C., & Klein, L. F. (2023). Data feminism. MIT press.
-
Perez, C. C. (2019). Invisible women: Data bias in a world designed for men. Abrams.
-
Rahman, A. (2020). Algorithms of oppression: How search engines reinforce racism.
-
Beegle, K., Serajuddin, U., Stacy, B., & Wadhwa, D. (2023). Missing SDG Gender Indicators.
-
Ruberg, B., & Ruelos, S. (2020). Data for queer lives: How LGBTQ gender and sexuality identities challenge norms of demographics. Big Data & Society, 7(1), 2053951720933286.