Data is not the solution to the problem but without the right data, without giving visibility to the “missing data”, it is impossible to understand and to think about solutions.
It might seem to be common sense but it is important to understand who and what is counted when we are counting. The processes by which data are generated, classified and eventually used matters. Something as simple as opening a bank account might be impossible for the estimated 9 to 12 million gender non-binary people in the world to complete if the application form requires the user to “select gender”. Thus, without the right categories, the right data can’t be collected.
To offer an example of our work at ILDA,1 we are exploring Gender-related violence against women and its lethal outcome, feminicide, a serious problem in Latin America and the Caribbean, as they are in the rest of the world. Although most governments in the region have passed legislation criminalising feminicide (18 countries in the region), these laws have not been accompanied by relevant policy nor by robust data collection that measures the scope and scale of the problem. In this sense, feminicide data is “missing data”: data that have been neglected and whose missingness hinders progress towards ending violence against women.
When thinking about data on feminicide,2 there are a myriad of aspects that characterize these events. If we don’t consider these challenges in gathering data, we might be omitting certain crimes from the registries and, therefore, neglecting to consider those victims when designing and implementing policies and other measures. Feminicide data is “missing data”: data that have been neglected and whose missingness hinders progress towards ending violence against women.
Where official accounts of feminicide are non-existent or inadequate, activists, civil society organizations, and journalists have stepped in, attempting to fill in the gaps by compiling incidents of feminicide from news reports and publishing the results in databases, maps, and other forms of data visualisation, making feminicide visible through data. In parallel, the advent of new legislation and regional initiatives to standardise governments’ feminicide data, has prompted public officials across the region to review and improve their data practices around this issue.
Data Feminism in Action
Given that context, in 2020, ILDA together with Data+Feminism Lab (MIT)3 and FeminicidioUY4 organized “Data Against Feminicide”5 a month long series of interactive sessions In the context of the International Day for the Eradication of Violence against Women welcoming feminist activists, civil society organizations, international organizations, data journalists, policymakers, government officials, or academics, whether they were already working with feminicide data or considering it.
We began with a series of research presentations on data and feminicide to set the scene.
Approaches to feminicide data: Data, Gender and Violence: data standardization of feminicide in LAC presented by Silvana Fumega and Hassel Fallas; The challenges of measuring, comparing, and standardizing 'global' fem(in)icide data with Saide Mobayed); and an analysis of Data Frames of Feminicide from Helena Suárez Val).
We moved on to working with feminicide data: Telling stories with data, about violence against women with Mariana Villamizar Rodríguez and Juliana Galvis Nieto / Datasketch); Automated Feminicide Detection a machine learning classifier - for Activists and Civil Society Organizations from Catherine D'Ignazio); Spatial Analysis of feminicides in the State of Mexico presented by Fernanda Gutiérrez Amaros.
A long road ahead
Data is not the solution to the problem but without the right data, without giving visibility to the “missing data”, it is impossible to understand and to think about solutions. Thus, visibility and community building is the way we believe best to go forward.
We are taking small steps that include standardization of data, algorithms to help mappers to improve their work, and conversations to build a community, to name a few and we think we are going in the right direction. If we keep working together there might be a day when our work is no longer necessary. We sincerely hope that day comes sooner than expected.
References
D’Ignazio, Catherine, and Lauren F. Klein. Data Feminism. MIT Press, 2020.
Fumega, Silvana. ‘Standardisation of Femicide Data Requires a Complex, Participatory Process, but Important Lessons Are Already Emerging | LSE Latin America and Caribbean’. LSE Latin America and Caribbean Blog (blog), 8 August 2019. https://blogs.lse.ac.uk/latamcaribbean/2019/08/08/standardisation-of-femicide-data-requires-a-complex-participatory-process-but-important-lessons-are-already-emerging/.
ILDA. ‘Femicide Data Standardization’. ILDA (blog). Accessed 24 May 2021. https://idatosabiertos.org/proyectos/estandardatosfemicidios/.