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Data and algorithms to measure and prevent Gender Based Violence in the UK: an inward-placement of Data Pop Alliance at the University of Surrey

Start date

January 2023

End date

March 2023


Gender-based Violence (GBV), any violent act, attempt, or threat that affects persons of a particular gender disproportionately, is one of the most pervasive forms of human rights violations affecting an estimated 30% of women worldwide. Public policy decisions taken on the basis of these data are biased and may not be properly resourced to meet demand for program design and impact evaluation of prevention and treatment services.

This ESRC IAA funded project aims to foster collaborations and knowledge exchange between the external partner and experts at the University of Surrey, to develop a novel data-driven framework to identify and analyse the causes of GBV.

The goal is to produce a toolkit for policy makers and advocates to mitigate GBV in the UK and worldwide and highlight the importance of understanding the multiple factors that enable (or hinder) reporting and thus prevention and response to GBV, by generating a novel comprehensive, and holistic data-driven framework to identify and analyse its underlying causes.



Short-term outcomes include:

  • Workshop to connect relevant actors and learn about the state of art of gender-based violence data in the UK and engage with interested actors on our mission to create a data-driven framework against GBV (28 March 2023)
  • Materials: draft of a holistic data-driven framework for comments and feedback during the in-ward placement

Longer term outcomes and future plans

  • Dissemination/Mobilisation Activities: after the placement we plan the development and dissemination of the holistic data-driven framework for GBV underreporting (published in English), open thematic discussions through Eureka.
  • Preparation of bids to escalate the project: The aim is to use the ESRC IAA project funding to form a bidding team that can later apply to £500K+ grants jointly.



The overall goal is to ensure the approach and insights from this project can be leveraged in the UK.

Globally, there is a reliance on models and techniques generated in North America and Western Europe and these models are often transplanted to the Global South, in many cases by researchers that do not understand the local context. This work will demonstrate how models and modelling capacity can be developed with a Global South perspective that will enrich the local UK context.

The reach and significance of the entire project going forward has the potential to be unique, tapping into developed and developing countries, and strengthening policy and practice. By leveraging a novel framework to collect and analyse GBV data, future use of data and algorithms will prevent the biases of administrative records combining elements of qualitative research and machine learning (ML).

The team expects the resulting framework to offer opportunities for scaling GBV research, as well as the formulation of inclusive development policies and for the decolonization of data tools and methods for low- and middle-income countries.