In 2017, Data2X issued a call for research projects that sought to apply insights drawn from big data to the lives of women and girls.
The Governance Lab (The GovLab) based at New York University was one of ten recipients of a Big Data for Gender challenge grant. Two years later, these research projects are reporting on their findings. In this context, Data2X sat down with the GovLab to discuss their motivations for this work, what their results mean for gender data more broadly, and where they plan to go from here.
Data2X: You were already working on big data research when you applied for a Data2X Big Data for Gender challenge grant. What made you interested in this challenge?
The GovLab: Over the last few years, we have worked on unlocking and using data assets to help improve the way we solve societal challenges through data collaboratives. A data collaborative is a new form of collaboration, beyond the public-private partnership model, in which participants from different sectors exchange their data to create public value.
We were excited to apply to the Data2X Big Data for Gender challenge so we could establish a data collaborative to deepen our work leveraging private data, such as satellite and telecom data, for the public good with a specific focus on gender. We did this through a collaborative with UNICEF, Universidad del Desarrollo, Telefónica R&D Center, ISI Foundation, and DigitalGlobe. Our ultimate goal is to leverage the insights from the data collaboratives to better design policies and provide more actionable solutions that can help improve people’s lives — including those of women and girls — around the world.
Data2X: What was your topline learning from this project? (More details are available in this project brief.)
The GovLab: Our topline finding is a confirmation that urban mobility is gendered: women and men behave differently and have difference experiences and needs when they move around a city. For instance, we learned that women and girls in low-income areas of Santiago visit fewer and more localized places than men on average.
Our research also suggests that they spend their time in only a few locations — possibly due to cultural, infrastructure, resource, and safety constraints. In addition, women and girls generally travel to specific locations, such as hospitals and taxi stands, with more regularity.
Finally, our findings show that gender-limited mobility is more complex than simply accessibility to public transit: although access reduces mobility differences across socio-economic areas for men, it unfortunately has little impact on women. Education, employment, the presence of children in the home, and low income — likely the largest factor — all contribute to the gender mobility gap in Santiago.
Data2X: What does your work show about how big data can be used to gather insights about the lives of women and girls?
The GovLab: Our work shows that connecting open government data with data generated by satellite, geolocation and real-time mapping tools, and telecom interactions (generating call detail records, or CDRs) can both help establish a baseline of gender-limited urban mobility, and can also help identify the variables that make a difference for women and girls, such as employment, family structure, and education opportunities.
We have found that using big data has great potential to address gender-specific questions, and can help inform urban planners and, in this case, improve Santiago’s decision-making process. The real-time nature and affordability of CDRs will likely complement, if not provide an alternative, to collecting survey data. Perhaps more importantly, accessing CDR data enabled us to create a data model that can be replicated in other regions and settings, as well as a machine learning pipeline that helps estimate income from satellite images of cities where surveys are either difficult to distribute or are not available.
Data2X: Where will your research go from here?
The GovLab: Our objective is to work with our partners towards creating a Gender Data for Urban Mobility Hub (GD4M). The goal of this Hub will be to continue this research, ensure that gender and urban mobility questions are prioritized, and consider data needs to answer mobility questions. The Hub could also incubate new data collaboratives by serving as a “Data and Learn Tank”, and helping initiate data collaborative projects with various cities using lessons from existing efforts. As we have demonstrated, big data can offer important insights into gender-related urban mobility questions, and we hope our Hub can help guide Data2X and other international and national players in their efforts.
Finally, this work also informed our The 100 Questions Initiative which seeks to identify the most important societal questions, including gender, whose answers can be found through greater access to data and data science methods. Data2X contributes both financial support and expertise in improving the quality, availability, and use of data in the gender domain of the initiative. Additionally, Data2X is a cross-domain partner and has an advisory role to ensure coverage across other domains where gender considerations are applicable.