Quantitative Justice: Using Data Science for Good
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For the past several years, I have been closely involved with the Institute for the Quantitative Study of Inclusion, Diversity and Equity (QSIDE). This nonprofit organizes events and facilitates research in quantitative justice, the application of data and mathematical sciences to quantify, analyze and address social injustice. It uses the community-based participatory action research model to connect like-minded scholars, community partners, and activists together. Recently, QSIDE researchers met virtually in a Research Roundup to share our progress. Hearing all the incredible work that QSIDE has spawned and supported prompted me to reflect on the role that the group has played in my budding career and the ways in which the institute itself has grown since its founding in 2019.
Like many PhD candidates, my final year of graduate school was rife with burnout and uncertainty about post-graduation plans. Add to this mix a global pandemic, social isolation, and confinement to the same one-bedroom dwelling for the last year plus and you get a stew of anxiety. I was approaching my mental limit on the research I had been conducting, somewhere at the intersection of data science and fluid dynamics. While the problem I had been working on for my thesis was interesting, I was ready for a major change. I couldn’t picture myself in the usual post-graduate tracks: a post-doc at an R1 institution or working for a Big Tech company. These careers felt hyper-competitive, a turn-off during a period of significant burnout. I also couldn’t see their direct positive impact, which felt acutely important in this time of global social disarray. Though there were certainly other avenues, without seeing examples, it was challenging to picture myself in a career track that felt true to my values.
My outlook brightened immensely with two perfectly-aligned and well-timed opportunities. First, a job opening in data science at Seattle University, a social justice–focused institution that closely aligns with my desire to make a meaningful positive impact with my career. Second, I learned about the emerging community of scholars in data science for social justice that is QSIDE. I started picturing an academic path in which I could employ my quantitative skills for meaningful justice-oriented work. I began participating in events put on by QSIDE and its members, such as the ICERM Mathematical and Computational Approaches to Social Justice workshop and the Data4Justice Conference. I learned about the many ways mathematicians were shining light on and quantifying injustice, exploring topics like bias in federal sentencing, fairness in redistricting, and equity in healthcare, education and the environment. I was ignited with enthusiasm for this new trajectory. I boldly pitched a pivot in my research program in my job interview at Seattle U and was offered the job. Securing a position at an institution that explicitly values this work unlocked the proverbial door. QSIDE paved a path forward by connecting me to a network and opportunities for collaboration.
One such opportunity sprung from the inaugural 2021 QSIDE Datathon4Justice, where I volunteered to co-lead a team for the weekend-long “hackathon” style event. Throughout the weekend, our team made great headway on a very messy data problem. We read in, parsed and cleaned paper police logs from a small Massachusetts town whose police force had ongoing reports of misconduct. This event invited an extraordinarily interdisciplinary team, bringing expertise from the local community, law, policing, social science, and data science together. Our team made major strides in the problem, going from a vast pile of completely unusable data to summary statistics and maps of policing practices in only three days. We also knew there was much more work to be done and were now connected with community members who sought more answers. From this, the Small Town Police Accountability (SToPA) Research Lab was formed and has been working to democratize policing data since.
Since this early event and research lab, QSIDE has grown immensely into a network of ongoing collaboration between academics and community members. The Research Roundup event highlighted the ongoing contributions of their diverse working groups. The SToPA Lab expanded to investigate data from a handful of other small towns and has developed a toolkit for the public to collect and analyze their community’s policing data. This work has branched to include a focus on novel, community-initiated research in policing in the Data Science, Police Accountability, Community Engagement (DSPACE) group. The JUdicial System Transparency for Fairness through Archived Inferred Records (JUSTFAIR) research lab is working to understand disparities in federal judicial sentencing across eight states and counting. The Modern-Day Exploitation research lab seeks to identify and disrupt human trafficking through financial data. The Data for Accountability, Transparency, and Advancement to Lower Incarceration for Transformation (DATA2LIFT) initiative investigates incarceration-related topics such as calculating the monetary costs to society of incarceration, identifying concentrations of opportunity youth to facilitate employment matching, and re-envisioning community safety without incarceration. Their Data4Justice Curriculum also enables educators to simultaneously teach statistical skills and connect scientific content to social justice work. An impressive amount of community-anchored direct action, published research, and educational opportunities have resulted from this work.
While I have only a small part in this broader organization, QSIDE has played a monumental role in my growth as a scholar and citizen. I have had the opportunity to work alongside other QSIDE affiliates in my budding academic career and now feel solidly connected to a network of justice-oriented mathematicians. Our department is an ongoing consortium member at QSIDE, which enables our students to engage more directly with the organization. I aspire that this relationship might empower students to pursue quantitative research in a meaningful application as it has done for me.
Ariana Mendible is an Assistant Professor at Seattle University. She aims to address social injustice through the lens of data science, both in teaching and through community partnerships in research.