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Hunting for Mexico’s mass graves with machine learning
“The model uses obvious predictor variables, Ball says, such as whether or not a drug lab has been busted in that county, or if the county borders the United States, or the ocean, but also includes less-obvious predictor variables such as the percentage of the county that is mountainous, the presence of highways, and the academic results of primary and secondary school students in the county.”
Who Did What to Whom? Planning and Implementing a Large Scale Human Rights Data Project
Patrick Ball. Who Did What to Whom? Planning and Implementing a Large Scale Human Rights Data Project. © 1996 American Association for the Advancement of Science.
Violence in Blue
Patrick Ball. 2016. Granta 134: 4 March 2016. © Granta Publications. All rights reserved.
Predictive policing tools send cops to poor/black neighborhoods
In this post, Cory Doctorow writes about the Significance article co-authored by Kristian Lum and William Isaac.
Trips to and from Guatemala
Welcome!
Recognising Uncertainty in Statistics
In Responsible Data Reflection Story #7—from the Responsible Data Forum—work by HRDAG affiliates Anita Gohdes and Brian Root is cited extensively to make the point about how quantitative data are the result of numerous subjective human decisions. An excerpt: “The Human Rights Data Analysis Group are pioneering the way in collecting and analysing figures of killings in conflict in a responsible way, using multiple systems estimation.”
Data-driven crime prediction fails to erase human bias
Work by HRDAG researchers Kristian Lum and William Isaac is cited in this article about the Policing Project: “While this bias knows no color or socioeconomic class, Lum and her HRDAG colleague William Isaac demonstrate that it can lead to policing that unfairly targets minorities and those living in poorer neighborhoods.”
Mapping Mexico’s hidden graves
When Patrick Ball was introduced to Ibero’s database, the director of research at the Human Rights Data Analysis Group in San Francisco, California, saw an opportunity to turn the data into a predictive model. Ball, who has used similar models to document human rights violations from Syria to Guatemala, soon invited Data Cívica, a Mexico City–based nonprofit that creates tools for analyzing data, to join the project.
Using Math and Science to Count Killings in Syria
Capture-Recapture for Casualty Estimation and Beyond: Recent Advances and Research Directions
Manrique-Vallier, D., Ball, P., Sadinle, M. (2022). Capture-Recapture for Casualty Estimation and Beyond: Recent Advances and Research Directions. In: Carriquiry, A.L., Tanur, J.M., Eddy, W.F. (eds) Statistics in the Public Interest. Springer Series in the Data Sciences. Springer, Cham. https://doi.org/10.1007/978-3-030-75460-0_2
Estimating the human toll in Syria
Megan Price (2017). Estimating the human toll in Syria. Nature. 8 February 2017. © 2017 Macmillan Publishers Limited, part of Springer Nature. All rights reserved. Nature Human Behaviour. ISSN 2397-3374.
At Toronto’s Tamil Fest, human rights group seeks data on Sri Lanka’s civil war casualties
Earlier this year, the Canadian Tamil Congress connected with HRDAG to bring its campaign to Toronto’s annual Tamil Fest, one of the largest gatherings of Canada’s Sri Lankan diaspora.
Ravichandradeva, along with a few other volunteers, spent the weekend speaking with festival-goers in Scarborough about the project and encouraging them to come forward with information about deceased or missing loved ones and friends.
“The idea is to collect thorough, scientifically rigorous numbers on the total casualties in the war and present them as a non-partisan, independent organization,” said Michelle Dukich, a data consultant with HRDAG.
New Report Raises Questions Over CPD’s Approach to Missing Persons Cases
In this video, Trina Reynolds-Tyler of Invisible Institute talks about her work with HRDAG on the missing persons project in Chicago and Beneath the Surface.