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The Demography of Large-Scale Human Rights Atrocities: Integrating demographic and statistical analysis into post-conflicthistorical clarification in Timor-Leste.
Romesh Silva and Patrick Ball. “The Demography of Large-Scale Human Rights Atrocities: Integrating demographic and statistical analysis into post-conflicthistorical clarification in Timor-Leste.” Paper presented at the 2006 meetings of the Population Association of America.
Fosas clandestinas en México manifiestan existencia de crímenes de lesa humanidad
Patrick Ball, estadístico norteamericano, colabora con el Programa de Derechos Humanos de la Universidad Iberoamericana en una investigación sobre fosas clandestinas.
The Bigness of Big Data: samples, models, and the facts we might find when looking at data
Patrick Ball. 2015. The Bigness of Big Data: samples, models, and the facts we might find when looking at data. In The Transformation of Human Rights Fact-Finding, ed. Philip Alston and Sarah Knuckey. New York: Oxford University Press. ISBN: 9780190239497. © The Oxford University Press. All rights reserved.
Using Cemetery Information in the Search for the Disappeared: Lessons from a Pilot Study in Rionegro, Antioquia
Tamy Guberek, Daniel Guzmán, and Beatriz Vejarano. “Using Cemetery Information in the Search for the Disappeared: Lessons from a Pilot Study in Rionegro, Antioquia.” In Methodological Proposals for Documenting and Searching for Missing Persons in Colombia. (Available in Spanish) © 2010 EQUITAS. All rights reserved.
The Profile of Human Rights Violations in Timor-Leste, 1974-1999
Romesh Silva and Patrick Ball. “The Profile of Human Rights Violations in Timor-Leste, 1974-1999″, a Report by the Benetech Human Rights Data Analysis Group to the Commission on Reception, Truth and Reconciliation. 9 February 2006.
Analizando los patrones de violencia en Colombia con más de 100 bases de datos
Ciencia de datos para trazar un mapa de la crueldad a la mexicana
From the article: Esta entidad, que existe desde 1991, es liderada por su fundador, Patrick Ball, un científico que acumula una experiencia de más de 25 años realizando análisis cuantitativos en los lugares y en las situaciones más convulsos del planeta. Sobre su colaboración con el proyecto del predictor de fosas clandestinas en México, único en el mundo, Ball afirmó en entrevista:
“Cuando hablamos de crímenes de lesa humanidad estamos hablando de instituciones, de organizaciones grandes, cometiendo miles o centenares de miles de violaciones a víctimas distribuidas sobre una geografía enorme. Para entender los patrones en esas violaciones, la estadística puede brindar una mirada sobre quiénes son los responsables materiales e intelectuales, quiénes son las víctimas y dónde o cuándo pasaron esas violaciones. Pero la estadística no es contabilidad, pues no estamos hablando solamente de las violaciones que podemos ver, sino que también debemos calcular las violaciones no observadas, las escondidas, invisibles, para incluir en nuestro análisis la totalidad de las violaciones”.
Guatemalan National Police Archive Project
Celebrating Ten Years of Data from the AHPN
When Data Doesn’t Tell the Whole Story
Sierra Leone
Learning to Learn: Reflections on My Time at HRDAG
Welcoming Our New Foundation Relations and Strategy Lead
Data on Kosovo Killings
Celebrating Women in Statistics
In her work on statistical issues in criminal justice, Lum has studied uses of predictive policing—machine learning models to predict who will commit future crime or where it will occur. In her work, she has demonstrated that if the training data encodes historical patterns of racially disparate enforcement, predictions from software trained with this data will reinforce and—in some cases—amplify this bias. She also currently works on statistical issues related to criminal “risk assessment” models used to inform judicial decision-making. As part of this thread, she has developed statistical methods for removing sensitive information from training data, guaranteeing “fair” predictions with respect to sensitive variables such as race and gender. Lum is active in the fairness, accountability, and transparency (FAT) community and serves on the steering committee of FAT, a conference that brings together researchers and practitioners interested in fairness, accountability, and transparency in socio-technical systems.