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Biotechniques published an interview with Patrick Ball, inspired by his John Maddox Prize award.
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.
Sarah L. Desmarais and Evan M. Lowder (2019). Pretrial Risk Assessment Tools: A Primer for Judges, Prosecutors, and Defense Attorneys. Safety and Justice Challenge, February 2019. © 2019 Safety and Justice Challenge. <<HRDAG's Kristian Lum and Tarak Shah served as Project Members and made contributions to the primer.>>
Sarah L. Desmarais and Evan M. Lowder (2019). Pretrial Risk Assessment Tools: A Primer for Judges, Prosecutors, and Defense Attorneys. Safety and Justice Challenge, February 2019. © 2019 Safety and Justice Challenge. <<HRDAG’s Kristian Lum and Tarak Shah served as Project Members and made significant contributions to the primer.>>
In this afternoon "Lightning Talk" at RightsCon 2014, Megan Price spoke about the importance of using models to adjust for variability when reporting human rights violations and mentioned innovative tools that can be used for tracking abuses.
RIGHTSCON
March 4, 2014
San Francisco, California
Link to RightsCon program
Back to Talks
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HRDAG’s analysis and expertise continues to deepen the national conversation about police violence and criminal legal reform in the United States. In 2015 we began by considering undocumented victims of police violence, relying on the same methodological approach we’ve tested internationally for ...
HRDAG and our partners Data Cívica and the Iberoamericana University created a machine-learning model to predict which counties (municipios) in Mexico have the highest probability of unreported hidden graves. The predictions help advocates to bring public attention and government resources to search for the disappeared in the places where they are most likely to be found.
Context
For more than ten years, Mexican authorities have been discovering hidden graves (fosas clandestinas). The casualties are attributed broadly—and sometimes inaccurately—to the country’s “drug war,” but the motivations and perpetrators behind the mass murders ...
In this
Granta article, HRDAG explains that neither the infectiousness nor the deadliness of the disease is set in stone.
Data coding is the process of converting unstructured information, such as a narrative testimony, into discrete facts such as names and roles of actors (victims, witnesses, perpetrators) in crimes, as well as the date and place of act. Data coding must not discard or distort information. When more than one person is identifying, classifying and counting the elements reported in a qualitative source, the results of what they find may differ slightly based on each individual's interpretation and care in doing the coding. These differences can be measured by measuring IRR (inter-rater reliability). We give the same source document to several coders and ...
Bailey’s analysis stemmed from data we had access to as part of our ongoing collaboration with the Invisible Institute.
Field Consultant
Carolina Lopéz has worked with the Archivo Histórico de la Policía Nacional (AHPN) in Guatemala for eight years, and is currently a member of the Archive Technical Coordination team. A professional working within the social sciences, she prefers using alternative research on past practices to develop an understanding of the present. Her work consists primarily of monitoring and creating strategies to systematize, track and create process controls. She also has thorough knowledge of management of historical archive documents.
Since 2006, Carolina has worked in quantitative research at the AHPN with HRDAG team members Patrick ...
We’ve
built a model for estimating the true number of positives, using what we have determined to be the most reliable datasets—deaths.
HRDAG has been fortunate to have a long and exciting history that has taken us around the world to analyze data related to human rights violations. Along the way, we have met wonderful people, worked with amazing organizations and been a part of an amazing advancement of science through data analysis.
This page highlights key moments in our history.
We work around the world
Here’s more information about How We Choose Projects.
You are invited to
Illuminating the dark through data science:
Stories from the Human Rights Data Analysis Group
Thursday, 3 June 2021, 12–1pm PDT
A conversation with HRDAG advisory board member Margot Gerritsen, executive director Megan Price, statistician Maria Gargiulo, and field consultant Anita Gohdes.
The Human Rights Data Analysis Group uses data to help the world understand human stories. In this intimate, virtual conversation, executive director Megan Price and other inspiring HRDAG data scientists will share stories about how their data analysis has powered truth commissions and grassroots justice organizations, and held human rights ...
A monthly newsletter exploring how math and science help us understand the world.
Hi, I’m Patrick Ball. I’m a statistician, which is a type of scientist that uses mathematical analysis to try to figure out what we do and don’t know about data sets. I’m also a human rights advocate; I work with groups all over the world to help survivors in post-conflict countries understand what really happened and bring justice and accountability. It’s incredible work, and I feel grateful to do it.
I want to invite you to check out a new newsletter, Structural Zero. It’s written by me and my colleagues Megan Price, Bailey Passmore, Tarak Shah, and ...
Congratulations to Patrick on this well deserved award!
HRDAG is delighted to announce five additions to our team: one new staff member, three summer interns, and one fellow.
Administrative paperwork generated by police departments can hold evidence of police violence, but can present unique challenges for data processing.
IPFS is a peer-to-peer storage network that promotes the resiliency, immutability, and auditability of data. This README explains code written to shepherd the files from janky external USB drives to IPFS.