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verdata: An R package for analyzing data from the Truth Commission in Colombia
Maria Gargiulo, María Julia Durán, Paula Andrea Amado, and Patrick Ball (2024). verdata: An R package for analyzing data from the Truth Commission in Colombia. The Journal of Open Source Software. 6 January, 2024. 9(93), 5844, https://doi.org/10.21105/joss.05844. Creative Commons Attribution 4.0 International License.
Maria Gargiulo, María Julia Durán, Paula Andrea Amado, and Patrick Ball (2024). verdata: An R package for analyzing data from the Truth Commission in Colombia. The Journal of Open Source Software. 6 January, 2024. 9(93), 5844, https://doi.org/10.21105/joss.05844. Creative Commons Attribution 4.0 International License.
South Africa
Under apartheid, South Africans from all sides suffered violence and human rights abuses. One of the mandates of the the South African Truth and Reconciliation Commission (TRC) was to report truth by reporting on violations and victims.
Dr. Patrick Ball, as Deputy Director of the Science and Human Rights Program (SHRP) of the American Association for the Advancement of Science (AAAS), used the who-did-what-to-whom data model to provide statistical analysis of the violations reported to the Commission, for use in the final report of the TRC.
Links:
http://shr.aaas.org/southafrica/trcsa/
http://www.doj.gov.za/trc/index....
Welcome!
As of today, the Human Rights Data Analysis Group (HRDAG) is an independent* non-profit! It's been a long time coming, and we're delighted to have gotten to this point. HRDAG is a non-profit, non-partisan organization that applies rigorous science to the analysis of human rights violations around the world; for more information, see our About Us page.
Benetech has spun out the scientific and statistical part of the Human Rights Program to HRDAG. The spinout includes (as staff) me -- Patrick Ball -- and Dr Megan Price, as well as our many part-time scientific and field consultants (a list is here). The software and technology component of our work -- ...
Controlled vocabulary
What is a controlled vocabulary?
A controlled vocabulary provides the ability to transform information that has been collected on violations, victims, and perpetrators into a countable set of data categories. It is important that this process be done without discarding relevant information and without misrepresenting the collected information.
Why is it necessary?
The data collected about human rights violations originates from a wide range of information sources – legal case files, newspaper articles, e-mails, faxes, letters, phone conversations, testimonies, interviews, radio and television programs, video clips, and photos. This wide range of ...
In Solidarity
We stand with our partners and every organizer fighting for justice.
HRDAG Drops Dropbox
On Wednesday, April 9, the file hosting service Dropbox announced the addition of Condoleezza Rice, former U.S. National Security Advisor and Secretary of State, to their Board of Directors, citing the need for “a leader who could help us expand our global footprint.”
In response to this announcement, HRDAG requested (and rapidly received) a refund for our recent purchase of Dropbox for Business, and will drop the use of their service entirely.
Patrick Ball, HRDAG’s Executive Director stated: “As a human rights organization, we find Condoleezza Rice's complicity in the serious human rights abuses of the Bush administration very worrying. ...
Sierra Leone TRC Data and Statistical Appendix
HRDAG assisted the Sierra Leone Truth and Reconciliation Commission in building a systematic data coding system, electronic database, and secure data analysis process to manage the thousands of statements given to them in the course of their work. HRDAG executive director Patrick Ball and HRDAG field consultant Richard Conibere worked at the TRC full-time for approximately eighteen months starting in March 2003.
HRDAG worked with TRC researchers to help them incorporate quantitative findings to support the qualitative findings in their writing for the other chapters of the TRC report. In addition, HRDAG produced a Statistical Appendix to present ...
Reflections on Data Science for Real-World Problems
Trina Reynolds-Tyler's internship at HRDAG helped her use data science to find patterns in state-sanctioned violence.
Talks & Discussions
2021 Rafto Prize Videos
.ugb-8203b62 .ugb-video-popup__wrapper{height:460px !important;background-color:#000000;background-image:url(https://hrdag.org/wp-content/uploads/2022/12/Screen-Shot-2022-12-09-at-3.41.30-PM.png)}.ugb-8203b62 .ugb-video-popup__wrapper:before{background-color:#000000;opacity:0.3}.ugb-8203b62 .ugb-video-popup__wrapper:hover:before{opacity:0.6}.ugb-8203b62 .ugb-block-title{color:#ffffff}.ugb-8203b62 .ugb-block-description{color:#ffffff}@media screen and (max-width:768px){.ugb-8203b62 .ugb-video-popup__wrapper{height:208px !important}}The Rafto Prize 2021 | Rafto Foundation Rafto Foundation | HRDAG team | 2021 | 4 min
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HRDAG Offers New R Package – dga
Much of the work we do at HRDAG involves estimating the number of undocumented deaths using a statistical technique called multiple systems estimation (MSE, described in more detail here). One of our goals is to make this class of methods more broadly available to human rights researchers. In particular, we are finding that Bayesian approaches are extremely valuable for MSE. Accordingly, we are pleased to offer a new R package called dga (“decomposable graphs approach”) that performs Bayesian model averaging for MSE.
The main function in this package implements a model created by David Madigan and Jeremy York. This model was designed to ...
Predictive Policing Reinforces Police Bias
Issues surrounding policing in the United States are at the forefront of our national attention. Among these is the use of “predictive policing,” which is the application of statistical or machine learning models to police data, with the goal of predicting where or by whom crime will be committed in the future. Today Significance magazine published an article on this topic that I co-authored with William Isaac. Significance has kindly made this article open access (free!) for all of October. In the article we demonstrate the mechanism by which the use of predictive policing software may amplify the biases that already pervade our criminal ...
Testimonials
HRDAG is honored to work with a diverse set of partners. These organizations and the individuals that operate them are critical to our success, and our goal is to be critical to theirs. Here are a few quotes from our colleagues.
"Over the last two years, Dr Patrick Ball has spoken several times to relevant AI staff on the use (and mis-use) of quantitative data in human rights work. Each time, people rave about it afterwards commenting on Patrick's inimical skills to convey the complexity of statistical science in an accessible, relevant and fun way. This year, we also organised small meetings with individual teams who have to crunch 'big data' ...
HRDAG Retreat 2015
I look at the beach and then at the table surrounded by nerds, deep in thought and conversation about Dirichlet priors, matching algorithms, and armed conflicts. This peculiar (in the best way) environment catalyzes a moment of reflection: how did I get here?
Four years ago, as a second-year statistics PhD student, I watched "Guatemala: The Secret Files" on PBS Frontline World. I listened to stories of family members who disappeared without answers or justice. Then the story shifted to the work being done by archivists and data experts at Guatemala's Historic Archive of the National Police. The scientists' pursuit of the truth energized me. I ...
Guatemalan National Police Archive Project
The Historic Archive of the Guatemalan National Police (hereafter the Archive) was discovered, quite by accident, in July 2005. Researchers immediately recognized both the importance and the fragility of the Archive's contents. As a result, in early 2006 the Archive team invited Patrick to evaluate the documents and help them answer a seemingly simple question: How can we learn about the contents of the Archive in a shorter period of time than is needed to systematically examine each individual document?
After inspecting the Archive, Patrick designed a multi-stage random sample of documents. In May 2006, Tamy Guberek, Daniel Guzmán, and ...
Patrick Ball wins the Karl E. Peace Award
Patrick Ball won the Karl E. Peace Award for Outstanding Statistical Contributions for the Betterment of Society at the 2018 Joint Statistical Meeting.
In Pursuit of Excellent Data Processing
With help from HRDAG, Roman Rivera built the data backbone for the Invisible Institute's Citizens Police Data Project.
HRDAG Names New Board Members Julie Broome and Frank Schulenburg
We are pleased to announce that HRDAG will be supported by two additions to our Advisory Board, Julie Broome and Frank Schulenburg.
We’ve worked with Julie for many years, getting to know her when she was Director of Programmes at The Sigrid Rausing Trust. She is now the Director of London-based Ariadne, a network of European funders and philanthropists. She worked at the Trust for seven years, most notably Head of Human Rights, before becoming Director of Programmes in 2014. Before joining the Trust she was Programme Director at the CEELI Institute in Prague, where she was responsible for conducting rule of law-related trainings for judges and ...
Always Learning
The data science field is always changing, which means that I'll always be learning.
Letter from the Executive Director
Dear Friends,
This has been quite a year, and I don’t just mean the recent political events in the United States, Europe and the Middle East.
Thanks to your ongoing support, HRDAG has a number of accomplishments to be proud of this year:
Patrick’s testimony in the trial of Hissene Habré for crimes against humanity was cited by the judges three times in their determination of guilt.
We launched a book describing ten years of collaborative work with the Historic Archive of the National Police in Guatemala.
We contributed quantitative analyses to Amnesty International’s report on deaths in Syrian custody, and published an ...
Limitations of mitigating judicial bias with machine learning
Kristian Lum (2017). Limitations of mitigating judicial bias with machine learning. Nature. 26 June 2017. © 2017 Macmillan Publishers Limited, part of Springer Nature. All rights reserved. Nature Human Behavior. DOI 10.1038/s41562-017-0141.
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Kristian Lum (2017). Limitations of mitigating judicial bias with machine learning. Nature. 26 June 2017. © 2017 Macmillan Publishers Limited, part of Springer Nature. All rights reserved. Nature Human Behavior. DOI 10.1038/s41562-017-0141.