This new report by the United Nations Office of High Commissioner of Human Rights builds on three prior analyses and new statistical analysis by HRDAG on killings in Syria.
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HRDAG’s Year in Review: 2020
In 2020, HRDAG provided clarity on issues related to the pandemic, police misconduct, and more.
Estimating the Number of SARS-CoV-2 Infections and the Impact of Mitigation Policies
This Harvard Data Science Review article uses the least unreliable source of pandemic data: reported deaths.
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Lies, Damned Lies and Official Statistics
This essay in the Health and Human Rights Journal addresses attempts to undermine Covid-19 data collection.
HRDAG Welcomes New Staff, Interns and Fellow
HRDAG is delighted to announce five additions to our team: one new staff member, three summer interns, and one fellow.
Lessons at HRDAG: Holding Public Institutions Accountable
Principled Data Processing is a way to prove to someone, usually yourself, that what you did was right.
Innocence Discovery Lab – Harnessing Large Language Models to Surface Data Buried in Wrongful Conviction Case Documents
Ayyub Ibrahim, Huy Dao, and Tarak Shah (2024). “Innocence Discovery Lab - Harnessing Large Language Models to Surface Data Buried in Wrongful Conviction Case Documents." The Wrongful Conviction Law Review 5 (1):103-25. https://doi.org/10.29173/wclawr112. 31 May, 2024. Copyright (c) 2024 Ayyub Ibrahim, Huy Dao, Tarak Shah. Creative Commons Attribution 4.0 International License.
Ayyub Ibrahim, Huy Dao, and Tarak Shah (2024). “Innocence Discovery Lab – Harnessing Large Language Models to Surface Data Buried in Wrongful Conviction Case Documents.” The Wrongful Conviction Law Review 5 (1):103-25. https://doi.org/10.29173/wclawr112. 31 May, 2024. Copyright (c) 2024 Ayyub Ibrahim, Huy Dao, Tarak Shah. Creative Commons Attribution 4.0 International License.
How Review of Police Data Verified Neglect of Missing Black Women
Sloppy recordkeeping by Chicago police has compromised missing persons cases. HRDAG is working with Pulitzer Prize-winning Invisible Institute to shed light on these stories.
Deaths in Custody during the Armed Conflict in Syria, 2011–2023
Maria Gargiulo, Tarak Shah, Megan Price (2024). Deaths in Custody during the Armed Conflict in Syria, 2011–2023. Human Rights Data Analysis Group. 10 December, 2024. © 2024 HRDAG. Creative Commons BY-NC-SA.
Maria Gargiulo, Tarak Shah, Megan Price (2024). Deaths in Custody during the Armed Conflict in Syria, 2011–2023. Human Rights Data Analysis Group. 10 December, 2024. © 2024 HRDAG. Creative Commons BY-NC-SA.
The killings of social movement leaders and human rights defenders in Colombia 2018 – 2023: an estimate of the universe.
Valentina Rozo Ángel and Patrick Ball. 2024. The killings of social movement leaders and human rights defenders in Colombia 2018 - 2023: an estimate of the universe. Human Rights Data Analysis Group. 18 December 2024. © HRDAG 2024. Creative Commons International license 4.0.
Valentina Rozo Ángel and Patrick Ball. 2024. The killings of social movement leaders and human rights defenders in Colombia 2018 – 2023: an estimate of the universe. Human Rights Data Analysis Group. 18 December 2024. © HRDAG 2024. Creative Commons International license 4.0.
Evaluating gunshot detection technology
Bailey’s analysis stemmed from data we had access to as part of our ongoing collaboration with the Invisible Institute.
Kristian Lum in Bloomberg
The interview poses questions about Lum's focus on artificial intelligence and its impact on predictive policing and sentencing programs.
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 -- ...
Datasets available for research
Over the last few years, we've tried to make the data organized in our projects publicly accessible. We have encouraged our partners to publish the data at the completion of the project. We continue to believe it is important to offer access to the data used in our projects for the sake of transparency as well as to encourage further research and analysis. However, we are increasingly concerned about how raw data are used. Data collected by what we can observe is what statisticians call a convenience sample, which is subject to selection bias.
We're keeping these datasets available for researchers who want to use them for simulation or estimation ...
Press Release, Timor-Leste, November 2006
Palo Alto, CA, November 12, 2006 –The Benetech® Initiative congratulates the Commission for Reception, Truth and Reconciliation (CAVR) and the Timorese people for the official release of the CAVR's final report Chega! in Australia today. The 2,500 page report uncovers previously unknown findings about past human rights abuses in Timor-Leste between 1974 and 1999. In particular, the report uncovers widespread and systematic human rights violations in Timor-Leste during the period 1974-1999.
Benetech's statistical analysis establishes that at least 102,800 (+/- 11,000) Timorese died as a result of the conflict. Approximately 18,600 (+/- 1000) ...
Convenience Samples: What they are, and what they should (and should not) be used for
As noted on our Core Concepts page, we spend a lot of time worrying about the ways data are used to make claims about human rights violations. This is because inaccurate statistics can damage the credibility of human rights claims. Analyses of records of human rights violations are used to guide policy decisions, determine resource allocation for interventions, and inform transitional justice mechanisms. It is vital that such analyses are accurate.
Unfortunately, all too often these decisions are based, inappropriately, on analyses of a single convenience sample. (more…)
HRDAG contributes to textbook Counting Civilian Casualties
Next week, on June 11, Oxford University Press officially puts Counting Civilian Casualties: An Introduction to Recording and Estimating Nonmilitary Deaths in Conflict on the market. This textbook, edited by Taylor B. Seybolt, Jay D. Aronson, and Baruch Fischhoff, responds to the increasing concern for civilians in conflict and aims to promote scientific dialogue by highlighting the strengths and weaknesses of the most commonly used casualty recording and estimation techniques.
HRDAG is very well represented here, as our colleagues have co-authored four chapters, and Nicholas Jewell, who sits on our Science Committee, has co-authored a fifth. ...
Counting Casualties in Syria
Today the United Nations Office of the High Commissioner for Human Rights (OHCHR) released a report prepared by me and my colleagues describing the current state of reported killings in the Syrian Arab Republic from the beginning of the conflict in March 2011 through April 2013. (UN news release here.) This report is an update of work we published in January 2013. This updated analysis includes records from eight data sources documenting a total of 92,901 reported killings.
Our analysis begins with 263,055 total records reported by the eight data sources that include sufficient identifying information (name, date, and location*) to conduct ...
Why raw data doesn't support analysis of violence
This morning I got a query from a journalist asking for our data from the report we published yesterday. The journalist was hoping to create an interactive infographic to track the number of deaths in the Syrian conflict over time. Our data would not support an analysis like the one proposed, so I wrote this reply.
We can't send you these data because they would be misleading—seriously misleading—for the purpose you describe. Here's why:
What we have is a list of documented deaths, in essence, a highly non-random sample, though a very big one. We like bigger samples because we think that they must be closer to true. The mathematical justificat...