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What happens when you look at crime by the numbers

Kristian Lum’s work on the HRDAG Policing Project is referred to here: “In fact, Lum argues, it’s not clear how well this model worked at depicting the situation in Oakland. Those data on drug crimes were biased, she now reports. The problem was not deliberate, she says. Rather, data collectors just missed some criminals and crime sites. So data on them never made it into her model.”


Film: Solving for X

Solving for X documents Patrick's team as they travel to Guatemala, Kosovo, and Liberia, helping human rights supporters apply sophisticated computer analysis to human rights events.

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.

The story of one document inside the AHPN

The beginnings are crucial in every step—as critical as the beginning of sound, life, hope, and justice. Here are some first steps from the AHPN (Archivo Histórico de la Policía Nacional). This is the story of Oficio Number COC/207-laov, a document that at first appears uninteresting. But this is not just any oficio*. This is one of the many documents that helped bring to trial the people responsible for the disappearance of Edgar Fernando García. A father, husband, son, and student, García was, like many people today, interested in changing his community for the better. (more…)

Multiple Systems Estimation: Collection, Cleaning and Canonicalization of Data

<< Previous post: MSE: The Basics Q3. What are the steps in an MSE analysis? Q4. What does data collection look like in the human rights context? What kind of data do you collect? Q5. [In depth] Do you include unnamed or anonymous victims in the matching process? Q6. What do you mean by "cleaning" and "canonicalization?" Q7. [In depth] What are some of the challenges of canonicalization? (more…)

Weapons of Math Destruction

Weapons of Math Destruction: invisible, ubiquitous algorithms are ruining millions of lives. Excerpt:

As Patrick once explained to me, you can train an algorithm to predict someone’s height from their weight, but if your whole training set comes from a grade three class, and anyone who’s self-conscious about their weight is allowed to skip the exercise, your model will predict that most people are about four feet tall. The problem isn’t the algorithm, it’s the training data and the lack of correction when the model produces erroneous conclusions.


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. ...

Why Collecting Data In Conflict Zones Is Invaluable—And Nearly Impossible

HRDAG's work in Kosovo and in the Guatemalan trial of General José Efraín Ríos Montt is discussed in this article. Megan Price, HRDAG's director of research, is quoted. “There is a wide variety of things that could be considered data,” she says. From the story: Price’s main data analysis tool requires fitting a model to the data that ends up in her lap. That way, she can see whether there are gaps in the data and what more needs to be included. The method, called multiple systems estimation analysis, lets Price look at patterns across lists of data, for example, lists of victims. The resulting model reveals how much data is missing, to a ...

Reality and risk: A refutation of S. Rendón’s analysis of the Peruvian Truth and Reconciliation Commission’s conflict mortality study

Daniel Manrique-Vallier and Patrick Ball (2019). Reality and risk: A refutation of S. Rendón’s analysis of the Peruvian Truth and Reconciliation Commission’s conflict mortality study. Research & Politics, 22 March 2019. © Sage Journals. https://doi.org/10.1177/2053168019835628

Daniel Manrique-Vallier and Patrick Ball (2019). Reality and risk: A refutation of S. Rendón’s analysis of the Peruvian Truth and Reconciliation Commission’s conflict mortality study. Research & Politics, 22 March 2019. © Sage Journals. https://doi.org/10.1177/2053168019835628


Los asesinatos de líderes sociales que quedan fuera de las cuentas

Una investigación de Dejusticia y Human Rights Data Analysis Group concluyó que hay un subconteo en los asesinatos de líderes sociales en Colombia. Es decir, que el aumento de estos crímenes en 2016 y 2017 podría ser incluso mayor al reportado por las organizaciones y por las cifras oficiales.


Reflections: HRDAG Was Born in Washington

I began working with HRDAG in the summer of 2001 before it was ever even called HRDAG. In fact, not intended as a boast, I think I’m responsible for coming up with the name. After contracting with Dr. Patrick Ball for a time writing the Analyzer data management platform, I left New York City and joined him in Washington, DC, at AAAS in 2002. Soon after starting, Patrick decided to establish an identity for this new team, consisting mainly of myself, Miguel Cruz and a handful of field relationships. We discussed what to name it briefly in the AAAS Science & Policy break room, which at the time, being in the mind of unclever descriptive naming ...

HRDAG Report on Disappeared Tamils in Army Custody in Sri Lanka

HRDAG has published a report about the 500 Tamils who disappeared while in Army custody in Sri Lanka in 2009.

The Use of Unstructured Data to Study Police Use of Force

Tarak Shah, Cristian Allen, Ayyub Ibrahim, Harlan Kefalas, and Bavo Stevens (2024). The Use of Unstructured Data to Study Police Use of Force. 5 December, 2024. CHANCE, 37(4), 18–23. https://doi.org/10.1080/09332480.2024.2434437

Tarak Shah, Cristian Allen, Ayyub Ibrahim, Harlan Kefalas, and Bavo Stevens (2024). The Use of Unstructured Data to Study Police Use of Force. 5 December, 2024. CHANCE37(4), 18–23. https://doi.org/10.1080/09332480.2024.2434437


Welcoming Our 2019 Data Science Fellow

We’re pleased to announce that Camille Fassett has joined our team as our new data science fellow.

Trips to and from Guatemala

HRDAG has been working with the Historic Archive of the National Police in Guatemala (hereafter, the Archive) for the past seven years.  The Archive contains a treasure trove of data recorded and kept by the Guatemalan National Police over the past century.  When the Archive was first discovered in 2005, researchers there immediately recognized both the value and fragility of the tens of millions of documents.  As a result, they reached out to HRDAG, and we reached out to volunteers at Westat to devise a plan to estimate the contents of the entire Archive as quickly as possible in case the documents were destroyed or access to them was limited.  ...

CIIDH Data – Variables List

Version date: 2000.01.29 Current version: ATV20.1 Patrick Ball & Herbert F. Spirer Below are listed the 19 files that constitute the CIIDH database. We have noted those that include data that might be analytically useful in future versions of ATV. File names and brief definitions are in bold, and variable summaries are in bulleted points. CXTOV2 (Context; links to VLCNV2) Additional detail on geographic location of case Narrative summary CXTOV2ex (Context extension; links to CXTOV2) Fine breakdown on the age category & sex of anonymous victims CXTOV2lg (Context extension; links to CXTOV2) Legal procedures taken on behalf of the ...

The Ways AI Decides How Low-Income People Work, Live, Learn, and Survive

HRDAG is mentioned in the “child welfare (sometimes called “family policing”)” section: At least 72,000 low-income children are exposed to AI-related decision-making through government child welfare agencies’ use of AI to determine if they are likely to be neglected. As a result, these children experience heightened risk of being separated from their parents and placed in foster care.


Tech Note – using LLMs for structured info extraction

This post introduces the methodology of the Innocence Discovery Lab, a collaboration between IPNO and HRDAG.

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.


Insights Sessions

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 ...

Our work has been used by truth commissions, international criminal tribunals, and non-governmental human rights organizations. We have worked with partners on projects on five continents.

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