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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. .

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.


Theoretical limits of microclustering for record linkage

James E Johndrow, Kristian Lum and D B Dunson (2018). Theoretical limits of microclustering for record linkage. Biometrika. 19 March 2018. © 2018 Oxford University Press. DOI 10.1093/biomet/asy003.

John E Johndrow, Kristian Lum and D B Dunson (2018). Theoretical limits of microclustering for record linkage. Biometrika. 19 March 2018. © 2018 Oxford University Press. DOI 10.1093/biomet/asy003.


Using Statistics to Assess Lethal Violence in Civil and Inter-State War

Patrick Ball and Megan Price (2019). Using Statistics to Assess Lethal Violence in Civil and Inter-State War. Annual Review of Statistics and Its Application, Volume 6. 7 March 2019. © 2019 Annual Reviews. All rights reserved. https://doi.org/10.1146/annurev-statistics-030718-105222.

Patrick Ball and Megan Price (2019). Using Statistics to Assess Lethal Violence in Civil and Inter-State War. Annual Review of Statistics and Its Application. 7 March 2019. © 2019 Annual Reviews. All rights reserved. https://doi.org/10.1146/annurev-statistics-030718-105222.


Low-risk population size estimates in the presence of capture heterogeneity

James Johndrow, Kristian Lum and Daniel Manrique-Vallier (2019). Low-risk population size estimates in the presence of capture heterogeneity. Biometrika, asy065, 22 January 2019. © 2019 Biometrika Trust. https://doi.org/10.1093/biomet/asy065

James Johndrow, Kristian Lum and Daniel Manrique-Vallier (2019). Low-risk population size estimates in the presence of capture heterogeneityBiometrika, asy065, 22 January 2019. © 2019 Biometrika Trust. https://doi.org/10.1093/biomet/asy065


A Model to Estimate SARS-CoV-2-Positive Americans

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 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 ...

Overbooking’s Impact on Pre-Trial Risk Assessment Tools

How do police officer booking decisions affect tools relied upon by judges?

In Solidarity

We stand with our partners and every organizer fighting for justice.

Update of Iraq and Syria Data in New Paper

This week The Statistical Journal of the IAOS published a new(ish) paper by Megan Price and Patrick Ball. The open-access paper, Selection bias and the statistical patterns of mortality in conflict, is a revisiting and updating of both the Iraq and Syria examples used in an earlier paper, Big Data, Selection Bias, and the Statistical Patterns of Mortality in Conflict, which was published last year inThe SAIS Review of International Affairs (JHU Press, 2014). HRDAG believes that the concerns highlighted by these examples are important for a wide variety of audiences, including both the foreign policy readers reached by The SAIS Review and the ...

A geeky deep-dive: database deduplication to identify victims of human rights violations

In our work, we merge many databases to figure out how many people have been killed in violent conflict. Merging is a lot harder than you might think. Many of the database records refer to the same people--the records are duplicated. We want to identify and link all the records that refer to the same victims so that each victim is counted only once, and so that we can use the structure of overlapping records to do multiple systems estimation. Merging records that refer to the same person is called entity resolution, database deduplication, or record linkage. For definitive overviews of the field, see Scheuren, Herzog, and Winkler, Data Quality ...

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 ...

Get Involved/Donate

Donating to HRDAG Thank you for your interest in making a donation to the Human Rights Data Analysis Group to help us use science to support our partners in the human rights world. You can make a donation by credit card on the Community Partners® Network for Good page. HRDAG is a "project of Community Partners," and right below  the section on payment information, you'll be able to select "Human Rights Data Analysis Group" from a drop-down menu. (On most browsers, if you use this link, HRDAG will be pre-selected on the drop-down menu.) This transaction will appear on your credit card statement as "Network for Good." If you donate by check, ...

Coming soon: HRDAG 2019 Year-End Review

The online version of the 2019 Year-End Review will appear in January 2020.            

Cuentas y mediciones de la criminalidad y de la violencia

Exploración y análisis de los datas para comprender la realidad. Patrick Ball y Michael Reed Hurtado. 2015. Forensis 16, no. 1 (July): 529-545. © 2015 Instituto Nacional de Medicina Legal y Ciencias Forenses (República de Colombia).


El Salvador 1991 – Who Did What To Whom?

Members of the Salvadoran military committed tens of thousands of killings during the country’s civil war which raged from the late 1970’s until 1990. While working for a peace organization in El Salvador in 1991, Patrick Ball was asked by a colleague at a human rights group to help organize a large collection of human rights testimonies. Trained as a social scientist, Ball created the “Who Did What To Whom” (WTWTW) model for examining human rights data. Ball used this system to create a structured, relational database of violations reported in more than 9,000 testimonies to the Salvadoran Human Rights Commission. To determine who was most ...

Primer to Inform Discussions about Bail Reform

The primer addresses what pretrial risk assessment is and what the research supports.

Coders Bare Invasion Death Count


Celebrating our First Anniversary and Welcoming Our Newest Board Member

One year ago, HRDAG cast out on its own as an independent nonprofit—and this first year has been busy, productive, and exciting. We’re indebted to our Advisory Board for their valuable contributions and to our funders for their generosity and participation in our mission. Highlights of the past year include contributing testimony to three court cases, publishing two reports on conflict-casualties in Syria, presenting over a dozen talks (many of which are available on our talks page), traveling to over half a dozen countries to testify, collaborate with partners, and participate in conferences/workshops, hiring a new technical lead, and bringing in ...

Clustering and Solving the Right Problem

In our database deduplication work, we’re trying to figure out which records refer to the same person, and which other records refer to different people. We write software that looks at tens of millions of pairs of records. We calculate a model that assigns each pair of records a probability that the pair of records refers to the same person. This step is called pairwise classification. However, there may be more than just one pair of records that refer to the same person. Sometimes three, four, or more reports of the same death are recorded. So once we have all the pairs classified, we need to decide which groups of records refer to the ...

Welcoming a New Board Member

As we get ready to begin our fourth year as an independent nonprofit, we are, as always, indebted to our Advisory Board and to our funders for their support and vision. We’re finishing up a busy year that took us to Dakar (for the trial of former Chadian dictator Hissène Habré), Pristina (for the release of the Kosovo Memory Book), Colombia (for work on a book about the Guatemalan Police Archives), and kept us busy here at home working on police violence statistics. But one of our biggest victories has been to score a new, talented, wise Advisory Board member—Michael Bear Kleinman, whom we first met when he was working with Humanity United. ...

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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