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Collecting Sensitive Human Rights Data in the Field: A Case Study from Amritsar, India.

Romesh Silva and Jasmine Marwaha. “Collecting Sensitive Human Rights Data in the Field: A Case Study from Amritsar, India.” In JSM Proceedings, Social Statistics Section. Alexandria, VA. © 2011 American Statistical Association. All rights reserved.


The case against Hissene Habre


Guilty Verdict and 40 year Maximum Sentence in Edgar Fernando Garcia Case


Making the Case. Investigating Large Scale Human Rights Violations Using Information Systems and Data Analysis

Patrick Ball, Herbert F. Spirer, and Louise Spirer, eds. Making the Case. Investigating Large Scale Human Rights Violations Using Information Systems and Data Analysis . © 2000 American Association for the Advancement of Science. All rights reserved. Reprinted with permission. [full text] [intro] [chapters 1 2 3 4 5 67 8 9 10 11 12]


Colombian Key in Guatemala Forced Disappearance Case


Por qué los datos casan con la hipótesis de que hubo genocidio


R programming language demands the right use case

Megan Price, director of research, is quoted in this story about the R programming language. “Serious data analysis is not something you’re going to do using a mouse and drop-down boxes,” said HRDAG’s director of research Megan Price. “It’s the kind of thing you’re going to do getting close to the data, getting close to the code and writing some of it yourself.”


Calculations for the Greater Good

Rollins School of Public HealthAs executive director of the Human Rights Data Analysis Group, Megan Price uses statistics to shine the light on human rights abuses.


New Report Raises Questions Over CPD’s Approach to Missing Persons Cases

In this video, Trina Reynolds-Tyler of Invisible Institute talks about her work with HRDAG on the missing persons project in Chicago and Beneath the Surface.


Calculating Body Counts


Epidemiology has theories. We should study them.

With so many dashboards and shiny visualizations, how can an interested non-technical reader find good science among the noise?

The ‘Dirty War Index’ and the Real World of Armed Conflict.

Amelia Hoover, Romesh Silva, Tamy Guberek, and Daniel Guzmán. “The ‘Dirty War Index’ and the Real World of Armed Conflict.” May 23, 2009. © 2009 HRDAG. Creative Commons BY-NC-SA.


In Syrian Conflict, Real-Time Evidence Of Violations


A better statistical estimation of known Syrian war victims

Researchers from Rice University and Duke University are using the tools of statistics and data science in collaboration with Human Rights Data Analysis Group (HRDAG) to accurately and efficiently estimate the number of identified victims killed in the Syrian civil war.

Using records from four databases of people killed in the Syrian war, Chen, Duke statistician and machine learning expert Rebecca Steorts and Rice computer scientist Anshumali Shrivastava estimated there were 191,874 unique individuals documented from March 2011 to April 2014. That’s very close to the estimate of 191,369 compiled in 2014 by HRDAG, a nonprofit that helps build scientifically defensible, evidence-based arguments of human rights violations.


Selection Bias and the Statistical Patterns of Mortality in Conflict.

Megan Price and Patrick Ball. 2015. Statistical Journal of the IAOS 31: 263–272. doi: 10.3233/SJI-150899. © IOS Press and the authors. All rights reserved. Creative Commons BY-NC-SA.


Seeking the Truth with Documentation

The need to establish the truth around events is central to goals of transitional justice, particularly securing accountability, establishing legitimate and effective justice mechanisms, and laying the foundations for a peaceful society. Documentation to provide verifiable and widely accepted accounts of such events is a critical component of establishing this truth, or the multiple truths that may exist for a population. It is difficult to overstate the important role of documentation in transitional justice efforts. If some of what follows sounds familiar, echoing points of previous posts, it is no coincidence.  Documentation, in a word, is the ...

Unbiased algorithms can still be problematic

“Usually, the thing you’re trying to predict in a lot of these cases is something like rearrest,” Lum said. “So even if we are perfectly able to predict that, we’re still left with the problem that the human or systemic or institutional biases are generating biased arrests. And so, you still have to contextualize even your 100 percent accuracy with is the data really measuring what you think it’s measuring? Is the data itself generated by a fair process?”

HRDAG Director of Research Patrick Ball, in agreement with Lum, argued that it’s perhaps more practical to move it away from bias at the individual level and instead call it bias at the institutional or structural level. If a police department, for example, is convinced it needs to police one neighborhood more than another, it’s not as relevant if that officer is a racist individual, he said.


What HBR Gets Wrong About Algorithms and Bias

“Kristian Lum… organized a workshop together with Elizabeth Bender, a staff attorney for the NY Legal Aid Society and former public defender, and Terrence Wilkerson, an innocent man who had been arrested and could not afford bail. Together, they shared first hand experience about the obstacles and inefficiencies that occur in the legal system, providing valuable context to the debate around COMPAS.”


Justice Served in Guatemala: Testimonies from The National Security Archive & Benetech’s Human Rights Data Analysis Group


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.

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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