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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.
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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.
Partners
How we work with partners is how we relate to the whole human rights community. We work with human rights advocates and defenders to support their goals by complementing their substantive expertise with our technical expertise. To date, partners have included truth commissions, international criminal tribunals, United Nations missions, and non-governmental human rights organizations on five continents.
Here are a few stories that illustrate how we work with our partners:
HRDAG partner stories:
Quantifying Police Misconduct in Louisiana (2023)
Scraping for Pattern: Protecting Immigrant Rights in Washington State (2022)
Police Violence ...
Announcing New HRDAG Advisory Board Member
Cynthia Conti-Cook came on board in March, 2025.
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 ...
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. ...
To predict and serve?
Kristian Lum and William Isaac (2016). To predict and serve? Significance. October 10, 2016. © 2016 The Royal Statistical Society.
Kristian Lum and William Isaac (2016). To predict and serve? Significance. October 10, 2016. © 2016 The Royal Statistical Society.
Social Science Scholars Award for HRDAG Book
In March 2013, I entered a contest called the California Series in Public Anthropology International Competition, which solicits book proposals from social science scholars who write about how social scientists create meaningful change. The winners of the Series are awarded a publishing contract with the University of California Press for a book targeted to undergraduates. With the encouragement of my HRDAG colleagues Patrick Ball and Megan Price, I proposed a book about the work of HRDAG researchers entitled, Everybody Counts: How Scientists Document the Unknown Victims of Political Violence. Earlier this month, I was contacted by the Series judges ...
Data Mining for Good: CJA Drink + Think
At the Center for Justice and Accountability's happy hour, "Drink and Think," Patrick Ball spoke about "Data Mining for Good." The talk included a discussion of how HRDAG brings human rights abusers to justice through data analysis, and HRDAG's work conducting quantitative analysis for truth commissions, NGOs, the UN and other partners. The event was held at Eventbrite. More photos are below.
The Center for Justice and Accountability
Young Professionals' Committee for Human Rights
September 16, 2014
San Francisco, California
Link to CJA event page
Back to Talks
All photos © 2014 Carter Brooks.
Syria 2012 – Modeling Multiple Datasets in an Ongoing Conflict
The struggle between Syrian President Bashar al-Assad's regime and opposition forces has generated extensive global press coverage, but few accurate estimates of casualties. In January 2013, the United Nations Office of the High Commissioner for Human Rights (OHCHR) released a report on the number of conflict-related killings in Syria. The UN report is based on statistical analysis conducted by HRDAG scientists Megan Price, Jeff Klingner and Patrick Ball. This chapter examines HRDAG’s findings which compared information from a database collected by the Syrian government with six databases compiled by Syrian human rights activists and citizen ...
Predictive policing violates more than it protects
William Isaac and Kristian Lum. Predictive policing violates more than it protects. USA Today. December 2, 2016. © USA Today.
William Isaac and Kristian Lum. Predictive policing violates more than it protects. USA Today. December 2, 2016. © USA Today.
Setting the Record Straight on Predictive Policing and Race
William Isaac and Kristian Lum (2018). Setting the Record Straight on Predictive Policing and Race. In Justice Today. 3 January 2018. © 2018 In Justice Today / Medium.
William Isaac and Kristian Lum (2018). Setting the Record Straight on Predictive Policing and Race. In Justice Today. 3 January 2018. © 2018 In Justice Today / Medium.
In Solidarity
We stand with our partners and every organizer fighting for justice.
Newsletters
2025
24 August 2025 - Structural Zero 03: Without Encryption, My Work Wouldn’t Be Possible
17 July 2025 - Structural Zero 02: Scatter and keep working
3 June 2025 - Structural Zero 01: Dictatorships create a lot of data
24 June, 2025 - Breaking through the noise with evidence
19 May 2025 - Structural Zero 00: Introducing Structural Zero
20 March, 2025 - Focus on HRDAG’s US-based projects
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How Structuring Data Unburies Critical Louisiana Police Misconduct Data
In Orleans Parish, Louisiana, home of New Orleans, 78 percent of wrongful convictions have been linked to a police officer’s failure to share exculpatory evidence with the defense. This is a rate more than double the national average.But while these actions, or any misconduct, by law enforcement personnel may be recorded officially, the data may be difficult to use or find. Depending on a parish’s resources, the data may be archived in a non-digital format, for example, on paper.
Innocence Project New Orleans (IPNO) has as its mission the overturning of wrongful convictions in Louisiana. A police officer involved in a wrongful conviction may ...
Data coding and inter-rater reliability (IRR)
Data coding is the process of converting unstructured information, such as a narrative testimony, into discrete facts such as names and roles of actors (victims, witnesses, perpetrators) in crimes, as well as the date and place of act. Data coding must not discard or distort information. When more than one person is identifying, classifying and counting the elements reported in a qualitative source, the results of what they find may differ slightly based on each individual's interpretation and care in doing the coding. These differences can be measured by measuring IRR (inter-rater reliability). We give the same source document to several coders and ...
Evaluating gunshot detection technology
Bailey’s analysis stemmed from data we had access to as part of our ongoing collaboration with the Invisible Institute.
The Limits of Observation for Understanding Mass Violence.
Megan Price and Patrick Ball. 2015. Canadian Journal of Law and Society / Revue Canadienne Droit et Société volume 30 issue 2 (June): 1-21. doi:10.1017/cls.2015.24. © Cambridge University Press. All rights reserved. Restricted access.
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.
Publications
From time to time, we issue our own scientific reports that focus on the statistical aspects of the data analysis we have done in support of our partners. These reports are non-partisan, and they leave the work of advocacy to our partners.
You can search our publications by keyword or by year.