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Help HRDAG use data science to work for justice, accountability, and human rights. We are nonpartisan and nonprofit, but we are not neutral; we are always on the side of human rights.
Cryptocurrency donations to 501(c)3 charities receive the same tax treatment as stocks. Your donation is a non-taxable event, meaning you do not owe capital gains tax on the appreciated amount and can deduct it on your taxes. This makes Bitcoin and other cryptocurrency donations one of the most tax efficient ways to support us.
We are a team of experts in machine learning, applied and mathematical statistics, computer science, demography, and social science, and ...
HRDAG Retreat 2022
A week in the California redwoods amongst a hodgepodge of people united by their passion for using quantitative analysis to combat injustice.
Making Missing Data Visible in Colombia
Valentina Rozo Ángel has worked with HRDAG and the Colombian Truth Commission to acknowledge victims of the 50-year conflict who are not visible or easily counted.
Human Rights and the Decentralized Web
Our partners were eager to learn and talk about emerging decentralized technology.
How Data Scraping Provides Insights into Immigrant Arrests
In Washington State, some law enforcement officers illegally tip off ICE and CBP for civil immigration arrests. HRDAG helped identify where the problematic practices occurred.
Trove to IPFS
IPFS is a peer-to-peer storage network that promotes the resiliency, immutability, and auditability of data. This README explains code written to shepherd the files from janky external USB drives to IPFS.
IN THE FACE OF TYRANNY
Taking a Stand as Data Scientists
As human rights data analysts, we center our moral understanding on the values of the Universal Declaration of Human Rights. We believe that "recognition of the inherent dignity and of the equal and inalienable rights of all members of the human family is the foundation of freedom, justice and peace in the world," as the Declaration's preamble states. This is our guide, and these are our values. For thirty-five years, this has meant using our skills as statisticians and programmers to help other people in their campaigns for truth and justice.
When a doctor sees a sick or injured person, they ...
IN THE FACE OF TYRANNY
Taking a Stand as Data Scientists
As human rights data analysts, we center our moral understanding on the values of the Universal Declaration of Human Rights. We believe that “recognition of the inherent dignity and of the equal and inalienable rights of all members of the human family is the foundation of freedom, justice and peace in the world,” as the Declaration’s preamble states. This is our guide, and these are our values. For thirty-five years, this has meant using our skills as statisticians and programmers to help other people in their campaigns for truth and justice.
When a doctor sees a sick or injured ...
All of the ways we remember: How data scientists hold memory with and for survivors
Those most vulnerable to state violence are already marginalized and undercounted, their experiences ignored or minimized in official sources. To avoid perpetuating these harms in our analyses, we have to find ways to incorporate unofficial data sources and all of the ways we remember.
South America
Colombia
Perú
Timor-Leste FAQs
How do you know that there are more conflict-related deaths than have been reported to the Commission for Reception, Truth and Reconciliation (CAVR, by its Portuguese acronym)?
Where did the method of multiple systems estimation come from?
If you didn't have access to the whole population, how do you know how representative these data are of the entire population? i.e. How do you control for bias?
What are the total conflict-related mortality numbers? How many people were killed and disappeared between 1974 and 1999? And how many people died due to hunger and illness?
What is the margin of error associated with these results?
What is ...
Frequently Asked Questions
Multiple Systems Estimation
What is MSE?
What do you mean by statistical inference?
What is an overlap, and how do we know when lists overlap?
How does MSE find the total number of violations?
How was MSE originally developed?
How does the Benetech Human Rights Program use MSE?
1. What is MSE?
A: Multiple Systems Estimation, or MSE, is a family of techniques for statistical inference. MSE uses the overlaps between several incomplete lists of human rights violations to determine the total number of violations.
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2. What do you mean by statistical inference?
A: ...
Multiple Systems Estimation: The Basics
Multiple systems estimation, or MSE, is a family of techniques for statistical inference. MSE uses the overlaps between several incomplete lists of human rights violations to determine the total number of violations. In this blogpost, and four more to follow, I’ll answer both conceptual and practical questions about this important method. (In posts to follow, questions that refer to specific statistical procedures or debates will be marked, "In depth.") (more…)
Multiple Systems Estimation: Does it Really Work?
<< Previous post, MSE: Stratification and Estimation
Q15. Are there other MSE models one might use with human rights data?
Q16. Is it possible to use MSE to model non-lethal human rights violations?
Q17. I am concerned about using MSE with my data, because the datasets were gathered by opposing organizations. Victims who were reported to an NGO were very unlikely to be reported to state sources, but also very likely to be reported to religious organizations. Won't that cause the overlaps between the NGO list and the state list to be artificially low, and the overlaps between the NGO list and the church list to be artificially high? Does ...
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. ...
How We Choose Projects
For more than 20 years, HRDAG has been carving out a niche in the international human rights movement. We know what we’re good at and what we’re not qualified to do. We know what quantitative questions we think are important for the community, and we know what we like to do. These preferences guide us as we consider whether to take on a project. We’re scientists, so our priorities will come as no surprise. We like to stick to science (not ideology), avoid advocacy, answer quantifiable questions, and increase our scientific understanding.
While we have no hard-and-fast rules about what projects to take on, we organize our deliberation ...
How We Choose Projects
For more than 20 years, HRDAG has been carving out a niche in the international human rights movement. We know what we’re good at and what we’re not qualified to do. We know what quantitative questions we think are important for the community, and we know what we like to do. These preferences guide us as we consider whether to take on a project. We’re scientists, so our priorities will come as no surprise. We like to stick to science (not ideology), avoid advocacy, answer quantifiable questions, and increase our scientific understanding.
While we have no hard-and-fast rules about what projects to take on, we organize our deliberation ...
Counting Civilian Casualties: An Introduction to Recording and Estimating Nonmilitary Deaths in Conflict
ed. by Taylor B. Seybolt, Jay D. Aronson, and Baruch Fischhoff. Oxford University Press. © 2013 Oxford University Press. All rights reserved.
The following four chapters are included:
— Todd Landman and Anita Gohdes (2013). “A Matter of Convenience: Challenges of Non-Random Data in Analyzing Human Rights Violations in Peru and Sierra Leone.”
— Jeff Klingner and Romesh Silva (2013). “Combining Found Data and Surveys to Measure Conflict Mortality.”
— Daniel Manrique-Vallier, Megan E. Price, and Anita Gohdes (2013). “Multiple-Systems Estimation Techniques for Estimating Casualties in Armed Conflict.”
— Jule Krüger, Patrick Ball, Megan Price, and Amelia Hoover Green (2013). “It Doesn’t Add Up: Methodological and Policy Implications of Conflicting Casualty Data.”
Our Story
Dec 10, 1991
HRDAG is born when Patrick Ball begins database design at the Human Rights Office of the Salvadoran Lutheran Church. The work soon moves to the non-governmental Human Rights Commission (CDHES). The database analysis identified the 100 worst officers in the Salvadoran military — who were forced to resign as part of the peace process.
1994
Patrick publishes A Definit...
Stephen Fienberg 1942-2016
We are saddened by the passing of Steve Fienberg yesterday in Pittsburgh, at the age of 74. He is perhaps best known around the world for bringing statistics to science and public policy and was a beloved professor at Carnegie Mellon University. At HRDAG we are in awe of and grateful for the work Steve did formalizing multiple systems estimation. His work on that front blazed a trail and essentially enabled all of our most important analytical work at the intersection of human rights and statistical science.
If we are to reduce the amount of human violence in the world, the first task is to determine the scope of the violence, to know how much of ...