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Rapid response to: Civilian deaths from weapons used in the Syrian conflict
On November 4, 2015, the BMJ published our "Rapid Response" to Civilian deaths from weapons used in the Syrian conflict (BMJ 2015;351:h4736). The response was co-authored by Megan Price, Anita Gohdes, Jay Aronson (Carnegie Mellon University, Center for Human Rights Science), and Christopher McNaboe (Carter Center, Syria Conflict Mapping Project).
We have three concerns about this article. First, the article apportions responsibility for casualties to particular perpetrator organizations based on a single snapshot of territorial control that ignores the numerous (and well-documented) changes in this phenomenon over time. Second, combining Syrian ...
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.
Lies, Damned Lies and Official Statistics
This essay in the Health and Human Rights Journal addresses attempts to undermine Covid-19 data collection.
Big Data Predictive Analytics Comes to Academic and Nonprofit Institutions to Fuel Innovation
"Revolution Analytics will allow HRDAG to handle bigger data sets and leverage the power of R to accomplish this goal and uncover the truth." Director of Research Megan Price is quoted.
REVOLUTION ANALYTICS
Press release
February 4, 2014
Link to press release
Back to Press Room
How Machine Learning Protects Whistle-Blowers in Staten Island
People filed complaints against NYPD officers, and HRDAG went above and beyond to protect the privacy of the people who reported the offenses.
Casanare, Colombia
Estimates of Killings and Disappearances in Casanare
Casanare is a large, rural department or state in Colombia that includes 19 municipalities and a population of almost 300,000 inhabitants. Located in the foothills of the Andes and on the eastern plains, Casanare has a history of violence. Multiple armed groups have operated in Casanare including paramilitaries, guerillas and the Colombian military. Many Casanare citizens have suffered violent deaths and disappearances.
But how many people have been killed or disappeared? For reasons of policy, accountability and historical clarification, this question deserves a valid answer. In February ...
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 ...
The World According to Artificial Intelligence (Part 1)
The World According to Artificial Intelligence: Targeted by Algorithm (Part 1)
The Big Picture: The World According to AI explores how artificial intelligence is being used today, and what it means to those on its receiving end.
Patrick Ball is interviewed: “Machine learning is pretty good at finding elements out of a huge pool of non-elements… But we’ll get a lot of false positives along the way.”
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 ...
Kosovo
During the conflict between NATO and Yugoslavia in early 1999, hundreds of thousands of people fled Kosovo, and thousands more were killed. Who were the perpetrators? Statistical analysis helped answer this question.
While at the American Association for the Advancement of Science (AAAS), members of the HRDAG team wrote several reports on the conflict. With partners at ABA CEELI (American Bar Association/Central European and Eurasian Law Initiative), HRDAG submitted an expert report that was used in the trial of former Yugoslav president Slobodan Milošević at the ICTY (International Criminal Tribunal for the Former Yugoslavia) in The Hague, ...
Learning to Learn: Reflections on My Time at HRDAG
So much of what I learned at HRDAG was intangible, and I'm grateful to have been able to go deep.
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 ...
HRDAG Testimony in Guatemala Retrials
HRDAG analysis presented by Patrick found that 5 percent of the indigenous Maya Ixil population was killed in a 15-month period.
HRDAG Adds Three New Board Members
HRDAG's advisory board has added three new members.
Mexico
HRDAG and our partners Data Cívica and the Iberoamericana University created a machine-learning model to predict which counties (municipios) in Mexico have the highest probability of unreported hidden graves. The predictions help advocates to bring public attention and government resources to search for the disappeared in the places where they are most likely to be found.
Context
For more than ten years, Mexican authorities have been discovering hidden graves (fosas clandestinas). The casualties are attributed broadly—and sometimes inaccurately—to the country’s “drug war,” but the motivations and perpetrators behind the mass murders ...
Data on Kosovo Killings
The data on killings in Kosovo are in four files. All of the files are comma-delimited ASCII. The fields in each file are described below.
If you use these data on Kosovo killings, please cite them with the following citation, as well as this note:
“These are convenience sample data, and as such they are not a statistically representative sample of events in this conflict. These data do not support conclusions about patterns, trends, or other substantive comparisons (such as over time, space, ethnicity, age, etc.).”
Patrick Ball, Wendy Betts, Fritz Scheuren, Jana Dudukovich, and Jana Asher. (2002). AAAS/ABA-CEELI/Human Rights Data ...
Why raw data doesn't support analysis of violence
This morning I got a query from a journalist asking for our data from the report we published yesterday. The journalist was hoping to create an interactive infographic to track the number of deaths in the Syrian conflict over time. Our data would not support an analysis like the one proposed, so I wrote this reply.
We can't send you these data because they would be misleading—seriously misleading—for the purpose you describe. Here's why:
What we have is a list of documented deaths, in essence, a highly non-random sample, though a very big one. We like bigger samples because we think that they must be closer to true. The mathematical justificat...