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On or off the record? Detecting patterns of silence about death in Guatemala’s National Police Archive
Tamy Guberek and Margaret Hedstrom (2017). On or off the record? Detecting patterns of silence about death in Guatemala’s National Police Archive. Archival Science. 9 February 2017. © Springer. DOI 10.1007/s10502-017-9274-3.
Tamy Guberek and Margaret Hedstrom (2017). On or off the record? Detecting patterns of silence about death in Guatemala’s National Police Archive. Archival Science. 9 February 2017. © Springer. DOI 10.1007/s10502-017-9274-3.
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.
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 ...
Uncertainty in COVID Fatality Rates
In this Granta article, HRDAG explains that neither the infectiousness nor the deadliness of the disease is set in stone.
Introducing Structural Zero, HRDAG’s New Monthly Newsletter
I want to invite you to check out HRDAG's new newsletter, Structural Zero. It’s written by me and my colleagues Megan Price, Bailey Passmore, Tarak Shah, and Maria Gargiulo. Each month, one of us will write about a mathematical or scientific concept we use in our work and how it can be applied to understanding the world. We’ll offer some of the real world examples we've come across, including the times when we or our partners worked to collect and process data in very dangerous situations. We’ll talk about some of the key insights we've uncovered through our work, and the cultural context for understanding what those insights mean.
You ...
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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.)
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Volunteering with HRDAG
Are you interested in volunteering your time to the Human Rights Data Analysis Group? We’re very flattered—but at this time we’re ...
New death toll estimated in Syrian civil war
Kevin Uhrmacher of the Washington Post prepared a graph that illustrates reported deaths over time, by number of organizations reporting the deaths.
Washington Post
Kevin Uhrmacher
August 22, 2014
Link to story on Washington Post
Related blogpost (Updated Casualty Count for Syria)
Back to Press Room
Why It Took So Long To Update the U.N.-Sponsored Syria Death Count
In this story, Carl Bialik of FiveThirtyEight interviews HRDAG executive director Patrick Ball about the process of de-duplication, integration of databases, and machine-learning in the recent enumeration of reported casualties in Syria.
New reports of old deaths come in all the time, Ball said, making it tough to maintain a database. The duplicate-removal process means “it’s a lot like redoing the whole project each time,” he said.
FiveThirtyEight
Carl Bialik
August 23, 2014
Link to story on FiveThirtyEight
Related blogpost (Updated Casualty Count for Syria)
Back to Press Room
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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. ...
Syria’s status, the migrant crisis and talking to ISIS
In this week’s “Top Picks,” IRIN interviews HRDAG executive director Patrick Ball about giant data sets and whether we can trust them. “No matter how big it is, data on violence is always partial,” he says.
Rise of the racist robots – how AI is learning all our worst impulses
“If you’re not careful, you risk automating the exact same biases these programs are supposed to eliminate,” says Kristian Lum, the lead statistician at the San Francisco-based, non-profit Human Rights Data Analysis Group (HRDAG). Last year, Lum and a co-author showed that PredPol, a program for police departments that predicts hotspots where future crime might occur, could potentially get stuck in a feedback loop of over-policing majority black and brown neighbourhoods. The program was “learning” from previous crime reports. For Samuel Sinyangwe, a justice activist and policy researcher, this kind of approach is “especially nefarious” because police can say: “We’re not being biased, we’re just doing what the math tells us.” And the public perception might be that the algorithms are impartial.
Our Copyright Policy
We have specified "Some Rights Reserved" on our website, instead of the more conventional "All Rights Reserved." This is because some of our web content is covered by a Creative Commons license, which means that it may be copied and even re-purposed, with some stipulations. We have made this decision because HRDAG wants to contribute to the digital commons, defined by Creative Commons as "a pool of content that can be copied, distributed, edited, remixed, and built upon, all within the boundaries of copyright law."
Our Creative Commons License
We are using the Attribution-NonCommercial-ShareAlike license, also known as the BY-NC-SA license. Here is ...
Who Did What to Whom? Planning and Implementing a Large Scale Human Rights Data Project
/whodidwhattowhom/contents.html
Patrick Ball. Who Did What to Whom? Planning and Implementing a Large Scale Human Rights Data Project. © 1996 American Association for the Advancement of Science.
Sierra Leone
Following a brutal 11-year civil war, the Parliament of Sierra Leone called for a Truth and Reconciliation Commission (TRC) to create "an impartial, historical record of the conflict", and "address impunity; respond to the needs of victims; promote healing and reconciliation; and prevent a repetition of the violations and abuses suffered." The full text of the TRC report is available on the Sierra Leone Web.
HRDAG assisted the TRC to build 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. Dr. Ball visited Freetown twice, and HRDAG ...
Hunting for Mexico’s mass graves with machine learning
“The model uses obvious predictor variables, Ball says, such as whether or not a drug lab has been busted in that county, or if the county borders the United States, or the ocean, but also includes less-obvious predictor variables such as the percentage of the county that is mountainous, the presence of highways, and the academic results of primary and secondary school students in the county.”