655 results for search: %E3%80%8C%ED%98%84%EB%AA%85%ED%95%9C%20%ED%8F%B0%ED%8C%85%E3%80%8D%20O6O~5OO~%C6%BC469%20%2049%EC%82%B4%EB%82%A8%EC%84%B1%EC%84%B9%ED%8C%8C%EB%8D%B0%EC%9D%B4%ED%8C%85%2049%EC%82%B4%EB%82%A8%EC%84%B1%EC%84%B9%ED%8C%8C%EB%8F%99%EC%95%84%EB%A6%AC%E2%98%9C49%EC%82%B4%EB%82%A8%EC%84%B1%EC%84%B9%ED%8C%8C%EB%8F%99%ED%98%B8%ED%9A%8C%E2%96%9349%EC%82%B4%EB%82%A8%EC%84%B1%EC%84%B9%ED%8C%8C%EB%A7%8C%EB%82%A8%E2%93%A5%E3%82%89%E5%BF%A6hybridity/feed/content/colombia/copyright
Documents of war: Understanding the Syrian Conflict
Megan Price, Anita Gohdes, and Patrick Ball. 2015. Significance 12, no. 2 (April): 14–19. doi: 10.1111/j.1740-9713.2015.00811.x. © 2015 The Royal Statistical Society. All rights reserved. [online abstract]
Liberian Truth and Reconciliation Commission Data
In July 2009, The Human Rights Data Analysis Group concluded a three-year project with the Liberian Truth and Reconciliation Commission to help clarify Liberia’s violent history and hold perpetrators of human rights abuses accountable for their actions. In the course of this work, HRDAG analyzed more than 17,000 victim and witness statements collected by the Liberian Truth and Reconciliation Commission and compiled the data into a report entitled “Descriptive Statistics From Statements to the Liberian Truth and Reconciliation Commission.”
Liberian TRC data and the accompanying data dictionary
anonymized-statgivers.csv contains information ...
How Structuring Data Unburies Critical Louisiana Police Misconduct Data
In Louisiana, appeals for police disciplinary action are often buried in meeting minutes. HRDAG uses machine learning to extract, structure data and make it searchable..
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.
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.
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 ...
Update of Iraq and Syria Data in New Paper
This week The Statistical Journal of the IAOS published a new(ish) paper by Megan Price and Patrick Ball. The open-access paper, Selection bias and the statistical patterns of mortality in conflict, is a revisiting and updating of both the Iraq and Syria examples used in an earlier paper, Big Data, Selection Bias, and the Statistical Patterns of Mortality in Conflict, which was published last year inThe SAIS Review of International Affairs (JHU Press, 2014).
HRDAG believes that the concerns highlighted by these examples are important for a wide variety of audiences, including both the foreign policy readers reached by The SAIS Review and the ...
Get Involved/Donate
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.)
This transaction will appear on your credit card statement as "Network for Good."
If you donate by check, ...
Contact Us
You may contact us via info @ hrdag.org or use this form.
Would you like to receive our newsletter?
Great! Please sign up here.
Find us on Mastodon
Follow HRDAG on Mastodon.
Employment with HRDAG
Please keep in touch by signing up for our newsletters and following us on Twitter @hrdag or Mastodon.
If you do not see a job listed here, please do not send your CV or résumé, as we do not file or save them, and we will only have to send you a sad “no thank you” letter.
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
Stay informed about our work
#mc_embed_signup{background:#fff; clear:left; font:14px Helvetica,Arial,sans-serif; }
/* Add your own Mailchimp form style overrides in your site stylesheet or in this style block.
We recommend moving this block and the preceding CSS link to the HEAD of your HTML file. */
#mc_embed_signup .mc-field-group input {
display: block;
width: 100%;
padding: 8px 0;
text-indent: 2%;
color: #333 !important;
}
Subscribe
* indicates required
Email Address *
First Name
Last Name
Organization
(function($) {window.fnames = new ...
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.
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. ...
Guatemala CIIDH Data
Welcome to the web data resource for the International Center for Human Rights Research (Centro Internacional para Investigaciones en Derechos Humanos, or CIIDH). Here you will find raw data on human rights violations in Guatemala during the period 1960-1996. You're welcome to use it for your own statistical analyses.
ASCII delimited (csv)
Resource Information
Data Dictionary
Value Labels
File Structure (Variables)
These files are between 300-700 kilobytes. The data are stored in a zipped compression format.
For an explanation of how the data are structured and what the variables represent, see the data dictionary.
If you use ...
Haiti
In 1995, the Haitian National Commission for Truth and Justice (CNVJ) requested the advice of the American Association for the Advancement of Science (AAAS) and Dr. Patrick Ball on how to develop a large-scale project to take the testimonies of several thousand witnesses of human rights abuses in Haiti.
The team conducted work incorporating over 5,000 interviews covering over 8,500 victims to produce detailed regional analyses, using quantitative material from the interviews, historical, economic and demographic analysis.
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.
South Africa
Under apartheid, South Africans from all sides suffered violence and human rights abuses. One of the mandates of the the South African Truth and Reconciliation Commission (TRC) was to report truth by reporting on violations and victims.
Dr. Patrick Ball, as Deputy Director of the Science and Human Rights Program (SHRP) of the American Association for the Advancement of Science (AAAS), used the who-did-what-to-whom data model to provide statistical analysis of the violations reported to the Commission, for use in the final report of the TRC.
Links:
http://shr.aaas.org/southafrica/trcsa/
http://www.doj.gov.za/trc/index....
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.”