204 results for search: 가평출장마사지☆[010-8226-1872) 매탄출장마사지✻청라출장마사지●수원출장마사지 일산출장마사지/feed/press-release-tchad-2010jan-fr
State Coordinated Violence in Chad under Hissene Habre: A Statistical Analysis of Reported Prison Mortality in Chad’s DDS Prisons and Command Responsibility of Hissene Habre, 1982-1990.
Romesh Silva, Jeff Klingner, and Scott Weikart. “State Coordinated Violence in Chad under Hissene Habre: A Statistical Analysis of Reported Prison Mortality in Chad’s DDS Prisons and Command Responsibility of Hissene Habre, 1982-1990.” A Report by Benetech’s Human Rights Data Analysis Group to Human Rights Watch and the Chadian Association of Victims of Political Repression and Crimes. 29 January 2010. (Available in French) © 2010 Benetech. Creative Commons BY-NC-SA.
To Count the Uncounted: An Estimation of Lethal Violence in Casanare,
Tamy Guberek, Daniel Guzmán, Megan Price, Kristian Lum and Patrick Ball, “To Count the Uncounted: An Estimation of Lethal Violence in Casanare,” A Report by the Benetech Human Rights Program. 10 February 2010. (Available in Spanish) © 2010 Benetech. Creative Commons BY-NC-SA.
Different Convenience Samples, Different Stories: The Case of Sierra Leone.
Anita Gohdes. “Different Convenience Samples, Different Stories: The Case of Sierra Leone.” Benetech. 2010. © 2010 Benetech. Creative Commons BY-NC-SA.
Comments to the article ‘Is Violence Against Union Members in Colombia Systematic and Targeted?
Megan Price and Daniel Guzmán. “Comments to the article ‘Is Violence Against Union Members in Colombia Systematic and Targeted?’” 28 May 2010. (Available in Spanish) © 2010 Benetech. Creative Commons BY-NC-SA.
Measuring lethal counterinsurgency violence in Amritsar District, India using a referral-based sampling technique
Romesh Silva, Jeff Klingner, and Scott Weikart. “Measuring lethal counterinsurgency violence in Amritsar District, India using a referral-based sampling technique.” In JSM Proceedings, Social Statistics Section. Alexandria, VA: American Statistical Association, 2010. © 201o JSM. All rights reserved.
Talks
Learning to Learn: Reflections on My Time at HRDAG
Ouster of Guatemala’s Attorney General
How we make sure that nobody is counted twice: A peek into HRDAG's record de-duplication
Connect with HRDAG
How we go about estimating casualties in Syria—Part 1
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.
