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Update on Work in Guatemala and the AHPN
HRDAG has sampled and analyzed documents at Guatemala's AHPN and has testified against war criminals based on that analysis.
Violence in Blue: The 2020 Update
HRDAG has refreshed a 2016 Granta article about homicides committed by police in the United States.
Reflections: A Simple Plan
I got an email from my superheroic PhD adviser in June 2006: Would I be interested in relocating to Palo Alto for six months in order to work with Patrick Ball at the Human Rights Data Analysis Group? (She'd gotten a grant and would cover my stipend.) Since I'd spent the last several months in New Haven wrestling ineffectually with giant, brain-melting methodological problems, I said yes immediately.
The plan with my adviser was simple: I'd digitize the ancient, multiply-photocopied pages of data from the United Nations Truth Commission for El Salvador, combine them with two other datasets, match across all the records, and produce reliable ...
Learning Day by Day: Quantitative Research at the AHPN
Working at the Historic Archive of the National Police (AHPN) of Guatemala, there are many skills I learned on the job. My many years of work on the team that studies the recovered documents have been like a custom-made course in how to do quantitative research.
The Archive documents I study are the result of 36 years of creation during civil war (1960 to 1996). Many of these documents are simply administrative—but we are able to use them to understand patterns that occurred during the conflict, to get a sense of what mattered to the National Police and what didn’t. Our quantitative research shows us the Police behavior in broad strokes. ...
Tech Corner
The HRDAG Tech Corner is where we collect the deeper and geekier content that we create for the website. Click the accordion blocks below to reveal each of the Tech Corner entries.
Sifting Massive Datasets with Machine Learning
Principled Data Processing
Welcoming Our 2021-2022 Human Rights and Data Science Intern
Larry Barrett has joined HRDAG as a Human Rights and Data Science Intern until February, 2022.
Reflections: Challenging Tasks and Meticulous Defenders
I have made it my personal objective to amplify HRDAG's message of being extra careful and scientifically rigorous with human rights data.
Multiple Systems Estimation: The Matching Process
<<Previous post: Collection, Cleaning, and Canonicalization of Data
Q8. What do you mean by "overlap," and why are overlaps important?
Q9. [In depth] Why is automated matching so important, and what process do you use to match records?
Q8. What do you mean by "overlap," and why are overlaps important?
MSE estimates the total number of violations by comparing the size of the overlap(s) between lists of human rights violations to the sizes of the lists themselves. By "overlap," we mean the set of incidents, such as deaths, that appear on more than one list of human rights violations. Accurately and efficiently identifying overlaps between ...
The Truth of Truth Commissions: Comparative Lessons from Haiti, South Africa, and Guatemala.
Audrey Chapman and Patrick Ball. “The Truth of Truth Commissions: Comparative Lessons from Haiti, South Africa, and Guatemala.” Human Rights Quarterly. 23(4):1-42. 2001
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.
A Comparison of Marginal and Conditional Models for Capture–Recapture Data with Application to Human Rights Violations Data
Shira Mitchell, Al Ozonoff, Alan Zaslavsky, Bethany Hedt-Gauthier, Kristian Lum and Brent Coull (2013). A Comparison of Marginal and Conditional Models for Capture-Recapture Data with Application to Human Rights Violations Data. Biometrics, Volume 69, Issue 4, pages 1022–1032, December 2013. © 2013, The International Biometric Society. DOI: 10.1111/biom.12089.
Shira Mitchell, Al Ozonoff, Alan Zaslavsky, Bethany Hedt-Gauthier, Kristian Lum and Brent Coull (2013). A Comparison of Marginal and Conditional Models for Capture-Recapture Data with Application to Human Rights Violations Data. Biometrics, Volume 69, Issue 4, pages 1022–1032, December 2013. © 2013, The International Biometric Society. DOI: 10.1111/biom.12089.
HRDAG’s Year in Review: 2020
In 2020, HRDAG provided clarity on issues related to the pandemic, police misconduct, and more.
Drug-Related Killings in the Philippines
HRDAG analysis shows that the government figures are a gross underestimation of the drug-related killings in the Philippines.
How Causal Analysis Confirmed Impact of Cash Bail on Verdicts
Causal inference methods show that for indigent clients, money bail increases their likelihood of a guilty conviction.
‘Bias deep inside the code’: the problem with AI ‘ethics’ in Silicon Valley
Kristian Lum, the lead statistician at the Human Rights Data Analysis Group, and an expert on algorithmic bias, said she hoped Stanford’s stumble made the institution think more deeply about representation.
“This type of oversight makes me worried that their stated commitment to the other important values and goals – like taking seriously creating AI to serve the ‘collective needs of humanity’ – is also empty PR spin and this will be nothing more than a vanity project for those attached to it,” she wrote in an email.
HRDAG Names New Board Member William Isaac
William Isaac joins HRDAG's Advisory Board, bringing expertise in fairness and artificial intelligence.
The Day We Fight Back
Today, February 11, is the day of national protests against the National Security Administration.
The critical threat is mass surveillance. In the words of The Day We Fight Back, “Together we will push back against powers that seek to observe, collect, and analyze our every digital action. Together, we will make it clear that such behavior is not compatible with democratic governance. Together, if we persist, we will win this fight.” (more…)
HRDAG and #GivingTuesday 2018
Will you help HRDAG advance human rights?
Data Collection and Documentation for Truth-Seeking and Accountability
Megan Price and Patrick Ball (2014). The Syrian Justice and Accountability Centre. © 2014 SJAC.Creative Commons BY-NC-SA.