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/wp-content/uploads/2013/01/Definition_of_Database_Design_Standards_1994.pdf
Patrick Ball. “A Definition of Database Design Standards for Human Rights Agencies.” © 1994 American Association for the Advancement of Science. [pdf]
HRDAG built a machine-learning tool to strip the raw data of any potentially identifying information such as names and court case numbers. There was no "acceptable error rate."
The modular nature of the workflow and use of Git allowed us to work on different parts of the project from across the country.
“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.
Doing an investigation on the contents of the Archive brought with it three major lessons. The first big lesson was the constant movement (nothing was static), The second great lesson was that everything evolved (the changes were a constant). The third major lesson was to discover how two institutions can work together while geographically far apart.
The constant movement
As there were other processes being carried out at the Archive, everything was in constant movement. In other words, one day the documents were in X location and tomorrow they may be in location Y or dispersed in multiple locations. This made it impossible to know with certai...
Access to the records contained in archives is a concern shared by many. Archives support memory and free access to them strengthens democratic processes. Everyone should be allowed to see first-hand the records contained in an archive and be free to interpret them as needed.
Access to archives can increase knowledge on various topics and opens opportunities for different fields of knowledge. (more…)
Patrick Ball won the Karl E. Peace Award for Outstanding Statistical Contributions for the Betterment of Society at the 2018 Joint Statistical Meeting.
I will use the skills and culture I learned from HRDAG’s team to understand how the conflict has affected the people in my country.
On Wednesday, April 9, the file hosting service Dropbox announced the addition of Condoleezza Rice, former U.S. National Security Advisor and Secretary of State, to their Board of Directors, citing the need for “a leader who could help us expand our global footprint.”
In response to this announcement, HRDAG requested (and rapidly received) a refund for our recent purchase of Dropbox for Business, and will drop the use of their service entirely.
Patrick Ball, HRDAG’s Executive Director stated: “As a human rights organization, we find Condoleezza Rice's complicity in the serious human rights abuses of the Bush administration very worrying. ...
After almost two months of searching for the perfect fit, we’re very pleased to announce that Josh Shadlen has joined HRDAG as our new technical lead. Finding Josh was no easy feat. We were looking for what many people would call a “data scientist,” that is, someone with expertise in both computer science and statistics. These days, “data science” is one of the hottest fields out there.
Bringing the perfect mix of academic depth and thoughtful reflection, Josh stood out for us. With prior jobs including gigs at Silicon Valley startups and Twitter, he’s got high-level (more…)
HRDAG's work in Kosovo and in the Guatemalan trial of General José Efraín Ríos Montt is discussed in this article. Megan Price, HRDAG's director of research, is quoted. “There is a wide variety of things that could be considered data,” she says.
From the story:
Price’s main data analysis tool requires fitting a model to the data that ends up in her lap. That way, she can see whether there are gaps in the data and what more needs to be included. The method, called multiple systems estimation analysis, lets Price look at patterns across lists of data, for example, lists of victims. The resulting model reveals how much data is missing, to a ...
HRDAG contributes to the project by helping to classify, filter, extract, and standardize the records so that they can be useful in the database.
I joined the Benetech Human Rights Program at essentially the same time that HRDAG did, coming to Benetech from years of analyzing data for large companies in the transportation, hospitality and retail industries. But the data that HRDAG dealt with was not like the data I was familiar with, and I was fascinated to learn about how they used the data to determine "who did what to whom." Although some of the methodologies were similar to what I had experience with in the for-profit sector, the goals and beneficiaries of the analyses were very different.
At Benetech, I was initially predominantly focused on product management for Martus, a free ...
In 1984, as a fresh PhD, I heard Richard Savage give his presidential address at the Joint Statistical Meetings in Philadelphia. He called it "Hard/Soft Problems" and made a big pitch for statisticians to get involved in human rights data analysis. It was inspirational, and I was immediately sold. I started working with the American Statistical Association's Committee on Scientific Freedom and Human Rights (now chaired by HRDAG's own Megan Price). Over time, a growing set of statisticians became involved, initially in letter-writing campaigns to help dissident statisticians (and other quantitative academics—economists seemed to have a particular ...
But while HRDAG’s estimate relied on the painstaking efforts of human workers to carefully weed out potential duplicate records, hashing with statistical estimation proved to be faster, easier and less expensive. The researchers said hashing also had the important advantage of a sharp confidence interval: The range of error is plus or minus 1,772, or less than 1 percent of the total number of victims.
“The big win from this method is that we can quickly calculate the probable number of unique elements in a dataset with many duplicates,” said Patrick Ball, HRDAG’s director of research. “We can do a lot with this estimate.”
Researchers from Rice University and Duke University are using the tools of statistics and data science in collaboration with Human Rights Data Analysis Group (HRDAG) to accurately and efficiently estimate the number of identified victims killed in the Syrian civil war.
…
Using records from four databases of people killed in the Syrian war, Chen, Duke statistician and machine learning expert Rebecca Steorts and Rice computer scientist Anshumali Shrivastava estimated there were 191,874 unique individuals documented from March 2011 to April 2014. That’s very close to the estimate of 191,369 compiled in 2014 by HRDAG, a nonprofit that helps build scientifically defensible, evidence-based arguments of human rights violations.
Multiple systems estimation, or MSE, is a family of techniques for statistical inference. MSE uses the overlaps between several incomplete lists of human rights violations to determine the total number of violations. In this blogpost, and four more to follow, I’ll answer both conceptual and practical questions about this important method. (In posts to follow, questions that refer to specific statistical procedures or debates will be marked, "In depth.") (more…)
HRDAG assisted the Sierra Leone Truth and Reconciliation Commission in building 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. HRDAG executive director Patrick Ball and HRDAG field consultant Richard Conibere worked at the TRC full-time for approximately eighteen months starting in March 2003.
HRDAG worked with TRC researchers to help them incorporate quantitative findings to support the qualitative findings in their writing for the other chapters of the TRC report. In addition, HRDAG produced a Statistical Appendix to present ...
With help from HRDAG, Roman Rivera built the data backbone for the Invisible Institute's Citizens Police Data Project.
