HRDAG is currently evaluating the quality and completeness of the Kosovo Memory Book of the Humanitarian Law Center (HLC) in Belgrade, Serbia. The objective of the Kosovo Memory Book (KMB) is to commemorate every single person who fell victim to armed conflict in Kosovo from 1998 to 2000, either through death or disappearance.
While building and reviewing their database, one of the things that HLC has to do is “record linkage,” a process also known as “matching.” Matching determines whether two records are the same people (“a match”) or different people (“a non-match”). Matching helps to identify whether two existing records refer ...
Issues surrounding policing in the United States are at the forefront of our national attention. Among these is the use of “predictive policing,” which is the application of statistical or machine learning models to police data, with the goal of predicting where or by whom crime will be committed in the future. Today Significance magazine published an article on this topic that I co-authored with William Isaac. Significance has kindly made this article open access (free!) for all of October. In the article we demonstrate the mechanism by which the use of predictive policing software may amplify the biases that already pervade our criminal ...
Ten data nerds gathered in a large hilltop beach house to analyze counts of killings from several war-torn countries. The time was January 16-20, 2014, the place was near San Francisco, the agenda was packed, and I was excited to be there.
Having defended my dissertation at Carnegie Mellon University just days before, I had often supposed that my thesis on a generalization of
log-linear models for capture-recapture might serve little other purpose than to fill a line on my curriculum vitae. This perception faded after a mid-2013 discussion with Patrick convinced me that HRDAG's data challenges could easily be the best match to my research ...
Version date: 2000.01.29
Current version: ATV20.1
Patrick Ball & Herbert F. Spirer
v_ind
-------------+-----------
Victim |
Ethnic |
category |
| Freq.
-------------+-----------
1 Indigenous | 2,722
2 Ladino | 1,014
3 Unknown | 13,687
|
Total | 17,423
-------------+-----------
v_sex
----------+-----------
Victim |
Sex | Freq.
----------+-----------
4 F | 2,001
5 M | 11,445
6 d | 3,977
|
Total | 17,423
----------+-----------
v_eth
-------------+-----------
Victim |
Maternal |
language ...
Las estimaciones se estratificaron por ubicación y perpetrador.
We work around the world
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Q15. Are there other MSE models one might use with human rights data?
Q16. Is it possible to use MSE to model non-lethal human rights violations?
Q17. I am concerned about using MSE with my data, because the datasets were gathered by opposing organizations. Victims who were reported to an NGO were very unlikely to be reported to state sources, but also very likely to be reported to religious organizations. Won't that cause the overlaps between the NGO list and the state list to be artificially low, and the overlaps between the NGO list and the church list to be artificially high? Does ...
For years I have been engaged in a quantitative study at Guatemala’s Historic Archive of the National Police, or AHPN. (See the blogposts below.) In this study coders collect data on sheets of paper according to criteria established and explained in manuals. But when collecting data, there’s always room for human error—this is why the validity of the study hinges on verifying that coders use the correct criteria.
It is important to mention that the mainstay of coding is the use of a controlled vocabulary. A controlled vocabulary gives analysts a framework, or frame of reference, when converting qualitative information into categories ...
The American Statistical Association’s 2018 Karl E. Peace Award for Outstanding Statistical Contributions for the Betterment of Society recently recognized the work of leading human rights mathematician Patrick Ball of the Human Rights Data Analysis Group (HRDAG). The award is presented annually to statisticians whose exemplary statistical research is matched by the impact their work has had on the lives of people.
Established by the family of Karl E. Peace in honor of his work for the good of society, the award—announced at the Joint Statistical Meetings—is bestowed upon distinguished individual(s) who have made substantial contributions to the statistical profession, contributions that have led in direct ways to improving the human condition. Recipients will have demonstrated through their accomplishments their commitment to service for the greater good.”
This year, Ball became the 10th recipient of the award. Read more …
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.”
What is a controlled vocabulary?
A controlled vocabulary provides the ability to transform information that has been collected on violations, victims, and perpetrators into a countable set of data categories. It is important that this process be done without discarding relevant information and without misrepresenting the collected information.
Why is it necessary?
The data collected about human rights violations originates from a wide range of information sources – legal case files, newspaper articles, e-mails, faxes, letters, phone conversations, testimonies, interviews, radio and television programs, video clips, and photos. This wide range of ...
“I was always a math nerd. My mother has a polaroid of me in the fourth grade with my science fair project … . It was the history of mathematics. In college, I was a math major for a year and then switched to statistics.
I always wanted to work in social justice. I was raised by hippies, went to protests when I was young. I always felt I had an obligation to make the world a little bit better.”
Work by HRDAG researchers Kristian Lum and William Isaac is cited in this article about the Policing Project: “While this bias knows no color or socioeconomic class, Lum and her HRDAG colleague William Isaac demonstrate that it can lead to policing that unfairly targets minorities and those living in poorer neighborhoods.”
Coverage of Megan Price at the Women in Data Science Conference held at Stanford University. “Price discussed her organization’s behind-the-scenes work to collect and analyze data on the ground for human rights advocacy organizations. HRDAG partners with a wide variety of human rights organizations, including local grassroots non-governmental groups and—most notably—multiple branches of the United Nations.”
Using multiple system estimation, we estimate the total population of social movement leaders killed in Colombia during 2018.
The Rafto Foundation, an international human rights organization, has bestowed the 2021 Rafto Prize to HRDAG for its distinguished work defending human rights and democracy.
With HRDAG's help, the University of Washington Center for Human Rights team has been able to analyze the scraped text and search for key words such as “jail” in order to gain insight into where immigration arrests are being made.
