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It’s inevitable that databases will have information gaps, and special care must be taken to account for these gaps.
Cory Doctorow of Boing Boing writes about HRDAG director of research Patrick Ball’s article “Violence in Blue,” published March 4 in Granta. From the post: “In a must-read article in Granta, Ball explains the fundamentals of statistical estimation, and then applies these techniques to US police killings, merging data-sets from the police and the press to arrive at an estimate of the knowable US police homicides (about 1,250/year) and the true total (about 1,500/year). That means that of all the killings by strangers in the USA, one third are committed by the police.”
In this free, downloadable report, Mike Barlow of O’Reilly Media cites several examples of how data and the work of data scientists have made a measurable impact on organizations such as DataKind, a group that connects socially minded data scientists with organizations working to address critical humanitarian issues. HRDAG—and executive director Megan Price—is one of the first organizations whose work is mentioned.
If we could glean key missing information from those fields, we would be able to use more records.
The institution’s objectives were to learn the truth about what happened during the armed conflict.
Upcoming Talks
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2015
Presentation on the research behind the Evaluation of the Kosovo Memory Book Database. National Archive, Pristina, Kosovo. Patrick Ball. February 4, 2015.
How do we know what we know? Patrick Ball. Arizona State University. January, 2015.
AAAS Science & Human Rights Coalition Meeting: Big Data & Human Rights. Megan Price, panelist. Washington, D.C. January 15-16, 2015.
Examining the Crisis in Syria: Conference Hosted by New America and Arizona State University’s Center on the Future of War and the Walter Cronkite School of Journalism and Mass Communication. Megan Price, panelist. Washingt...
This post describes how we organize our work over ten years, twenty analysts, dozens of countries, and hundreds of projects: we start with a task. A task is a single chunk of work, a quantum of workflow. Each task is self-contained and self-documenting; I'll talk about these ideas at length below. We try to keep each task as small as possible, which makes it easy to understand what the task is doing, and how to test whether the results are correct.
In the example I'll describe here, I'm going to describe work from our Syria database matching project, which includes about 100 tasks. I'll start with the first thing we do with files we receive ...
When people talk about war criminals in Guatemala, which war are they talking about?
They’re talking about the Guatemalan civil war, which began in 1960 and ended in 1996. That’s thirty-six years of civil war. Even though it ended almost two decades ago, Guatemala is still recovering from it. At its simplest, this civil war story was right-wing government forces fighting leftist rebels. But it went deeper than that, of course. The majority of the rebel forces was composed of indigenous peoples, primarily the Maya, (more…)
Patrick Ball expanded his use of multiple systems estimation (MSE) to clarify the history of a deadly conflict in Kosovo. The violence began in 1989 when Serbian President Slobodan Milošević revoked Kosovo's autonomous status within the Republic of Serbia triggering fighting between Kosovar Albanians and the Yugoslav government. Allegations of widespread and systematic human rights violations were made against Serbian forces and NATO intervened to repel Serb forces from Kosovo. Ball and Scheuren gathered data from Albanian border crossings and other sources in the region. They used this information to examine the claim by the Yugoslav government ...
The goal of this project is identify Mexican municipalities with a high probability of having clandestine graves. Knowing where to search will help to create better public programs regarding missing persons in Mexico.
At HRDAG, we worry about what we don't know. Specifically, we worry about how we can use statistical techniques to estimate homicides that are not observed by human rights groups. Based on what we've seen studying many conflicts over the last 25 years, what we don't know is often quite different from what we do know.
The technique we use most often to estimate what we don't know is called "multiple systems estimation." In this medium-technical post, I explain how to organize data and use three R packages to estimate unobserved events.
Click here for Computing Multiple Systems Estimation in R.
We’ve
built a model for estimating the true number of positives, using what we have determined to be the most reliable datasets—deaths.
How we built a model to search hundreds of thousands of text messages from the perpetrators of a human rights crime.
The other data is in three files. All of the files are comma-delimited UTF-8 (like ASCII but including the characters to render Serbian names). The fields in each file are described below.
If you use these data, please cite them with the following citation, as well as this note:
“These are convenience sample data, and as such they are not a statistically representative sample of events in this conflict. These data do not support conclusions about patterns, trends, or other substantive comparisons (such as over time, space, ethnicity, age, etc.).”
Human Rights Data Analysis Group. (2002). Database of NATO airstrikes, geographic coding, and KLA ...
Data integration and statistical estimation: A collaboration with the Colombian Truth Commission (CEV) and the Special Jurisdiction for Peace (JEP)
Colombia and the guerrilla of the Revolutionary Armed Forces of Colombia (FARC) reached a Peace Agreement in 2016, which created the Commission for the Clarification of the Truth, Coexistence and Non-Repetition (CEV). The objective of this temporary institution was to discover the truth of what happened in the context of the armed conflict.
2020-2022: The Truth Commission joined with the Special Jurisdiction for Peace (JEP) and HRDAG in the "JEP-CEV-HRDAG data integration and statistical estimation" ...
2021 Rafto Prize Videos
.ugb-8203b62 .ugb-video-popup__wrapper{height:460px !important;background-color:#000000;background-image:url(https://hrdag.org/wp-content/uploads/2022/12/Screen-Shot-2022-12-09-at-3.41.30-PM.png)}.ugb-8203b62 .ugb-video-popup__wrapper:before{background-color:#000000;opacity:0.3}.ugb-8203b62 .ugb-video-popup__wrapper:hover:before{opacity:0.6}.ugb-8203b62 .ugb-block-title{color:#ffffff}.ugb-8203b62 .ugb-block-description{color:#ffffff}@media screen and (max-width:768px){.ugb-8203b62 .ugb-video-popup__wrapper{height:208px !important}}The Rafto Prize 2021 | Rafto Foundation Rafto Foundation | HRDAG team | 2021 | 4 min
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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 ...
As noted on our Core Concepts page, we spend a lot of time worrying about the ways data are used to make claims about human rights violations. This is because inaccurate statistics can damage the credibility of human rights claims. Analyses of records of human rights violations are used to guide policy decisions, determine resource allocation for interventions, and inform transitional justice mechanisms. It is vital that such analyses are accurate.
Unfortunately, all too often these decisions are based, inappropriately, on analyses of a single convenience sample. (more…)
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
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 ...