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Always Learning

The data science field is always changing, which means that I'll always be learning.

Killings and Refugee Flow in Kosovo, March–June, 1999 (A report to ICTY).

Patrick Ball, Wendy Betts, Fritz Scheuren, Jana Dudukovic, and Jana Asher. Killings and Refugee Flow in Kosovo, March–June, 1999 (A report to ICTY). © 2002 American Association for the Advancement of Science and American Bar Association Central and East European Law Initiative. [full text]

Timor-Leste 2006 – Combining Found Data and Innovative Surveys To Uncover the Truth

Large-scale human rights violations in Timor-Leste began in 1975 when the Indonesian government invaded the small island and continued until Timorese independence in 1999. Disappearances, torture, forced displacement and extra-judicial killings took place during the Indonesian occupation compounded by a severe famine. Estimates of deaths ranged from 50,000 to 200,000, but individual sources reflected only a fraction of total fatalities. The Commission for Reception, Truth and Reconciliation in East Timor (CAVR) asked HRDAG to investigate abuses during the conflict. This chapter describes how Ball and HRDAG scientists Romesh Silva and Scott Weikart ...

Guatemala 2011 – Developing Sampling Methods to Help Convict Perpetrators

During 36 years of internal armed conflict, which ended in 1996, an estimated 200,000 Guatemalans were killed or disappeared. HRDAG researchers returned to Guatemala in 2006 to analyze a sample of the estimated 46 million records discovered in the archive of the now disbanded Guatemalan National Police. HRDAG statisticians Daniel Guzmán, Romesh Silva, Patrick Ball and Tamy Guberek, together with Paul Zador and Gary Shapiro of the American Statistical Association, developed a multi-stage random sample of the archive to get a clearer picture of its contents. Sampled documents shed light on the disappearance of Guatemalan union leader Edgar Fernando ...

Reflections: The People Who Make the Data

HRDAG associate Miguel Cruz has an epiphany. All those data he’s drowning in? Each datapoint is a personal tragedy, a story both dark and urgent, and he’s privileged to have access.

FAT* Conference 2018

Kristian Lum spoke about "Understanding the Context and Consequences of Pre-Trial Detention" at the Conference on Fairness, Accountability, and Transparency (FAT*).

Learning a Modular, Auditable and Reproducible Workflow

The modular nature of the workflow and use of Git allowed us to work on different parts of the project from across the country.

Layers of Bias: A Unified Approach for Understanding Problems With Risk Assessment

Laurel Eckhouse, Kristian Lum, Cynthia Conti-Cook and Julie Ciccolini (2018). Layers of Bias: A Unified Approach for Understanding Problems With Risk Assessment. Criminal Justice and Behavior. November 23, 2018. © 2018 Sage Journals. All rights reserved. https://doi.org/10.1177/0093854818811379

Laurel Eckhouse, Kristian Lum, Cynthia Conti-Cook and Julie Ciccolini (2018). Layers of Bias: A Unified Approach for Understanding Problems With Risk Assessment. Criminal Justice and Behavior. November 23, 2018. © 2018 Sage Journals. All rights reserved. https://doi.org/10.1177/0093854818811379

The World According to Artificial Intelligence (Part 1)

The World According to Artificial Intelligence: Targeted by Algorithm (Part 1)

The Big Picture: The World According to AI explores how artificial intelligence is being used today, and what it means to those on its receiving end.

Patrick Ball is interviewed: “Machine learning is pretty good at finding elements out of a huge pool of non-elements… But we’ll get a lot of false positives along the way.”

Civilian killings and disappearances during civil war in El Salvador (1980–1992)

Amelia Hoover Green and Patrick Ball (2019). Civilian killings and disappearances during civil war in El Salvador (1980–1992). Demographic Research, 1 October 2019. © 2019 Demographic Research. DOI: 10.4054/DemRes.2019.41.27  

Amelia Hoover Green and Patrick Ball (2019). Civilian killings and disappearances during civil war in El Salvador (1980–1992). Demographic Research, 1 October 2019. © 2019 Demographic Research. DOI: 10.4054/DemRes.2019.41.27

Lies, Damned Lies and Official Statistics

This essay in the Health and Human Rights Journal addresses attempts to undermine Covid-19 data collection.

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.

Core Concepts

Inaccurate statistics can damage the credibility of human rights claims—and that's why we strive to ensure that statistics about human rights violations are generated with as much rigor and are as scientifically accurate as possible. But, what are the pitfalls leading to inaccuracy—when, where, and how do data become compromised? How are patterns biased by having only partial data? And what are the best scientific methods for collecting, managing, processing and analyzing data? Here are the data pitfalls that HRDAG has identified, as well as some of our approaches for meeting these challenges. We believe that human rights researchers must take ...

The causal impact of bail on case outcomes for indigent defendants in New York City

Kristian Lum, Erwin Ma and Mike Baiocchi (2017). The causal impact of bail on case outcomes for indigent defendants in New York City. Observational Studies 3 (2017) 39-64. 31 October 2017. © 2017 Institute of Mathematical Statistics.

Kristian Lum, Erwin Ma and Mike Baiocchi (2017). The causal impact of bail on case outcomes for indigent defendants in New York City. Observational Studies 3 (2017) 39-64. 31 October 2017. © 2017 Institute of Mathematical Statistics.

HRDAG and #GivingTuesday 2017

Help us hold human rights violators accountable!

Multiple Systems Estimation: Collection, Cleaning and Canonicalization of Data

<< Previous post: MSE: The Basics Q3. What are the steps in an MSE analysis? Q4. What does data collection look like in the human rights context? What kind of data do you collect? Q5. [In depth] Do you include unnamed or anonymous victims in the matching process? Q6. What do you mean by "cleaning" and "canonicalization?" Q7. [In depth] What are some of the challenges of canonicalization? (more…)

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 ...

HRDAG Offers New R Package – dga

Much of the work we do at HRDAG involves estimating the number of undocumented deaths using a statistical technique called multiple systems estimation (MSE, described in more detail here). One of our goals is to make this class of methods more broadly available to human rights researchers. In particular, we are finding that Bayesian approaches are extremely valuable for MSE. Accordingly, we are pleased to offer a new R package called dga (“decomposable graphs approach”) that performs Bayesian model averaging for MSE. The main function in this package implements a model created by David Madigan and Jeremy York. This model was designed to ...

Why It Took So Long To Update the U.N.-Sponsored Syria Death Count

In this story, Carl Bialik of FiveThirtyEight interviews HRDAG executive director Patrick Ball about the process of de-duplication, integration of databases, and machine-learning in the recent enumeration of reported casualties in Syria.
New reports of old deaths come in all the time, Ball said, making it tough to maintain a database. The duplicate-removal process means “it’s a lot like redoing the whole project each time,” he said.

Nonprofits Are Taking a Wide-Eyed Look at What Data Could Do

In this story about how data are transforming the nonprofit world, Patrick Ball is quoted. Here’s an excerpt: “Data can have a profound impact on certain problems, but nonprofits are kidding themselves if they think the data techniques used by corporations can be applied wholesale to social problems,” says Patrick Ball, head of the nonprofit Human Rights Data Analysis Group.
Companies, he says, maintain complete data sets. A business knows every product it made last year, when it sold, and to whom. Charities, he says, are a different story.
“If you’re looking at poverty or trafficking or homicide, we don’t have all the data, and we’re not going to,” he says. “That’s why these amazing techniques that the industry people have are great in industry, but they don’t actually generalize to our space very well.”

Our work has been used by truth commissions, international criminal tribunals, and non-governmental human rights organizations. We have worked with partners on projects on five continents.

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