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The AHPN: Home of Stories Old and New
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…)
HRDAG Retreat 2015
I look at the beach and then at the table surrounded by nerds, deep in thought and conversation about Dirichlet priors, matching algorithms, and armed conflicts. This peculiar (in the best way) environment catalyzes a moment of reflection: how did I get here?
Four years ago, as a second-year statistics PhD student, I watched "Guatemala: The Secret Files" on PBS Frontline World. I listened to stories of family members who disappeared without answers or justice. Then the story shifted to the work being done by archivists and data experts at Guatemala's Historic Archive of the National Police. The scientists' pursuit of the truth energized me. I ...
Using Data and Statistics to Bring Down Dictators
In this story, Guerrini discusses the impact of HRDAG’s work in Guatemala, especially the trials of General José Efraín Ríos Montt and Colonel Héctor Bol de la Cruz, as well as work in El Salvador, Syria, Kosovo, and Timor-Leste. Multiple systems estimation and the perils of using raw data to draw conclusions are also addressed.
Megan Price and Patrick Ball are quoted, especially in regard to how to use raw data.
“From our perspective,” Price says, “the solution to that is both to stay very close to the data, to be very conservative in your interpretation of it and to be very clear about where the data came from, how it was collected, what its limitations might be, and to a certain extent to be skeptical about it, to ask yourself questions like, ‘What is missing from this data?’ and ‘How might that missing information change these conclusions that I’m trying to draw?’”
Stephen Fienberg 1942-2016
We are saddened by the passing of Steve Fienberg yesterday in Pittsburgh, at the age of 74. He is perhaps best known around the world for bringing statistics to science and public policy and was a beloved professor at Carnegie Mellon University. At HRDAG we are in awe of and grateful for the work Steve did formalizing multiple systems estimation. His work on that front blazed a trail and essentially enabled all of our most important analytical work at the intersection of human rights and statistical science.
If we are to reduce the amount of human violence in the world, the first task is to determine the scope of the violence, to know how much of ...
New publication in BIOMETRIKA
New paper in Biometrika, co-authored by HRDAG's Kristian Lum and James Johndrow: Theoretical limits of microclustering in record linkage.
Talks
Upcoming Talks
TBA
Past Talks
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...
Happy Hacking
From my first introduction to the HRDAG community at the annual retreat it was clear to me that mentorship is an organizational priority and that the contributions of interns are valued. Much of my first couple weeks as a summer intern at HRDAG were spent familiarizing myself with Patrick’s paradigm for principled data processing. At the same time, I was learning the skills and tricks (bash, make, vim, git) that promote an effortless programming workflow, a pursuit that Patrick calls “sharpening the saw” (just like in programming, you can cut down a tree with a dull blade, but your life will be much easier if you take the time to sharpen ...
Welcoming Our New Data Scientist
We're thrilled to announce that Tarak Shah has joined our team as our new data scientist.
New Research on Civilian Deaths and Disappearances in El Salvador
This rigorous estimate shows that 1-2 percent of the country’s population was killed or disappeared during the civil war.
Uncertainty in COVID Fatality Rates
In this Granta article, HRDAG explains that neither the infectiousness nor the deadliness of the disease is set in stone.
A Model to Estimate SARS-CoV-2-Positive Americans
We’ve built a model for estimating the true number of positives, using what we have determined to be the most reliable datasets—deaths.
Violence in Blue: The 2020 Update
HRDAG has refreshed a 2016 Granta article about homicides committed by police in the United States.
Data coding and inter-rater reliability (IRR)
Data coding is the process of converting unstructured information, such as a narrative testimony, into discrete facts such as names and roles of actors (victims, witnesses, perpetrators) in crimes, as well as the date and place of act. Data coding must not discard or distort information. When more than one person is identifying, classifying and counting the elements reported in a qualitative source, the results of what they find may differ slightly based on each individual's interpretation and care in doing the coding. These differences can be measured by measuring IRR (inter-rater reliability). We give the same source document to several coders and ...
The Art and Science of Coding AHPN Documents
The coding, from my perspective, is the heart of the project. I say this, because the coding team has the responsibility of selecting documents according to the random sample, recording the documents’ contents, and applying the criteria to convert that content into an entry in a quantitative database. Not to mention the fact that this team has the privilege of being in direct contact with the documents.
At present, because of advanced organizational processes, not everyone has a chance to hold an original document in their hands. The quantitative study had many advantages in this regard; since we started work in parallel with the archival ...
CIIDH Data – Value Labels
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 ...
Quantifying Police Misconduct in Louisiana
HRDAG contributes to the project by helping to classify, filter, extract, and standardize the records so that they can be useful in the database.
R programming language demands the right use case
Megan Price, director of research, is quoted in this story about the R programming language. "Serious data analysis is not something you're going to do using a mouse and drop-down boxes," said HRDAG's director of research Megan Price. "It's the kind of thing you're going to do getting close to the data, getting close to the code and writing some of it yourself."
TechTarget blog
Ed Burns
March 19, 2014
Link to story in TechTarget
Back to Press Room
R programming language demands the right use case
Megan Price, director of research, is quoted in this story about the R programming language. “Serious data analysis is not something you’re going to do using a mouse and drop-down boxes,” said HRDAG’s director of research Megan Price. “It’s the kind of thing you’re going to do getting close to the data, getting close to the code and writing some of it yourself.”
String matching for governorate information in unstructured text
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Lies, Damned Lies and Official Statistics
This essay in the Health and Human Rights Journal addresses attempts to undermine Covid-19 data collection.