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Lessons at HRDAG: Making More Syrian Records Usable
If we could glean key missing information from those fields, we would be able to use more records.
Los asesinatos de líderes sociales que quedan fuera de las cuentas
Una investigación de Dejusticia y Human Rights Data Analysis Group concluyó que hay un subconteo en los asesinatos de líderes sociales en Colombia. Es decir, que el aumento de estos crímenes en 2016 y 2017 podría ser incluso mayor al reportado por las organizaciones y por las cifras oficiales.
The ghost in the machine
“Every kind of classification system – human or machine – has several kinds of errors it might make,” [Patrick Ball] says. “To frame that in a machine learning context, what kind of error do we want the machine to make?” HRDAG’s work on predictive policing shows that “predictive policing” finds patterns in police records, not patterns in occurrence of crime.
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 ...
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 ...
Estimating the Number of SARS-CoV-2 Infections and the Impact of Mitigation Policies
This Harvard Data Science Review article uses the least unreliable source of pandemic data: reported deaths.
Violence in Blue: The 2020 Update
HRDAG has refreshed a 2016 Granta article about homicides committed by police in the United States.
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.
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.
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.
Welcoming Our New Data Scientist
We're thrilled to announce that Tarak Shah has joined our team as our new data scientist.
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 ...
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.
Reflections: It Began In Bogotá
It was July of 2006, I’d spent five years working at a local human rights NGO in Bogotá, and I had reached retirement age. But then a whole new world opened up for me to discover. Tamy Guberek, then HRDAG Latin America coordinator, whom I had met at the NGO, approached me about becoming part of the HRDAG Colombia team as a research/administrative assistant. Over a cup of suitably Colombian coffee, the deal was quickly "signed.” My responsibilities ranged from fundraising to translations, from support in data gathering for estimates on homicides and disappearances in various regions of Colombia to editorial support to different Benetech-HRDAG ...
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 ...
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?’”
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 ...
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…)
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 ...
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 ...