548 results for search: P Paris en direct Retrait instantané{WWW,RT33,TOP}코드 b77}Télévision en temps réelץParis sur Antigua-et-BarbudaЈemplacement rtゔOuzbékistanƛagent de laminageౡParis sur l'Angola≑équipe nationale tchèque∇Saint-Vincent-et-les Grenadines Totoぴ.jpi
Uncovering Police Violence in Chicago: A collaboration between HRDAG and Invisible Institute
In 2014 and again in 2020, the Invisible Institute, a Chicago grassroots organization, won lawsuits that granted them access to decades of complaints of misconduct by Chicago police officers. The collection contains hundreds of thousands of pages of allegation forms, memos, various police administrative forms, interviews and testimonies, pictures, and even embedded audio files. The Institute published scanned images on the Citizens Police Data Project, and is using them for a project with HRDAG known as Beneath the Surface, which is a detailed investigation into gender-based violence by Chicago Police.
Image: David Peters
Often, gender-b...
Lessons at HRDAG: Holding Public Institutions Accountable
Principled Data Processing is a way to prove to someone, usually yourself, that what you did was right.
How We Choose Projects
For more than 20 years, HRDAG has been carving out a niche in the international human rights movement. We know what we’re good at and what we’re not qualified to do. We know what quantitative questions we think are important for the community, and we know what we like to do. These preferences guide us as we consider whether to take on a project. We’re scientists, so our priorities will come as no surprise. We like to stick to science (not ideology), avoid advocacy, answer quantifiable questions, and increase our scientific understanding.
While we have no hard-and-fast rules about what projects to take on, we organize our deliberation ...
How We Choose Projects
For more than 20 years, HRDAG has been carving out a niche in the international human rights movement. We know what we’re good at and what we’re not qualified to do. We know what quantitative questions we think are important for the community, and we know what we like to do. These preferences guide us as we consider whether to take on a project. We’re scientists, so our priorities will come as no surprise. We like to stick to science (not ideology), avoid advocacy, answer quantifiable questions, and increase our scientific understanding.
While we have no hard-and-fast rules about what projects to take on, we organize our deliberation ...
Multiple Systems Estimation: Does it Really Work?
<< Previous post, MSE: Stratification and Estimation
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 ...
Reflections on Data Science for Real-World Problems
Trina Reynolds-Tyler's internship at HRDAG helped her use data science to find patterns in state-sanctioned violence.
Reflections: A Love Letter to HRDAG
On the anniversary of the Universal Declaration of Human Rights, HRDAG executive director Megan Price tells us why she loves her work, and why she feels hopeful about the future.
Quantitative Research at the AHPN Guatemala
In early 2006 I joined the Historical Archive of the National Police (Archivo Histórico de la Policía Nacional, or AHPN) without knowing the impact it would have on my future. I started with cleaning, organizing and classifying documents—and learning, with other colleagues, what a historical archive is and how it works.
By April of that year, parallel to these learning processes, I was selected along with 20 other people to begin work on the challenging Quantitative Research project. I started as a "coder," transferring key content from documents into a database. (more…)
El Salvador
Some of the earliest large-scale human rights information projects happened in El Salvador. One was developed by Patrick Ball at the Salvadoran non-governmental Human Rights Commission, also known as Comision de Derechos Humanos de El Salvador (CDHES-ng). Between 1977 and 1990, more than 9,000 testimonies were taken in an effort to document the nature and scope of the bloody conflict between the army and the Farabundo Marti National Liberation Front (FMLN). Starting in 1991, Patrick worked with CDHES staff to organize the information in an early computer database. They linked reported human rights violations with the career structures of individual ...
Our People
The Human Rights Data Analysis Group is composed of a diverse group of board members, full-time staff, and consultants. Employing a multidisciplinary approach, we work with experts in the fields of computer science, software development, mathematical and applied statistics, and demography.
Advisory Board
As a nonprofit organization, our Advisory Board serves as our governing body. This board helps us to make decisions, keeps us on track with our mission and goals, and oversees the organization in legal and logistical matters.
David Banks, Professor, Statistical Science, Duke University
Kim Keller, Executive Director, The Keller Foundation
Dinah ...
Multiple Systems Estimation: Stratification and Estimation
<< Previous post, MSE: The Matching Process
Q10. What is stratification?
Q11. [In depth] How do HRDAG analysts approach stratification, and why is it important?
Q12. How does MSE find the total number of violations?
Q13. [In depth] What are the assumptions of two-system MSE (capture-recapture)? Why are they not necessary with three or more systems?
Q14. What statistical model(s) does HRDAG typically use to calculate MSE estimates? (more…)
Mapping Mexico’s hidden graves
When Patrick Ball was introduced to Ibero’s database, the director of research at the Human Rights Data Analysis Group in San Francisco, California, saw an opportunity to turn the data into a predictive model. Ball, who has used similar models to document human rights violations from Syria to Guatemala, soon invited Data Cívica, a Mexico City–based nonprofit that creates tools for analyzing data, to join the project.
The Data Scientist Helping to Create Ethical Robots
Kristian Lum is focusing on artificial intelligence and the controversial use of predictive policing and sentencing programs.
What’s the relationship between statistics and AI and machine learning?
AI seems to be a sort of catchall for predictive modeling and computer modeling. There was this great tweet that said something like, “It’s AI when you’re trying to raise money, ML when you’re trying to hire developers, and statistics when you’re actually doing it.” I thought that was pretty accurate.
Locating Hidden Graves in Mexico
For more than 10 years, and with regularity, Mexican authorities have been discovering mass graves, known as fosas clandestinas, in which hundreds of bodies and piles of bones have been found. The casualties are attributed broadly to the country’s “drug war,” although the motivations and perpetrators behind the mass murders are often unknown.
Recently, HRDAG collaborated with two partners in Mexico—Data Cívica and Programa de Derechos Humanos of the Universidad Iberoamericana—to model the probability of identifying a hidden grave in each county (municipio). The model uses an set of independent variables and data about graves from 2013 ...
Policy or Panic? The Flight of Ethnic Albanians from Kosovo, March–May, 1999.
Patrick Ball. Policy or Panic? The Flight of Ethnic Albanians from Kosovo, March–May, 1999. © 2000 American Association for the Advancement of Science, Science and Human Rights Program. [pdf – English][html – English][html – shqip (Albanian)] [html – srpski (Serbian)]
Controlled vocabulary
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 ...
Innocence Discovery Lab – Harnessing Large Language Models to Surface Data Buried in Wrongful Conviction Case Documents
Ayyub Ibrahim, Huy Dao, and Tarak Shah (2024). “Innocence Discovery Lab - Harnessing Large Language Models to Surface Data Buried in Wrongful Conviction Case Documents." The Wrongful Conviction Law Review 5 (1):103-25. https://doi.org/10.29173/wclawr112. 31 May, 2024. Copyright (c) 2024 Ayyub Ibrahim, Huy Dao, Tarak Shah. Creative Commons Attribution 4.0 International License.
Ayyub Ibrahim, Huy Dao, and Tarak Shah (2024). “Innocence Discovery Lab – Harnessing Large Language Models to Surface Data Buried in Wrongful Conviction Case Documents.” The Wrongful Conviction Law Review 5 (1):103-25. https://doi.org/10.29173/wclawr112. 31 May, 2024. Copyright (c) 2024 Ayyub Ibrahim, Huy Dao, Tarak Shah. Creative Commons Attribution 4.0 International License.
Capture-Recapture for Casualty Estimation and Beyond: Recent Advances and Research Directions
Daniel Manrique-Vallier, Patrick Ball, Mauricio Sadinle. (2022). Capture-Recapture for Casualty Estimation and Beyond: Recent Advances and Research Directions. In: Carriquiry, A.L., Tanur, J.M., Eddy, W.F. (eds) Statistics in the Public Interest. Springer Series in the Data Sciences. Springer, Cham. https://doi.org/10.1007/978-3-030-75460-0_2
Manrique-Vallier, D., Ball, P., Sadinle, M. (2022). Capture-Recapture for Casualty Estimation and Beyond: Recent Advances and Research Directions. In: Carriquiry, A.L., Tanur, J.M., Eddy, W.F. (eds) Statistics in the Public Interest. Springer Series in the Data Sciences. Springer, Cham. https://doi.org/10.1007/978-3-030-75460-0_2
The Demography of Conflict-Related Mortality in Timor-Leste (1974-1999): Empirical Quantitative Measurement of Civilian Killings, Disappearances & Famine-Related Deaths
Romesh Silva and Patrick Ball. “The Demography of Conflict-Related Mortality in Timor-Leste (1974-1999): Empirical Quantitative Measurement of Civilian Killings, Disappearances & Famine-Related Deaths” In Statistical Methods for Human Rights, J. Asher, D. Banks and F. Scheuren, eds., Springer (New York) (2007)