257 results for search: Что сделать чтобы обратить внимание старшеклассника детальнее bit.ly/psy3000/feed/guatemala
How to Become a Data Scientist: My Lessons at HRDAG
I will use the skills and culture I learned from HRDAG’s team to understand how the conflict has affected the people in my country.
Reflections: Challenging Tasks and Meticulous Defenders
I have made it my personal objective to amplify HRDAG's message of being extra careful and scientifically rigorous with human rights data.
Reflections: HRDAG Was Born in Washington
I began working with HRDAG in the summer of 2001 before it was ever even called HRDAG. In fact, not intended as a boast, I think I’m responsible for coming up with the name. After contracting with Dr. Patrick Ball for a time writing the Analyzer data management platform, I left New York City and joined him in Washington, DC, at AAAS in 2002. Soon after starting, Patrick decided to establish an identity for this new team, consisting mainly of myself, Miguel Cruz and a handful of field relationships. We discussed what to name it briefly in the AAAS Science & Policy break room, which at the time, being in the mind of unclever descriptive naming ...
In Pursuit of Excellent Data Processing
With help from HRDAG, Roman Rivera built the data backbone for the Invisible Institute's Citizens Police Data Project.
Policing
If you'd like to support HRDAG in this project, please consider making a donation via Our Donate page.
Over the last year, HRDAG has deepened the national conversation about homicides by police, predictive policing software, and the role that bail plays in the criminal justice system. Our studies describe how the racial bias inherent in police practice becomes data input to predictive policing tools. In another project, we are shining light on the iniquities of bail decisions.
TEAM
Click each team member's photo for full bio. Here's the team on Twitter.
Examining the Impact of Bail
When a defendant is detained before trial, she will face ...
The UDHR Turns 70
We're thinking about how rigorous analysis can fortify debates about components of our criminal justice system such as cash bail, pretrial risk assessment and fairness in general.
Chad – FAQs
State Coordinated Violence in Chad under Hissène Habré -- [Français]
Rionegro
Texto en Español
Using Cemetery Information to Search for the Disappeared Lessons from a Pilot Study in Rionegro, Antioquia, Colombia
Between May and July 2009, researchers from the Benetech Human Rights Data Analysis Group (HRDAG) conducted a pilot study to examine patterns of information about unidentified bodies at a cemetery in Rionegro, a town located Antioquia, Colombia. The study was carried out to support ongoing efforts by HRDAG's partner organization EQUITAS (Colombian Interdisciplinary Team for Forensic Work and Psychosocial Assistance) to identify bodies of unknown persons in the Rionegro cemetery. EQUITAS has found that cemeteries in ...
Donate with Cryptocurrency
Help HRDAG use data science to work for justice, accountability, and human rights. We are nonpartisan and nonprofit, but we are not neutral; we are always on the side of human rights.
Cryptocurrency donations to 501(c)3 charities receive the same tax treatment as stocks. Your donation is a non-taxable event, meaning you do not owe capital gains tax on the appreciated amount and can deduct it on your taxes. This makes Bitcoin and other cryptocurrency donations one of the most tax efficient ways to support us.
We are a team of experts in machine learning, applied and mathematical statistics, computer science, demography, and social science, and ...
How Predictive Policing Reinforces Bias
Algorithmic tools like PredPol were supposed to reduce bias. But HRDAG has found that racial bias is baked into the data used to train the tools.
RustConf 2019, and systems programming as a data scientist
It could make sense to use Rust as a data journalist for in-browser computations, and other thoughts from RustConf.
A geeky deep-dive: database deduplication to identify victims of human rights violations
In our work, we merge many databases to figure out how many people have been killed in violent conflict. Merging is a lot harder than you might think.
Many of the database records refer to the same people--the records are duplicated. We want to identify and link all the records that refer to the same victims so that each victim is counted only once, and so that we can use the structure of overlapping records to do multiple systems estimation.
Merging records that refer to the same person is called entity resolution, database deduplication, or record linkage. For definitive overviews of the field, see Scheuren, Herzog, and Winkler, Data Quality ...
Making Missing Data Visible in Colombia
Valentina Rozo Ángel has worked with HRDAG and the Colombian Truth Commission to acknowledge victims of the 50-year conflict who are not visible or easily counted.
Happy Ada Lovelace Day!
As an organization that uses science to advocate for human rights, the goals and issues represented by Ada Lovelace Day are very near and dear to our hearts. Additionally, we are lucky to work with and be advised by some pretty kick-ass ladies in STEM (see our People page to learn more about these amazing women (and men)).
I brainstormed a list of women I could write about, as Finding Ada suggests we celebrate today by blogging about a STEM heroine. I considered Anita Borg (she has her own institute!), who advocated tirelessly for women in computer science. I thought about Sally Wyatt, keynote speaker and organizer of the fascinating workshop...
Learning Day by Day: Quantitative Research at the AHPN
Working at the Historic Archive of the National Police (AHPN) of Guatemala, there are many skills I learned on the job. My many years of work on the team that studies the recovered documents have been like a custom-made course in how to do quantitative research.
The Archive documents I study are the result of 36 years of creation during civil war (1960 to 1996). Many of these documents are simply administrative—but we are able to use them to understand patterns that occurred during the conflict, to get a sense of what mattered to the National Police and what didn’t. Our quantitative research shows us the Police behavior in broad strokes. ...
IRR: Agreement Among Coders is Key
For years I have been engaged in a quantitative study at Guatemala’s Historic Archive of the National Police, or AHPN. (See the blogposts below.) In this study coders collect data on sheets of paper according to criteria established and explained in manuals. But when collecting data, there’s always room for human error—this is why the validity of the study hinges on verifying that coders use the correct criteria.
It is important to mention that the mainstay of coding is the use of a controlled vocabulary. A controlled vocabulary gives analysts a framework, or frame of reference, when converting qualitative information into categories ...
Claudia Carolina López Taks
Field Consultant
Carolina Lopéz has worked with the Archivo Histórico de la Policía Nacional (AHPN) in Guatemala for eight years, and is currently a member of the Archive Technical Coordination team. A professional working within the social sciences, she prefers using alternative research on past practices to develop an understanding of the present. Her work consists primarily of monitoring and creating strategies to systematize, track and create process controls. She also has thorough knowledge of management of historical archive documents.
Since 2006, Carolina has worked in quantitative research at the AHPN with HRDAG team members Patrick ...
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?’”
The task is a quantum of workflow
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 ...