295 results for search: https:/www.hab.cl/buy-aciphex-baikal-pharmacycom-rtlx/feed/rss2/copyright
Accountability at home and abroad
Letter from the Executive Director
Where Stats and Rights Thrive Together
HRDAG and #GivingTuesday 2018
Update on Work in Guatemala and the AHPN
La estadística de mortalidad del conflicto en Perú
HRDAG Retreat 2022
Letter from Alejandro Valencia Villa
verdata: An R package for analyzing data from the Truth Commission in Colombia
The Journal of Open Source Software
The data compiled by the joint JEP-CEV-HRDAG project are publicly available from the Departamento Administrativo Nacional de Estadística (DANE). The data published by DANE is available in a format that may not be familiar to researchers who have not previously worked with statistical imputation methods. Recognizing this, verdata was created to support researchers in responsibly and correctly using the data despite the potential unfamiliarity of its structure. Researchers can use verdata to verify that the data files they are using in their analyses have not been altered, to replicate the main findings of the technical appendix, and to design new analyses of the conflict in Colombia.
Creative Commons Attribution 4.0 International License.
Maria Gargiulo, María Julia Durán, Paula Andrea Amado, and Patrick Ball (2024). verdata: An R package for analyzing data from the Truth Commission in Colombia. The Journal of Open Source Software. 6 January, 2024. 9(93), 5844, https://doi.org/10.21105/joss.05844. Creative Commons Attribution 4.0 International License.
Innocence Discovery Lab – Harnessing large language models to surface data buried in wrongful conviction case documents
The Wrongful Conviction Law Review
The recent advent of commercial artificial intelligence (AI), especially in natural language processing (NLP), introduces transformative possibilities for wrongful conviction research. NLP, a pivotal branch of AI that forms the basis for Large Language Models (LLMs), enables computers to interpret human language with a nuanced understanding. This technological advancement is particularly valuable for analyzing the complex language found in case documents associated with wrongful convictions. This paper explores the effectiveness of LLMs in analyzing and extracting data from case documents collected by the Innocence Project New Orleans and the National Registry of Exonerations. The diverse and comprehensive nature of these datasets makes them ideal for assessing the capabilities of LLMs. The findings of this study advance our understanding of how LLMs can be utilized to make wrongful conviction case documents easily accessible by automating the extraction of relevant data.
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. 31 May, 2024. https://doi.org/10.29173/wclawr112. © 2024 Ayyub Ibrahim, Huy Dao, Tarak Shah.
The use of unstructured data to study police use of force
CHANCE magazine
The challenges and opportunities researchers face when working with unstructured data are hardly new. This article defines unstructured data as data that is not organized according to pre-existing schemas or structures for the sake of statistical analysis. Unstructured data poses a unique challenge for researchers focused on police and policing. The article discusses a definition of unstructured data and two of the primary challenges faced when working with such data, namely information extraction and classification problems. Two case studies are used to illuminate the challenges.
Tarak Shah, Cristian Allen, Ayyub Ibrahim, Harlan Kefalas, and Bavo Stevens (2024). The Use of Unstructured Data to Study Police Use of Force. 5 December, 2024. CHANCE, 37 (4), 18–23. © The American Statistical Association (ASA) and Taylor & Francis Group 2024. https://doi.org/10.1080/09332480.2024.2434437
Shots fired: Can technology really keep us safe from gunfire?
Significance
An expensive American gunshot detection system claims it’s necessary because humans don’t always call the police to report gunfire. But opponents say it’s fatally flawed. To investigate, Bailey Passmore and Larry Barrett analysed data on emergencies within the city of Chicago.
Bailey Passmore and Larry Barrett (2025). Shots fired: Can technology really keep us safe from gunfire? Significance, Volume 22, Issue 4, July 2025, Pages 34–37. 27 May 2025. © Royal Statistical Society 2025. https://doi.org/10.1093/jrssig/qmaf042
Dictatorships create a lot of data
Rapid response to: Civilian deaths from weapons used in the Syrian conflict
The Limits of Observation for Understanding Mass Violence.
Humanitarian Statistics
In late 2006, a statistical study of deaths that occurred after the invasion of Iraq ignited a storm of controversy. This Lancet study estimated that more than 650,000 additional Iraqis died during the invasion than would have at pre-invasion death rates, a vastly higher estimate than any previous. But in January, a World Health Organization study placed the number at about 150,000.
SermonNew death toll estimated in Syrian civil war
Kevin Uhrmacher of the Washington Post prepared a graph that illustrates reported deaths over time, by number of organizations reporting the deaths.