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An agenda for addressing bias in conflict data

With increased availability of disaggregated conflict event data for analysis, there are new and old concerns about bias. All data have biases, which we define as an inclination, prejudice, or directionality to information. In conflict data, there are often perceptions of damaging bias, and skeptici...

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Autores principales: Miller, Erin, Kishi, Roudabeh, Raleigh, Clionadh, Dowd, Caitriona
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9525611/
https://www.ncbi.nlm.nih.gov/pubmed/36180448
http://dx.doi.org/10.1038/s41597-022-01705-8
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author Miller, Erin
Kishi, Roudabeh
Raleigh, Clionadh
Dowd, Caitriona
author_facet Miller, Erin
Kishi, Roudabeh
Raleigh, Clionadh
Dowd, Caitriona
author_sort Miller, Erin
collection PubMed
description With increased availability of disaggregated conflict event data for analysis, there are new and old concerns about bias. All data have biases, which we define as an inclination, prejudice, or directionality to information. In conflict data, there are often perceptions of damaging bias, and skepticism can emanate from several areas, including confidence in whether data collection procedures create systematic omissions, inflations, or misrepresentations. As curators and analysts of large, popular data projects, we are uniquely aware of biases that are present when collecting and using event data. We contend that it is necessary to advance an open and honest discussion about the responsibilities of all stakeholders in the data ecosystem – collectors, researchers, and those interpreting and applying findings – to thoughtfully and transparently reflect on those biases; use data in good faith; and acknowledge limitations. We therefore posit an agenda for data responsibility considering its collection and critical interpretation.
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spelling pubmed-95256112022-10-02 An agenda for addressing bias in conflict data Miller, Erin Kishi, Roudabeh Raleigh, Clionadh Dowd, Caitriona Sci Data Comment With increased availability of disaggregated conflict event data for analysis, there are new and old concerns about bias. All data have biases, which we define as an inclination, prejudice, or directionality to information. In conflict data, there are often perceptions of damaging bias, and skepticism can emanate from several areas, including confidence in whether data collection procedures create systematic omissions, inflations, or misrepresentations. As curators and analysts of large, popular data projects, we are uniquely aware of biases that are present when collecting and using event data. We contend that it is necessary to advance an open and honest discussion about the responsibilities of all stakeholders in the data ecosystem – collectors, researchers, and those interpreting and applying findings – to thoughtfully and transparently reflect on those biases; use data in good faith; and acknowledge limitations. We therefore posit an agenda for data responsibility considering its collection and critical interpretation. Nature Publishing Group UK 2022-09-30 /pmc/articles/PMC9525611/ /pubmed/36180448 http://dx.doi.org/10.1038/s41597-022-01705-8 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Comment
Miller, Erin
Kishi, Roudabeh
Raleigh, Clionadh
Dowd, Caitriona
An agenda for addressing bias in conflict data
title An agenda for addressing bias in conflict data
title_full An agenda for addressing bias in conflict data
title_fullStr An agenda for addressing bias in conflict data
title_full_unstemmed An agenda for addressing bias in conflict data
title_short An agenda for addressing bias in conflict data
title_sort agenda for addressing bias in conflict data
topic Comment
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9525611/
https://www.ncbi.nlm.nih.gov/pubmed/36180448
http://dx.doi.org/10.1038/s41597-022-01705-8
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