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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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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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. |
format | Online Article Text |
id | pubmed-9525611 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
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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