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A best–worst scaling experiment to prioritize concern about ethical issues in citizen science reveals heterogeneity on people-level v. data-level issues

“Citizen science” refers to the participation of lay individuals in scientific studies and other activities having scientific objectives. Citizen science gives rise to unique ethical issues that stem from the potentially multifaceted contributions of citizen scientists to the research process. We so...

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Autores principales: Guerrini, Christi J., Crossnohere, Norah L., Rasmussen, Lisa, Bridges, John F. P.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8476613/
https://www.ncbi.nlm.nih.gov/pubmed/34580327
http://dx.doi.org/10.1038/s41598-021-96743-4
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author Guerrini, Christi J.
Crossnohere, Norah L.
Rasmussen, Lisa
Bridges, John F. P.
author_facet Guerrini, Christi J.
Crossnohere, Norah L.
Rasmussen, Lisa
Bridges, John F. P.
author_sort Guerrini, Christi J.
collection PubMed
description “Citizen science” refers to the participation of lay individuals in scientific studies and other activities having scientific objectives. Citizen science gives rise to unique ethical issues that stem from the potentially multifaceted contributions of citizen scientists to the research process. We sought to explore the ethical issues that are most concerning to citizen scientist practitioners, participants, and scholars to support ethical practices in citizen science. We developed a best–worst scaling experiment using a balanced incomplete block design and fielded it with respondents recruited through the U.S.-based Citizen Science Association. Respondents were shown repeated subsets of 11 ethical issues and identified the most and least concerning issues in each subset. Latent class analysis revealed two respondent classes. The “Power to the People” class was most concerned about power imbalance between project leaders and participants, exploitation of participants, and lack of diverse participation. The “Show Me the Data” class was most concerned about the quality of data generated by citizen science projects and failure of projects to share data and other research outputs.
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spelling pubmed-84766132021-09-29 A best–worst scaling experiment to prioritize concern about ethical issues in citizen science reveals heterogeneity on people-level v. data-level issues Guerrini, Christi J. Crossnohere, Norah L. Rasmussen, Lisa Bridges, John F. P. Sci Rep Article “Citizen science” refers to the participation of lay individuals in scientific studies and other activities having scientific objectives. Citizen science gives rise to unique ethical issues that stem from the potentially multifaceted contributions of citizen scientists to the research process. We sought to explore the ethical issues that are most concerning to citizen scientist practitioners, participants, and scholars to support ethical practices in citizen science. We developed a best–worst scaling experiment using a balanced incomplete block design and fielded it with respondents recruited through the U.S.-based Citizen Science Association. Respondents were shown repeated subsets of 11 ethical issues and identified the most and least concerning issues in each subset. Latent class analysis revealed two respondent classes. The “Power to the People” class was most concerned about power imbalance between project leaders and participants, exploitation of participants, and lack of diverse participation. The “Show Me the Data” class was most concerned about the quality of data generated by citizen science projects and failure of projects to share data and other research outputs. Nature Publishing Group UK 2021-09-27 /pmc/articles/PMC8476613/ /pubmed/34580327 http://dx.doi.org/10.1038/s41598-021-96743-4 Text en © The Author(s) 2021 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Guerrini, Christi J.
Crossnohere, Norah L.
Rasmussen, Lisa
Bridges, John F. P.
A best–worst scaling experiment to prioritize concern about ethical issues in citizen science reveals heterogeneity on people-level v. data-level issues
title A best–worst scaling experiment to prioritize concern about ethical issues in citizen science reveals heterogeneity on people-level v. data-level issues
title_full A best–worst scaling experiment to prioritize concern about ethical issues in citizen science reveals heterogeneity on people-level v. data-level issues
title_fullStr A best–worst scaling experiment to prioritize concern about ethical issues in citizen science reveals heterogeneity on people-level v. data-level issues
title_full_unstemmed A best–worst scaling experiment to prioritize concern about ethical issues in citizen science reveals heterogeneity on people-level v. data-level issues
title_short A best–worst scaling experiment to prioritize concern about ethical issues in citizen science reveals heterogeneity on people-level v. data-level issues
title_sort best–worst scaling experiment to prioritize concern about ethical issues in citizen science reveals heterogeneity on people-level v. data-level issues
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8476613/
https://www.ncbi.nlm.nih.gov/pubmed/34580327
http://dx.doi.org/10.1038/s41598-021-96743-4
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