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Modern Assessments of Intelligence Must Be Fair and Equitable

Historically, assessments of human intelligence have been virtually synonymous with practices that contributed to forms of inequality and injustice. As such, modern considerations for assessing human intelligence must focus on equity and fairness. First, we highlight the array of diversity, equity,...

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Detalles Bibliográficos
Autores principales: Holden, LaTasha R., Tanenbaum, Gabriel J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10301777/
https://www.ncbi.nlm.nih.gov/pubmed/37367528
http://dx.doi.org/10.3390/jintelligence11060126
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author Holden, LaTasha R.
Tanenbaum, Gabriel J.
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Tanenbaum, Gabriel J.
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description Historically, assessments of human intelligence have been virtually synonymous with practices that contributed to forms of inequality and injustice. As such, modern considerations for assessing human intelligence must focus on equity and fairness. First, we highlight the array of diversity, equity, and inclusion concerns in assessment practices and discuss strategies for addressing them. Next, we define a modern, non-g, emergent view of intelligence using the process overlap theory and argue for its use in improving equitable practices. We then review the empirical evidence, focusing on sub-measures of g to highlight the utility of non-g, emergent models in promoting equity and fairness. We conclude with suggestions for researchers and practitioners.
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spelling pubmed-103017772023-06-29 Modern Assessments of Intelligence Must Be Fair and Equitable Holden, LaTasha R. Tanenbaum, Gabriel J. J Intell Essay Historically, assessments of human intelligence have been virtually synonymous with practices that contributed to forms of inequality and injustice. As such, modern considerations for assessing human intelligence must focus on equity and fairness. First, we highlight the array of diversity, equity, and inclusion concerns in assessment practices and discuss strategies for addressing them. Next, we define a modern, non-g, emergent view of intelligence using the process overlap theory and argue for its use in improving equitable practices. We then review the empirical evidence, focusing on sub-measures of g to highlight the utility of non-g, emergent models in promoting equity and fairness. We conclude with suggestions for researchers and practitioners. MDPI 2023-06-20 /pmc/articles/PMC10301777/ /pubmed/37367528 http://dx.doi.org/10.3390/jintelligence11060126 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Essay
Holden, LaTasha R.
Tanenbaum, Gabriel J.
Modern Assessments of Intelligence Must Be Fair and Equitable
title Modern Assessments of Intelligence Must Be Fair and Equitable
title_full Modern Assessments of Intelligence Must Be Fair and Equitable
title_fullStr Modern Assessments of Intelligence Must Be Fair and Equitable
title_full_unstemmed Modern Assessments of Intelligence Must Be Fair and Equitable
title_short Modern Assessments of Intelligence Must Be Fair and Equitable
title_sort modern assessments of intelligence must be fair and equitable
topic Essay
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10301777/
https://www.ncbi.nlm.nih.gov/pubmed/37367528
http://dx.doi.org/10.3390/jintelligence11060126
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