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A deep learning model identifies emphasis on hard work as an important predictor of income inequality
High levels of income inequality can persist in society only if people accept the inequality as justified. To identify psychological predictors of people’s tendency to justify inequality, we retrained a pre-existing deep learning model to predict the extent to which World Values Survey respondents b...
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/PMC9194778/ https://www.ncbi.nlm.nih.gov/pubmed/35701456 http://dx.doi.org/10.1038/s41598-022-13902-x |
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author | Sheetal, Abhishek Chaudhury, Srinwanti H. Savani, Krishna |
author_facet | Sheetal, Abhishek Chaudhury, Srinwanti H. Savani, Krishna |
author_sort | Sheetal, Abhishek |
collection | PubMed |
description | High levels of income inequality can persist in society only if people accept the inequality as justified. To identify psychological predictors of people’s tendency to justify inequality, we retrained a pre-existing deep learning model to predict the extent to which World Values Survey respondents believed that income inequality is necessary. A feature importance analysis revealed multiple items associated with the importance of hard work as top predictors. As an emphasis on hard work is a key component of the Protestant Work Ethic, we formulated the hypothesis that the PWE increases acceptance of inequality. A correlational study found that the more people endorsed PWE, the less disturbed they were about factual statistics about wealth equality in the US. Two experiments found that exposing people to PWE items decreased their disturbance with income inequality. The findings indicate that machine learning models can be reused to generate viable hypotheses. |
format | Online Article Text |
id | pubmed-9194778 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-91947782022-06-16 A deep learning model identifies emphasis on hard work as an important predictor of income inequality Sheetal, Abhishek Chaudhury, Srinwanti H. Savani, Krishna Sci Rep Article High levels of income inequality can persist in society only if people accept the inequality as justified. To identify psychological predictors of people’s tendency to justify inequality, we retrained a pre-existing deep learning model to predict the extent to which World Values Survey respondents believed that income inequality is necessary. A feature importance analysis revealed multiple items associated with the importance of hard work as top predictors. As an emphasis on hard work is a key component of the Protestant Work Ethic, we formulated the hypothesis that the PWE increases acceptance of inequality. A correlational study found that the more people endorsed PWE, the less disturbed they were about factual statistics about wealth equality in the US. Two experiments found that exposing people to PWE items decreased their disturbance with income inequality. The findings indicate that machine learning models can be reused to generate viable hypotheses. Nature Publishing Group UK 2022-06-14 /pmc/articles/PMC9194778/ /pubmed/35701456 http://dx.doi.org/10.1038/s41598-022-13902-x 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 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 Sheetal, Abhishek Chaudhury, Srinwanti H. Savani, Krishna A deep learning model identifies emphasis on hard work as an important predictor of income inequality |
title | A deep learning model identifies emphasis on hard work as an important predictor of income inequality |
title_full | A deep learning model identifies emphasis on hard work as an important predictor of income inequality |
title_fullStr | A deep learning model identifies emphasis on hard work as an important predictor of income inequality |
title_full_unstemmed | A deep learning model identifies emphasis on hard work as an important predictor of income inequality |
title_short | A deep learning model identifies emphasis on hard work as an important predictor of income inequality |
title_sort | deep learning model identifies emphasis on hard work as an important predictor of income inequality |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9194778/ https://www.ncbi.nlm.nih.gov/pubmed/35701456 http://dx.doi.org/10.1038/s41598-022-13902-x |
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