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Socioeconomic Status and Public Sector Worker Stereotypes: Results from a Representative Survey.

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Title: Socioeconomic Status and Public Sector Worker Stereotypes: Results from a Representative Survey.
Authors: Bertram, Isa1 (AUTHOR) i.bertram@uu.nl, Bouwman, Robin2 (AUTHOR) bouwman@essb.eur.nl, Tummers, Lars1 (AUTHOR) l.g.tummers@uu.nl
Source: Public Administration Review. Mar2022, Vol. 82 Issue 2, p237-255. 19p. 12 Charts, 3 Graphs.
Subject Terms: *Civil service, Public opinion, Stereotypes, Perception (Philosophy)
Geographic Terms: Netherlands
Abstract: What views do people have of public sector workers? Public sector workers are often portrayed negatively. It is unclear, however, to what extent such negative perceptions are shared among different groups in society. Using a large representative survey in the Netherlands, we study whether people's socioeconomic status is related to having more negative stereotypes about public sector workers. Contrary to expectations, education and income are unrelated to stereotypes. We do find a relation with subjective income: People with low subjective income have more negative stereotypes. Moreover, the sector people work in is highly relevant. People working in core governmental sectors such as central and local government have positive stereotypes. Other groups—such as private sector and non‐profit workers—have a far more negative image of public sector workers. These findings help us to understand people's perceptions of public sector workers and the problems various groups have with the state. [ABSTRACT FROM AUTHOR]
Copyright of Public Administration Review is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Education Research Complete
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  Data: <searchLink fieldCode="JN" term="%22Public+Administration+Review%22">Public Administration Review</searchLink>. Mar2022, Vol. 82 Issue 2, p237-255. 19p. 12 Charts, 3 Graphs.
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  Data: *<searchLink fieldCode="DE" term="%22Civil+service%22">Civil service</searchLink><br /><searchLink fieldCode="DE" term="%22Public+opinion%22">Public opinion</searchLink><br /><searchLink fieldCode="DE" term="%22Stereotypes%22">Stereotypes</searchLink><br /><searchLink fieldCode="DE" term="%22Perception+%28Philosophy%29%22">Perception (Philosophy)</searchLink>
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  Data: What views do people have of public sector workers? Public sector workers are often portrayed negatively. It is unclear, however, to what extent such negative perceptions are shared among different groups in society. Using a large representative survey in the Netherlands, we study whether people's socioeconomic status is related to having more negative stereotypes about public sector workers. Contrary to expectations, education and income are unrelated to stereotypes. We do find a relation with subjective income: People with low subjective income have more negative stereotypes. Moreover, the sector people work in is highly relevant. People working in core governmental sectors such as central and local government have positive stereotypes. Other groups—such as private sector and non‐profit workers—have a far more negative image of public sector workers. These findings help us to understand people's perceptions of public sector workers and the problems various groups have with the state. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Public Administration Review is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1111/puar.13461
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        Text: English
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        PageCount: 19
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      – SubjectFull: Public opinion
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      – SubjectFull: Perception (Philosophy)
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      – SubjectFull: Netherlands
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              Text: Mar2022
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