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Nature ; 610(7930): 120-127, 2022 10.
Artigo em Inglês | MEDLINE | ID: mdl-36131023

RESUMO

Faculty hiring and retention determine the composition of the US academic workforce and directly shape educational outcomes1, careers2, the development and spread of ideas3 and research priorities4,5. However, hiring and retention are dynamic, reflecting societal and academic priorities, generational turnover and efforts to diversify the professoriate along gender6-8, racial9 and socioeconomic10 lines. A comprehensive study of the structure and dynamics of the US professoriate would elucidate the effects of these efforts and the processes that shape scholarship more broadly. Here we analyse the academic employment and doctoral education of tenure-track faculty at all PhD-granting US universities over the decade 2011-2020, quantifying stark inequalities in faculty production, prestige, retention and gender. Our analyses show universal inequalities in which a small minority of universities supply a large majority of faculty across fields, exacerbated by patterns of attrition and reflecting steep hierarchies of prestige. We identify markedly higher attrition rates among faculty trained outside the United States or employed by their doctoral university. Our results indicate that gains in women's representation over this decade result from demographic turnover and earlier changes made to hiring, and are unlikely to lead to long-term gender parity in most fields. These analyses quantify the dynamics of US faculty hiring and retention, and will support efforts to improve the organization, composition and scholarship of the US academic workforce.


Assuntos
Docentes , Seleção de Pessoal , Universidades , Recursos Humanos , Educação de Pós-Graduação/estatística & dados numéricos , Emprego/estatística & dados numéricos , Docentes/estatística & dados numéricos , Feminino , Humanos , Masculino , Seleção de Pessoal/estatística & dados numéricos , Grupos Raciais/estatística & dados numéricos , Fatores Socioeconômicos , Estados Unidos , Universidades/estatística & dados numéricos , Mulheres , Recursos Humanos/estatística & dados numéricos
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