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Unpacking gender and race segregation along occupational skills and socio-economic status in Brazil

Nature Human Behaviour (2025)Cite this article

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Abstract

The occupational specialization of social groups is closely tied to gender, racial and class identities, segmenting the labour market into perceived White/Black and male/female roles and skill sets. Using data from 100 million formal workers in Brazil (2003–2019), we examine patterns of occupational segmentation across 426 occupations, identifying distinct skill demands and socio-economic statuses linked to race/skin colour and gender. Classifications of ‘male’ or ‘female’ occupations are shaped by required skills, whereas distinctions between ‘White’ and ‘Black’ occupations reflect socio-economic status and historical inequalities. Women and men are segmented by gender-associated skill sets, such as engineering versus caregiving skills. Within these skill sets, strong hierarchical segregation persists, with Black individuals disproportionately concentrated in positions of lower socio-economic status. Despite recent socio-economic changes, occupational specialization patterns have remained stable. Our findings highlight that the strong association between race and lower-status occupations must be addressed for a more inclusive society.

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Fig. 1: Example of vertical and horizontal segregation in Brazil.
Fig. 2: The occupational space of Brazil.
Fig. 3: Relationship between occupations’ ISEI and socio-cognitive skills.
Fig. 4: Temporal evolution of the coefficient of skills positively associated with each gender.
Fig. 5: Temporal evolution of the adjusted ISEI (β) coefficient for the different social groups.

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Data availability

RAIS data are available from the Brazilian Ministry of Labor and Employment portal (https://www.gov.br/trabalho-e-emprego/pt-br/assuntos/estatisticas-trabalho/microdados-rais-e-caged). Census data are available from the Brazilian Institute of Geography and Statistics (IBGE) portal (https://www.ibge.gov.br/estatisticas/multidominio/cultura-recreacao-e-esporte/9662-censo-demografico-2010.html?=&t=microdados). Both RAIS and Census data are freely available for unrestricted use without licensing, patenting or control mechanisms, as explicitly stated on the government’s open data policy page at https://www.gov.br/trabalho-e-emprego/pt-br/acesso-a-informacao/dados-abertos. ESCO Skills-Occupation Matrix Tables are available at https://esco.ec.europa.eu/en/publication/skills-occupations-matrix-tables. The official titles and hierarchical structure of ISCO-08 occupation groups are available from the International Labour Organization’s ILOSTAT portal at https://ilostat.ilo.org/methods/concepts-and-definitions/classification-occupation/. The datasets necessary for reproducing the findings presented in this Article and Supplementary Information are available at https://doi.org/10.6084/m9.figshare.27184176 (ref. 53).

Code availability

All the code necessary to reproduce the results presented in this paper and Supplementary Information can be downloaded at https://doi.org/10.6084/m9.figshare.27184176 (ref. 53).

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Acknowledgements

B.-H.F.C. and L.S. are grateful for the financial support of the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES; finance code 001), and D.H. is grateful for the support from CNPq (406943/ 2021-4 and 315441/2021-6). B.-H.F.C. and D.H. thank the Ministry of Economics of Brazil for access to the 2003–2019 RAIS database (Processo SEI number 19965.106679/2021-1). F.L.P. acknowledges funding support from Fundação para a Ciência e a Tecnologia (FCT), under the project UIDB/04152, Centro de Investigação em Gestão de Informação (MagIC)/NOVA IMS. D.H. thanks C. Jara-Figueroa, M. Kaltenberg and C. Hidalgo for their insights on occupational networks in Brazil and the many fruitful discussions held at the MIT Media Lab in 2014–2016. All authors thank C. Scalon, E. Catela, G. Moura, K. de Souza Silva, participants at the SASE Rio conference 2023, and members of Necode-UFSC group meetings for valuable comments. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the paper.

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Authors and Affiliations

  1. Departamento de Economia e Relações Internacionais, Universidade Federal de Santa Catarina, Florianópolis, Brazil

    Ben-Hur Francisco Cardoso, Laís Souza, Liana Bohn & Dominik Hartmann

  2. NOVA Information Management School (NOVA IMS), Universidade Nova de Lisboa, Lisbon, Portugal

    Flávio L. Pinheiro

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  1. Ben-Hur Francisco Cardoso
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Contributions

B.-H.F.C., D.H., L.S., L.B. and F.L.P. conceived the study and designed the experiments. B.-H.F.C. performed the experiments and analysed the data. All authors participated in the writing and revision of the article.

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Correspondence to Flávio L. Pinheiro or Dominik Hartmann.

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Supplementary Figs. 1–45 and Tables 1–23, organized into Sections 1–12.

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Cardoso, BH.F., Souza, L., Pinheiro, F.L. et al. Unpacking gender and race segregation along occupational skills and socio-economic status in Brazil. Nat Hum Behav (2025). https://doi.org/10.1038/s41562-025-02272-9

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