Understanding the self-organization of occupational sex segregation with mobility networks
Bibliographic Data
| ID | 2090734 |
|---|---|
| Authors | Per Block (0000-0002-7583-2392, University of Zurich, corresponding author) |
| Year | 2023 |
| Volume | 73 |
| Pages | 42-50 |
| Publication date | 2023-05-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Social Networks (JOURNAL) |
| Journal identifiers | ISSN: 0378-8733 • E-ISSN: 1879-2111 |
| Publisher | Elsevier BV (PUBLISHER) |
| DOI | 10.1016/j.socnet.2022.12.004 |
| OpenAlex | W4313367367 |
| Language | EN |
| Citations received | 11 |
| References cited | 43 |
Decades after the beginning of the gender revolution, most women and men still work in sex-typed occupations. This is a primary driver of the gender wage gap. Most research describing the patterns of occupational sex segregation focuses on supposedly innate job characteristics that match gender stereotypical abilities and preferences, such as the use of mathematical skills or social skills, on income and status differences between occupations, and on organizational job characteristics, for example, the need to work long hours. However, beyond such occupational attributes, sex segregation is hypothesized to exhibit emergent patterns that are linked to the interdependent job mobility of women and men, in particular, men selectively leaving feminizing occupations. Developing new tools inspired by statistical network research, and using representative, longitudinal data that contain detailed occupational mobility from the UK between 2000 and 2008, this replacement mechanism is analyzed. It is shown that 19–28% of observed sex segregation is linked to this emergent phenomenon in a statistical model that disentangles the various predictors of the allocation of women and men to different occupations. This makes it the most important predictor of segregation in contrast to concurrently modelled explanations based on occupational characteristics. The BHPS data and the LFS data are available from the UK Data Service (https://www.ukdataservice.ac.uk/). The O*NET data is available from the O*NET homepage (https://www.onetcenter.org/). Software implemented in the environment R and code for data analysis are available upon request from the authors
Economics · Interdependence · Labour economics · Occupational prestige · Occupational segregation · Population · Sex segregation · Social science · Socioeconomic status · Sociology · Wage · Demography · Engineering · Gender Studies · Intergenerational and Educational Inequality Studies · Labor market dynamics and wage inequality · Psychology · Social Psychology · Youth Education and Societal Dynamics
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| Unique citing works | 11 |
|---|---|
| Citations per year | 3,67 |
| Citation span | 2023 - 2026 (4) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 11 |