Bibliographic record
Abstract
Occupational gender segregation is an obdurate feature of gender inequality in the United States The “family plans thesis”—the belief that women and men deliberately adjust their early career decisions to accommodate their anticipated family roles—is a common theoretical explanation of this segregation in the social sciences and in popular discourse. But do young men and women actually account for their family plans when making occupational choices? This article investigates the validity of this central mechanism of the family plans thesis. Drawing on in-depth interviews with 100 college students at three universities, I find that most women and men report no deliberate consideration of their family plans in their college major or post-graduation career choices. Only a quarter of men accommodate provider role plans in their choice of occupations, and only 7 of 56 women (13 percent) accommodate caregiving plans. Further, men who anticipate a provider role are not typically enrolled in more men-dominated fields, and women who seek caregiver-friendly occupations are not typically enrolled in more women-dominated fields. These findings question the validity of the family plans thesis and suggest instead that the thesis itself may reproduce segregation as a cultural schema that buttresses essentialist stereotypes about appropriate fields for men and women.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.027 |
| Scholarly communication | 0.006 | 0.012 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.020 | 0.003 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".