Women, Work, and Family: Estimating Married Women's Status Achievement Over Their Careers
Bibliographic record
Abstract
My dissertation project examines women’s family lives, career trajectories, and status attainment. I draw on the concept of the work-family interface to highlight how work and families operate as contextual layers that cross-over in shaping definitions and appraisals of mothers as workers and workers as mothers. Utilizing data on married mothers’ complete working histories, I demonstrate that job exits due to motherhood negatively impact women’s occupational status attainment (SES), but I also show that women face penalties when changing jobs involuntarily and also due to personal reasons not tied to the maternal role. Importantly, in each instance, I demonstrate that these effects operate independently of the non-employment durations they engender, offering broad support for the status characteristics framework which points to the role of employer appraisals of women’s work commitment in shaping their SES outcomes. I also bring families back into the discussion of the work-family interface via the construction of a family-level framework that draws on mothers’, fathers’ and children’s attitudes about maternal employment as a platform for the development of discrete family configurations. I reveal a wide array of family attitude configurations that underscore that maternal employment continues to be contested moral terrain in some families while it is ii supported in others. In particular, I show that in egalitarian families—where maternal employment is not seen as a risk to ‘good’ mothering—mothers report more positive experiences of family and marital relations, less housework and more paid work, and higher earnings. I argue that family contexts represent an important yet understudied contextual reality that is more than the sum of individual views and which have unique consequences for women’s family lives and status trajectories.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".