Racing Against a Career‐Fertility Countdown: The Prospective Motherhood Penalty and Gendered Ageism in China's Workplace
Bibliographic record
Abstract
ABSTRACT This study examines the prospective motherhood penalty encountered by women white‐collar workers of childbearing age, regardless of their childbearing status, in China's non‐state‐owned enterprises. Drawing on 63 qualitative interviews with women employees, selected from a broader study of 85 participants, it explores how women subjectively experience, emotionally negotiate, and strategically respond to anticipated discrimination based on reproductive potential. I introduce the concept of the Career‐Fertility Countdown—a socially constructed and culturally enforced temporal regime that compresses women's career advancement and childbearing into a narrow window of acceptability. To navigate these multifaceted pressures, women adopt diverse strategies: those intending to have children engage in strategic timing and planning, whereas those determined to remain childfree—particularly lesbian women—engage in strategic gender performance and identity signaling. The Career‐Fertility Countdown framework highlights how time, gender, and organizational expectations interact to shape embodied pressures and identity strategies, particularly under China's overwork‐intensive and ageist labor regime. Drawing on narratives from women of varied backgrounds, this study contributes to feminist understandings of how reproductive timelines are internalized and negotiated in competitive workplaces, where prospective motherhood becomes a source of precariousness for all women. The findings also emphasize the importance of incorporating age‐related cultural paradigms when studying women's barriers in the workplace. Such paradigms may exacerbate tensions between work and family aspirations and amplify gender discrimination for women at particular career stages.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".