Workplace Productivity: Gender, Parenthood, and Career Consequences in the United States
Bibliographic record
Abstract
ABSTRACT Many dual‐earner parents face ongoing challenges to securing reliable and accessible childcare, which potentially affect their productivity at work and consequential career rewards. Although productivity can ebb and flow, limited research has examined how productivity changes influence parents' access to organizational rewards, especially when productivity changes result from childcare issues outside their control. The answer to this question is crucial for understanding gender inequality given that childcare issues are more likely to affect mothers' productivity and employers could enact gender biases toward mothers (or fathers) when their productivity changes. Using a novel survey experiment fielded among 975 US managers, we assessed how a parent's productivity changes (because of childcare issues outside their control) influenced managers' recommendations of future organizational rewards (pay, promotions, etc.) to the parent. First, we find that managers assigned lower career rewards to workers whose productivity decreased, relative to workers whose productivity increased or stayed constant. Second, managers more severely penalized mothers, compared to fathers, when their productivity decreased. Third, exploratory analyses suggested that the widened gender gap in career rewards among parents whose productivity decreased was driven by men managers who penalized fathers less than women managers, primarily because men managers did not view fathers' decreased productivity as evidence of reduced competence, professional commitment, or interest in advancement. By revealing pro‐male biases that help explain the greater penalties faced by mothers relative to fathers when their productivity declined, our findings expose potential long‐lasting impacts of parents experiencing disruptions to childcare on gender inequality in the workplace.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".