In and out of the labour market: long‐term income consequences of child‐related interruptions to women's paid work
Bibliographic record
Abstract
Why do Canadian mothers have lower incomes than women who have never had children? Microdata from the 1995 GSS allow examination of two hypotheses: (1) mothers have spent more time out of the labour force, thus acquiring less human capital; (2) higher levels of unpaid work lead to fatigue and/or scheduling difficulties. Measuring work history does little to account for the ‘family gap.’ The estimated child penalty is reduced by allowing for ‘human capital depreciation’ and controlling for unpaid work hours, but the two hypotheses together cannot entirely explain the gap. JEL Classification: J0, J3 Entrées et sorties: marché du travail et conséquences à long terme des interruptions dans l'expérience sur le marché du travail à cause des enfants. Ce mémoire se demande pourquoi les femmes canadiennes qui ont eu des enfants ont des revenus plus bas que ceux des femmes qui n'en ont pas eus. Les microdonnées de l'Enquête sociale générale de 1995 de Statistiques Canada permettent d'examiner deux hypothèses: (1) les mères ont passé plus de temps en dehors de la main d'oeuvre active et donc ont accumulé moins de capital humain, ou (2) des niveaux plus élevés de travail non‐rémunéré peuvent entraîner fatigue ou difficultés d'organisation du temps. Des efforts pour construire une meilleure image de l'expérience de travail des femmes ne permettent pas d'expliquer cet ‘écart familial,’ même si la possibilité qu'il y ait ‘dépréciation du capital humain’ réduit la pénalisation attachée au fait d'avoir un enfant en particulier si l'interruption dans l'expérience sur le marché du travail est suivie d'un changement d'emploi. Le nombre hebdomadaire d'heures de travail non payé est relié négativement aux revenus, et si l'on normalise pour tenir compte des heures de travail non payé cela réduit la pénalisation attachée au fait d'avoir un enfant. Cependant les deux hypothèses combinées ne suffisent pas pour expliquer l'écart.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".