Work-Family Legislation in the United States, Canada, and Western Europe: A Quantitative Comparison
Bibliographic record
Abstract
and 77.5%.3In the fifteen countries that comprised the European Union (EU) before the eastern European countries were admitted in 2005, the female employment rate increased from 24.7% in 1994 to 35.4% in 2005. 4 In Canada, the percentage of women aged twenty-five to forty-four holding full-time jobs increased from 30% in 1976 to 42.7% in 2005.' This increased labor force participation of women, combined with the traditionally high labor force participation of men, has changed the dynamics of the family.Because a female taking care of the family with a male breadwinner is no longer the standard model, and women as well as men both participate in the labor force at high levels, all workers must now balance work and family responsibilities.Occasionally, these responsibilities will conflict.Thus, a substantial wealth of literature in the human resources field has developed on how this conflict is addressed. 6 This change in demographics raises the question of the extent to which the United States, through laws, should provide support to workers attempting to strike a balance between work and family.This paper attempts to address this question by drawing on a unique data set developed by
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.009 | 0.021 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".