Policy as normative influence? On the relationship between parental leave policy and social norms in gender division of childcare across 48 countries
Bibliographic record
Abstract
In the present work, we addressed the relationship between parental leave policies and social norms. Using a pre-registered, cross-national approach, we examined the relationship between parental leave policies and the perception of social norms for the gender division of childcare. In this study, 19,259 students (11,924 women) from 48 countries indicated the degree to which they believe childcare is (descriptive norm) and should be (prescriptive norm) equally divided among mothers and fathers. Policies were primarily operationalized as the existence of parental leave options in the respective country. The descriptive and prescriptive norms of equal division of childcare were stronger when parental leave was available in a country - also when controlling for potential confounding variables. Moreover, analyses of time since policy change suggested that policy change may initially affect prescriptive norms and then descriptive norms at a later point. However, due to the cross-sectional nature of the data, drawing causal inferences is difficult.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".