Do Fathers Who Took Childbirth Leave Become More Involved in Their Children’s Care? The Case of Spain
Bibliographic record
Abstract
This article is based on a survey that we conducted among 1,130 couples with children 3-8 years old, in Madrid and its metropolitan area. This allowed us, in the first place to obtain an estimation of the take-up rate and duration of the different kinds of childbirth leaves that Spanish workers use when they have or adopt a child. In the second place, the participation of the father has been analyzed in comparison to the mother’s in 18 specific childcare activities. A measure for father involvement in childcare (relative to the mother) that included 14 non-playful activities of childcare was built from there. Then, from a quantitative analysis with path analysis modelling with Amos program, we have obtained evidence that fathers who took more time off later tended to be more involved in the most routine childcare activities. Moreover, when considering other determinants of father’s involvement in childcare, we can highlight the importance of having egalitarian gender attitudes, working in a family-friendly company, the net earnings, and the mother’s working week. Most of these variables affect father’s involvement in childcare directly and indirectly, through their effects on the duration of childbirth leave (which serves as a mediating variable). Finally, a specific determinant of the duration of childcare leave was the introduction of a 13-day paternity leave in Spain, in March 2007.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".