The Unintended Effect of Paternity Leave on Union Stability: Evidence from the Quebec Parental Insurance Program
Bibliographic record
Abstract
The transition to parenthood is often stressful, as parents balance work and family responsibilities and adjust to new social roles. Paid parental benefits policies are explicitly aimed to encourage return-to-work and enhance infant health. However, some recent policies also aim to equalize housework and paid work within families by earmarking weeks of parental benefits for fathers that cannot be transferred to mothers. We examine two theoretical frameworks from sociology and economics to highlight potential mechanisms through which such policies may increase or decrease union dissolution, and why the direction and magnitude of the effects might differ across subpopulations. Then, using population-level administrative data, we examine how the Quebec Parental Insurance Program affected union dissolution. We find that overall, the policy decreased the divorce/separation rate by 0.6% points, a 7% reduction in the rate overall (intent-to-treat). Further, we find that the effect of fathers using parental benefits on the risk of divorce (treatment-on-treated) is more than double the intent-to-treat estimate. The policy had the greatest effects in reducing union dissolution among couples likely to be more egalitarian in orientation, and led to no increase in divorce, even in the most traditional couples.
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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 | 0.006 | 0.032 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".