The Effects of Extended Parental Benefits on Parents’ Employment and Earnings in Canada
Bibliographic record
Abstract
Paid parental benefits, with individually earmarked time for mothers and fathers, aim to promote gender equality in labor force participation, wages, and childcare. The Canadian province of Québec expanded parental benefits over and above the federal policy in 2006 with the Québec Parental Insurance Plan (QPIP), which introduced paid paternity leave and lower eligibility criteria as its key features. This policy aimed to increase gender equality by encouraging fathers to use parental benefits and expanding coverage to low-income parents. Using Canadian administrative data and exploiting the policy changes in 2006 as a natural experiment, we examine the effects of Québec's extended parental benefits policy on parents' employment and earnings over 10 years after the transition to parenthood. First, we find that fathers' use of parental benefits had positive long-run effects on mothers' and fathers' earnings 8-10 years after a first birth. Second, we find that among women with low earnings before the transition to parenthood, QPIP increased the likelihood of employment 1-7 years after a first birth. This article provides the first evidence that a policy dramatically expanding parental benefits and encouraging use among both parents can have long-term positive effects on parents' labor market outcomes.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".