21st International Review of Leave Policies and Related Research 2025
Bibliographic record
Abstract
The International Network on Leave Policies and Research has been producing an annual review of leave policies and related research since 2005 (for earlier reviews, go to the network’s website www.leavenetwork.org). The review covers Maternity, Paternity and Parental leaves; leave to care for sick children and other employment-related measures to support working parents; and early childhood education and care policy. The International Review is based on country notes from each participating country, prepared by members of the network and edited by a team of network members. Each country note follows a standard format: details of different types of leave; the relationship between leave policy and early childhood education and care policy; recent policy developments; information on take-up of leave. The International Review also includes definitions of the main types of leave policies; and cross-country comparisons. These comparative overviews cover: each main type of leave; the relationship between leave and ECEC entitlements; and policy changes and developments since the previous review. We also include a technical appendix. The 2025 International Review covers 52 countries. These are: Argentina, Australia, Austria, Belgium, Bosnia and Herzegovina, Bulgaria, Brazil, Canada, Chile, China, Colombia, Croatia, Cyprus, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Israel, Ireland, Italy, Japan, Korea, Kosovo, Latvia, Lithuania, Luxembourg, Malta, Mexico, Netherlands, New Zealand, Norway, Poland, Portugal, Romania, Russian Federation, Serbia, Slovak Republic, Slovenia, South Africa, Spain, Sweden, Switzerland, Turkey, United Kingdom, United States of America, Uruguay and Vietnam. Kosovo is a new country note joining the review this year for the first time. The content of the International Review is to the best of our knowledge correct at the time of going to press, but mistakes may occur. If you should have a query or find an error, we would be grateful if you would contact the country note authors as relevant and the editors. We recommend that readers consult the most recent version of the International Review where possible, as we are unable to retrospectively rectify errors.
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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 | 0.012 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.016 | 0.016 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.025 | 0.006 |
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".