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Record W3210627060 · doi:10.31219/osf.io/2frts

International Review of Leave Policies and Research 2024

2024· article· en· W3210627060 on OpenAlex
Sonja Blum, Alison Koslowski, Peter Moss

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicMedical and Agricultural Research Studies
Canadian institutionsnot available
Fundersnot available
KeywordsChinaPolitical scienceCzechSlovakGeographyEconomic growthEconomics

Abstract

fetched live from OpenAlex

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 2024 International Review covers 51 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, 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. Vietnam 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.The International Review is available online either as one complete document; or, for ease of downloading, divided into its constituent parts.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.580
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.181
GPT teacher head0.541
Teacher spread0.360 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Quick stats

Citations134
Published2024
Admission routes1
Has abstractyes

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