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Record W4398834468 · doi:10.7910/dvn/sczu92

PROSPERED Dataset: Maternity leave policy

2018· dataset· en· W4398834468 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueHarvard Dataverse · 2018
Typedataset
Languageen
FieldSocial Sciences
TopicRetirement, Disability, and Employment
Canadian institutionsMcGill University
FundersCanadian Institutes of Health Research
KeywordsMaternity leaveBusinessData scienceComputer scienceDemographic economicsEconomics

Abstract

fetched live from OpenAlex

This dataset captures whether women have a legislated right to paid maternity leave and/or parental leave. Longitudinal information on maternity leave policies includes whether paid leave was available for mothers to care for their infants, its length, and the rate at which wages were replaced. Length of leave was recorded in weeks without distinguishing between what portions of the leave have to be taken before and after the birth of the child. Scope: Longitudinal data is available for every year between 1995-2013 for the 121 countries that have been surveyed by either the Demographic and Health Surveys (DHS) or the Multiple Indicator Cluster Surveys (MICS) at least once between those dates.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.104
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0020.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0620.166

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 head0.147
GPT teacher head0.413
Teacher spread0.266 · 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