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Paid Family Leave Programs—Understanding the Consequences for Infant Health

2024· article· en· W4394567505 on OpenAlexaff
Katherine A. Ahrens, Teresa Janević, Jennifer A. Hutcheon

Bibliographic record

VenueJAMA Pediatrics · 2024
Typearticle
Languageen
FieldHealth Professions
TopicChild and Adolescent Health
Canadian institutionsUniversity of British Columbia
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institutes of Health
KeywordsMedicineFamily medicineOtorhinolaryngologyNeurologyPediatricsPsychiatry

Abstract

fetched live from OpenAlex

In this issue of JAMA Pediatrics, Debiasi and colleagues examine unintended consequences of Sweden's paid parental leave policy reforms in the 1980s on infant health. 1 Using an interrupted time series analysis with multiple treatment periods, they found the 1980 speed premium, which aimed to protect parents' earnings-based parental leave benefit if they had 2 children within 24 months, in advertently increased the risk of preterm birth (from approximately 4.4% to 5.6%, a relative increase of about 26%) and low-birth weight birth (approximately 3.0% to 3.4%, a relative increase of about 14%).These increased risks attenuated after the speed premium period increased to increased to 36 months in 1986.The authors found no effect of the policy changes on stillbirth and a slight decreased odds of small for gestational age among preterm births after the 1980 policy change, followed by no effect after the 1986 policy reform.The authors found effects only among births to mothers born in Sweden and other Nordic countries, even though the policies applied to all residents of Sweden.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0030.003
Open science0.0010.001
Research integrity0.0040.005
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 head0.162
GPT teacher head0.425
Teacher spread0.263 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2024
Admission routes1
Has abstractyes

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