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Record W4384627483 · doi:10.1002/ijgo.15017

The <scp>WHO</scp> abortion care guideline: Law and policy—Past, present, and future

2023· article· en· W4384627483 on OpenAlexaff
Joanna N. Erdman

Bibliographic record

VenueInternational Journal of Gynecology & Obstetrics · 2023
Typearticle
Languageen
FieldMedicine
TopicReproductive Health and Contraception
Canadian institutionsDalhousie University
Fundersnot available
KeywordsAbortionGuidelinePsychological interventionContext (archaeology)Health careAbortion lawPolitical sciencePublic relationsMedicineBusinessLawPublic administrationNursingFamily planningEnvironmental health

Abstract

fetched live from OpenAlex

In the 2022 Abortion Care Guideline, the World Health Organization (WHO) undertook systematic evidence reviews of seven law and policy interventions to assess their health and social impacts. Distinct recommendations were formulated for each. The present article highlights how the Guideline reconceptualizes abortion regulation as a complex structural intervention that shapes clinical care and service delivery and distributes risks and resources within these systems and in the care relations that define them. It then presents the Guideline recommendations and summarizes their evidence base, drawing on recent legal and policy developments to emphasize their real-world significance. The article concludes by anticipating the future of abortion law and policy, focusing on service delivery innovations and diverse care models, drug regulation and the supply of abortion pills, and protective interventions crafted in the context of political crisis and immediate need that serve policy objectives and take regulatory forms different from the past.

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)0.029
metaresearch head score (Gemma)0.076
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.096
Threshold uncertainty score0.190

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0290.076
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.004
Bibliometrics0.0060.007
Science and technology studies0.0020.004
Scholarly communication0.0050.004
Open science0.0060.004
Research integrity0.0170.014
Insufficient payload (model declined to judge)0.0040.002

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 head0.013
GPT teacher head0.332
Teacher spread0.319 · 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 designNot applicable
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

Citations11
Published2023
Admission routes1
Has abstractyes

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