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Record W2952288172 · doi:10.1080/26410397.2019.1626181

The gender injustice of abortion laws

2019· letter· en· W2952288172 on OpenAlexaff
Joanna N. Erdman

Bibliographic record

VenueSexual and Reproductive Health Matters · 2019
Typeletter
Languageen
FieldSocial Sciences
TopicInternational Human Rights and Reproductive Law
Canadian institutionsDalhousie University
Fundersnot available
KeywordsInjusticeAbortionHuman rightsLawReading (process)Political scienceEconomic JusticeCriminal lawCriminologySociology

Abstract

fetched live from OpenAlex

This commentary is a response to Katarzyna Sękowska-Kozłowska's article on the treatment of criminal abortion laws as a form of sex discrimination under international human rights law through a study of the communications, Mellet v. Ireland and Whelan v. Ireland. The commentary offers a reading of these communications, and specifically the sex discrimination analysis premised on inequalities of treatment among women, as an engagement with the structural discrimination that characterises abortion laws, and as a radical vision for gender justice under international human rights law.

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)0.007
metaresearch head score (Gemma)0.022
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: Commentary · Consensus signal: Commentary
Teacher disagreement score0.037
Threshold uncertainty score0.072

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.022
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0100.012
Scholarly communication0.0050.004
Open science0.0020.004
Research integrity0.0370.021
Insufficient payload (model declined to judge)0.0060.002

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 head0.050
GPT teacher head0.352
Teacher spread0.302 · 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
GenreCommentary

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

Citations3
Published2019
Admission routes1
Has abstractyes

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