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Record W3024071414 · doi:10.2307/j.ctv10tq4d2

Decriminalising Abortion in the UK

2020· book· en· W3024071414 on OpenAlexfundno aff

Bibliographic record

VenuePolicy Press eBooks · 2020
Typebook
Languageen
FieldSocial Sciences
TopicHomicide, Infanticide, and Child Abuse
Canadian institutionsnot available
FundersEconomic and Social Research CouncilUlster UniversityQueen's University BelfastQueen's UniversityLondon School of Economics and Political ScienceNational Institute for Health and Care ExcellenceWellcome TrustLondon School of Hygiene and Tropical Medicine
KeywordsAbortionPregnancyBiology

Abstract

fetched live from OpenAlex

The public and parliamentary debate about UK abortion law is often diverted away from key moral and political questions by disputes regarding basic questions of fact. And all too often, claims of scientific ‘fact’ are ideologically driven. 
 With each chapter written by leading experts in the fields of medicine, law, reproductive health and social science, this book offers a concise and authoritative account of the evidence regarding the likely impact of decriminalisation. 
Examining specific yet diverse regional and local contexts across Europe, this book uses original research to evaluate differences in scope, approach, orientation, and objectives. It examines the embedding of LLL policies into the regional economy, the labour market, education and training systems and the individual life projects of young people, with a focus on those in situations of near social exclusion. "

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 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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.930
Threshold uncertainty score0.974

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.074
GPT teacher head0.349
Teacher spread0.276 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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
Published2020
Admission routes1
Has abstractyes

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