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Record W2607065588 · doi:10.1177/1532708617704456

God’s Will

2017· article· en· W2607065588 on OpenAlexaff
Sonja Boon

Bibliographic record

VenueCulture Studies &#x2194 Critical Methodologies · 2017
Typearticle
Languageen
FieldArts and Humanities
TopicHistorical Studies on Reproduction, Gender, Health, and Societal Changes
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsPhilosophy

Abstract

fetched live from OpenAlex

This autoethnographic essay examines the complexity of reproductive storytelling. Framed around a pair of interwoven reproductive stories, and located within a reproductive justice framework, it asserts that women’s stories of fertility, pregnancy, contraception, and abortion have, both historically and in the contemporary period, been marked by silences. Such silences, the result of political, legal, social, and moral forces beyond women’s control, have limited women’s abilities to share and reflect on the intricate negotiations that have shaped their reproductive lives, and as a consequence, have also limited their capacities for telling their reproductive stories. As this article argues, all reproductive stories are complex stories. Too often, however, those complex nuances that shape women’s reproductive lives and stories remain hidden, unspoken, and secret. Making room for the intricacies of reproductive stories and storytelling can also, this article argues, offer greater nuance to continuing debates around reproductive rights and reproductive justice.

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.042
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0070.006
Scholarly communication0.0040.004
Open science0.0010.003
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0420.013

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 head0.406
GPT teacher head0.462
Teacher spread0.056 · 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 designQualitative
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

Citations2
Published2017
Admission routes1
Has abstractyes

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