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Record W2973125892 · doi:10.5206/fpq/2019.3.6210

On Finding Yourself in a State of Nature

2019· article· en· W2973125892 on OpenAlexvenueno aff
Jordan Pascoe

Bibliographic record

VenueFeminist Philosophy Quarterly · 2019
Typearticle
Languageen
FieldMedicine
TopicReproductive Health and Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsAbortionAutonomyPrinciple of legalityInjusticeReproductive rightsMoral orderIdeal (ethics)SociologyLawParallelsPolitical scienceEpistemologyPhilosophyPregnancySocial science

Abstract

fetched live from OpenAlex

I defend the right to an abortion at any stage of pregnancy by drawing on a Kantian account of consent and innate right. I examine how pregnant women are positioned in moral and legal debates about abortion, and develop a Kanitan account of bodily autonomy in order to pregnant women’s epistemic authority over the experience of pregnancy. Second, I show how Kant's distinction between innate and private right offers an excellent legal framework for embodied rights, including abortion and sexual consent, and I draw on the legal definition of sexual consent in order to show how abortion discourse undermines women's innate right. I then explore Kant’s treatment of the infanticidal mother, and draw out the parallels between this case and contemporary abortion rights in order to develop a distinctly Kantian framework of reproductive rights in non-ideal conditions. Finally, I explore the implications of this non-ideal approach for contemporary abortion discourse, arguing that debates about the legality of abortion should more broadly engage the barbaric conditions of reproductive injustice.

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0050.020
Scholarly communication0.0040.006
Open science0.0010.004
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0120.004

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 head0.016
GPT teacher head0.300
Teacher spread0.284 · 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 designTheoretical or conceptual
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

Citations3
Published2019
Admission routes1
Has abstractyes

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