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Record W3007157874 · doi:10.14453/ltc.659

A Rhetorical Matter of Life and Law: The Speculative Futures of (Bio)political Reproduction

2019· article· en· W3007157874 on OpenAlexaff
Stuart J. Murray

Bibliographic record

VenueLaw/text/culture · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicLaw in Society and Culture
Canadian institutionsCarleton University
Fundersnot available
KeywordsReproductionFutures contractRhetorical questionPoliticsLaw and economicsLawSociologyPolitical scienceEnvironmental ethicsPhilosophyEconomicsArtBiologyLiteratureEcologyFinancial economics

Abstract

fetched live from OpenAlex

This essay argues that the ‘materiality’ of life and law are today technological artefacts of a biopolitical project, and that sexual-reproductive and legislative boundaries are the boundaries around which power coheres and materializes—making life law’s matter, an effect that is slyly taken up as legal ‘cause’. I offer as case studies readings of two incommensurable texts: Milan Kundera’s political fiction, The Joke, and the contemporary fertility industry, an instantiation of biopolitical techno-science. Bringing into tension the ‘materiality’ of life and law across these two sites, I hope to surface some of the vernaculars of (bio)political power—rhetorical matters of historical, political, socioeconomic, and technological concern that nevertheless claim the objectivity of ‘matter’. Both texts also concern reproduction—sexual, artificial, cultural, political—and how it is used to promote a certain ideology of citizenship and to regulate political ‘freedoms’. While Kundera’s novel, written in the 1960s, represents a critique of ‘old’ materialism as the reproduction of Communist State power, here, in juxtaposition, Kundera’s fiction occasions my critique of (legal) ‘new’ materialism—as neoliberal and biopolitical investment in the speculative futures proffered by the fertility industry.

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)0.005
metaresearch head score (Gemma)0.011
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 score0.010
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0060.059
Scholarly communication0.0100.011
Open science0.0010.004
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0040.001

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 head0.283
Teacher spread0.268 · 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

Citations0
Published2019
Admission routes1
Has abstractyes

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