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Record W2279173580

Not a Lust Story: Judicial Imaginaries of Sexual Citizenship

2009· article· en· W2279173580 on OpenAlexaffabout
Ummni Khan

Bibliographic record

VenueSSRN Electronic Journal · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicLaw in Society and Culture
Canadian institutionsCarleton University
Fundersnot available
KeywordsThe ImaginaryHuman sexualityChauvinismLustPrerogativeHarmGender studiesCitizenshipPolitical scienceSociologySexual identityNormativeLawPsychologyPolitics
DOInot available

Abstract

fetched live from OpenAlex

This paper seeks to examine the explanations offered within the judicial imaginary to account for the desires of improper sexual subjects. I will consider primarily Canadian caselaw to investigate how the judicial imaginary makes sense of contested sexual practices by resorting to three interlocking sites of belonging and exclusion: gender, nation and humanness. I start by considering the gender imperatives perpetuated by the judicial analysis of contested sexual practices. I next consider how the Canadian courts circumscribe and limit the adjudicating national community, homogenizing Canadian sexual identity, and otherizing or marginalizing those whose sexuality does not fit within these discursive borders. Finally, I consider how these gender and national identity imperatives buttress judicially-articulated human imperatives, expunging practitioners of non-normative sexual behaviour from the category of human altogether. Ultimately, I argue that these judicial imperatives perpetuate the harm of what has been called sexual chauvinism, discriminating, devaluing and dehumanizing individuals based on their sexual practices, usually grounded upon stereotypes.

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)0.013
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.502
Threshold uncertainty score0.998

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0250.090
Scholarly communication0.0140.008
Open science0.0020.004
Research integrity0.0060.010
Insufficient payload (model declined to judge)0.0030.000

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 head0.014
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 designNot applicable
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
Published2009
Admission routes2
Has abstractyes

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