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Record W2337209174

Perpetuating the Cycle of Abuse: Feminist (Mis)Use of the Public/Private Dichotomy in the Case of Nixon v. Rape Relief

2015· article· en· W2337209174 on OpenAlexaffabout
Ummni Khan

Bibliographic record

VenueSSRN Electronic Journal · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicSexual Assault and Victimization Studies
Canadian institutionsCarleton University
Fundersnot available
KeywordsTranssexualComplaintDisadvantagePolitical scienceCriminologyLawSociologyTransgenderGender studies
DOInot available

Abstract

fetched live from OpenAlex

This article addresses the human rights case between Kimberly Nixon, a transsexual woman, and Vancouver Rape Relief and Women's Shelter (Rape Relief), a women-only collective, by critically analyzing the legal arguments and justifications put forth by Rape Relief and its counsel. Nixon was denied the opportunity to volunteer at Rape Relief on the basis that she was allegedly not born a woman and was not treated as one her entire life. By engaging in a discursive analysis of Rape Relief's oral arguments, Rape Relief's co-counsel Christine Boyle's academic arguments, and the judicial decisions related to the human rights complaint, I argue that Rape Relief exploited the governing assumptions of the public/private divide in its attempt to justify its exclusionary policy against transsexual women volunteers.As my title suggests, Rape Relief's use of the public/private dichotomy could be understood as perpetuating a cycle of abuse: it appropriated and perpetuated a legal principle that has consistently been used to the disadvantage of all women in society. Ultimately, I posit that Rape Relief's arguments worked against the interests of both transsexual and non-transsexual women.

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)0.006
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.447
Threshold uncertainty score0.935

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
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 head0.044
GPT teacher head0.325
Teacher spread0.280 · 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 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

Citations1
Published2015
Admission routes2
Has abstractyes

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