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Record W4384826221 · doi:10.1093/bjc/azad030

Rescuing women from the brinks of whiteness: Carceral restoration in a human trafficking court

2023· article· en· W4384826221 on OpenAlexafffund
Rashmee Singh

Bibliographic record

VenueThe British Journal of Criminology · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicSex work and related issues
Canadian institutionsUniversity of Waterloo
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsCriminologyPrioritizationHuman traffickingPolitical scienceDrug traffickingRace (biology)SociologyLawGender studiesEngineering

Abstract

fetched live from OpenAlex

Abstract Research on gender-specific penal reform programs critique their failure to prioritize the socio-economic recovery of criminalized women. This paper draws on these insights to examine the Women’s Refuge Court (WRC), a human trafficking court for adult women criminalized for prostitution and drug offences in Ohio. Using ethnographic research, I illustrate the WRC’s rejection of bootstrapping and emphasis on material resourcing as a penal reform strategy. I argue that the WRC’s prioritization of socio-economic recovery derives from fears over the status decline of the impoverished white women who predominate as defendants. Court officials rely on evangelical Christian imaginings of prostitution as ‘modern day slavery’ to frame participants as ‘trafficking victims’. I identify the WRC’s response as a racially specific form of gender responsive programming called carceral restoration.

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)0.004
metaresearch head score (Gemma)0.008
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.034
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0340.012
Scholarly communication0.0070.003
Open science0.0010.007
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0090.000

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 head0.063
GPT teacher head0.324
Teacher spread0.262 · 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

Citations0
Published2023
Admission routes2
Has abstractyes

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