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Record W2269571185 · doi:10.3138/cjwl.27.2.284

Transforming Choices: The Marginalization of Gender-Specific Policy Making in Canadian Approaches to Women's Federal Imprisonment

2015· article· en· W2269571185 on OpenAlexaboutno aff
Kelly Struthers Montford

Bibliographic record

VenueCanadian Journal of Women and the Law/Revue Femmes et Droit · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicCriminal Justice and Corrections Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsImprisonmentConceptualizationArgument (complex analysis)Political scienceService (business)SociologyLawMedicineBusiness

Abstract

fetched live from OpenAlex

In 2008, the Correctional Service of Canada accepted the 2007 report of Correctional Service of Canada Review Panel, A Roadmap to Strengthening Public Safety. This document provides the basis for the “transformation agenda” that now guides the administration of imprisonment for all populations. For federally sentenced women, this approach coexists with the recommendations made by the Task Force for Federally Sentenced Women in their 1990 report, Creating Choices. This analysis compares the composition of the committees responsible for these documents, their mandates, their consultation processes, and how these factors shaped their respective conclusions and recommendations. While Creating Choices can be understood as a feminist policy document, Roadmap employs a gender-neutral law-and-order discourse—its authors assume that the recommendations they make for male prisoners can be applied to women and minority groups. Shifting discourses about women, gender equality, and imprisonment are evident and are consistent with Laureen Snider's argument that the dominant conceptualization of imprisoned women has changed from that of the “woman in trouble” to that of the “atavistic woman.” Its implementation marks a shift in the trajectory of women's imprisonment and is a material example of the marginalization of gender considerations in public policy.

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)0.003
metaresearch head score (Gemma)0.000
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 score0.253
Threshold uncertainty score0.677

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.108
GPT teacher head0.293
Teacher spread0.185 · 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

Citations3
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Women and the Law/Revue Femmes et DroitSame topicCriminal Justice and Corrections AnalysisFrench-language works237,207