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Record W2002028339 · doi:10.5235/20504721.2.2.165

A discursive analysis of restorative justice in British Columbia

2014· article· en· W2002028339 on OpenAlexaffabout
Tara Ney

Bibliographic record

VenueRestorative Justice · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicCriminal Justice and Corrections Analysis
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsRestorative justiceLegislationCriminologyEconomic JusticeCriminal justiceSociologyPolitical scienceLawLaw and economicsPublic administration

Abstract

fetched live from OpenAlex

Though restorative processes offer benefits to victims of crime that cannot be gained from the traditional justice system, and though there is a general upward acceptance of restorative approaches, institutionalising these practices is nevertheless sporadic and slow-paced. This paper focuses on a particular policy provision within the Criminal Victim Assistance Program in British Columbia that is incoherent with a network of legislation and regulations that support restorative approaches to crime, and is, at the same time, effective in denying victims of crime the ability to choose a restorative justice approach. A ‘policy as discourse’ (Bacchi, 2009) framework is used to ask: ‘How does this policy provision come to have such force?’ The discourse analysis shows the policy provision to reside at the intersection of three constitutive and, at times, contradictory discourses—in this case bureaucratisation, neoliberalism and feminism—that collude and compete to deny victims of crime a restorative justice process.

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)0.002
metaresearch head score (Gemma)0.005
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 score0.145
Threshold uncertainty score0.992

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0050.008
Science and technology studies0.0400.020
Scholarly communication0.0120.002
Open science0.0020.004
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0060.000

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 head0.022
GPT teacher head0.328
Teacher spread0.306 · 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

Citations4
Published2014
Admission routes2
Has abstractyes

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