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Record W867725853

A 'Local' Response to Community Problems? A Critique of Community Justice Panels

2014· article· en· W867725853 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueRepository@Nottingham (University of Nottingham) · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicCriminal Justice and Corrections Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsGlobeRestorative justiceCriminal justiceCriminologyEconomic JusticePublic relationsSociologyPolitical sciencePublic administrationLawPsychology
DOInot available

Abstract

fetched live from OpenAlex

Community justice panels have had a long and varied history and are now established at one level or another in most advanced neoliberal states. They involve local members of the community as volunteers in responding to crime and have been lauded for their potential to reduce offending behaviour and provide a more localised, culturally sensitive approach to crime committed by people from those communities. Despite these claims, they have received relatively little attention from scholars working in the areas of community justice and restorative justice. This article seeks to review two different models of community justice panels. The first are those which have been devised in the United States, and subsequently England and Wales, to involve the community in the ‘fight against crime’. The second are those used in Australia and Canada which seek to minimise the use of a formal criminal justice response to offending behaviour by Indigenous peoples and to facilitate a culturally sensitive approach in those cases in which a formal response is unavoidable. Despite their perceived distinct orientation, this article demonstrates that both models have inherent limitations in attempting to ‘localise’ justice.

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.

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.153
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0040.001
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 head0.029
GPT teacher head0.287
Teacher spread0.258 · 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