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Record W2047902923 · doi:10.3138/cjccj.50.2.117

The Rise and Fall of RCMP Community Justice Forums: Restorative Justice and Public Safety Interoperability in Canada

2008· article· en· W2047902923 on OpenAlexaffvenueabout
John Edward Deukmedjian

Bibliographic record

VenueCanadian Journal of Criminology and Criminal Justice/La Revue canadienne de criminologie et de justice pénale · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicPolicing Practices and Perceptions
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsRestorative justicePeacemakingAgency (philosophy)Government (linguistics)Public administrationEconomic JusticeCorporate governancePublic relationsPolitical scienceInteroperabilityCollaborative governanceImmigrationSociologyCriminologyLawBusinessSocial science

Abstract

fetched live from OpenAlex

RCMP executives and the Canadian government promoted community justice forums (family group conferences) in the late 1990s. They did so because CJFs offered a process consistent with the national community-policing strategy. When this strategy changed, executives cut their support for the program. This paper argues that this “rise” and “fall” was a function of the program's theoretical and procedural alignment with shifting strategies of national governance. This raises a question about the role of restorative forums in Canadian governance. If such programs remain desirable, multi-agency forums (police, public schools, child welfare, immigration) may well align with the nascent governmental framework of public safety interoperability. The paper also considers another possibility: non-state local peacemaking forums. The conclusion discusses potential benefits and limits of these possibilities. It also offers general theoretical observations on the role of alignment in governmental programming.

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)0.006
metaresearch head score (Gemma)0.011
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 score0.093
Threshold uncertainty score0.675

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0270.012
Scholarly communication0.0090.004
Open science0.0020.006
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0050.000

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 head0.184
GPT teacher head0.348
Teacher spread0.164 · 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

Citations9
Published2008
Admission routes3
Has abstractyes

Explore more

Same venueCanadian Journal of Criminology and Criminal Justice/La Revue canadienne de criminologie et de justice pénaleSame topicPolicing Practices and PerceptionsFrench-language works237,207