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Record W6999232375

The Challenges of Institutionalizing Comprehensive\nRestorative Justice: Theory and Practice in Nova Scotia

2006· article· en· W6999232375 on OpenAlexaboutno aff

Bibliographic record

VenueeYLS (Yale Law School) · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicCriminal Justice and Corrections Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsNova scotiaRestorative justiceEconomic JusticeRelation (database)State (computer science)Grounded theory
DOInot available

Abstract

fetched live from OpenAlex

The Nova Scotia Restorative Justice Program ("NSRJ") is one of the oldest and by all accounts the most comprehensive in Canada. The program centres on youth justice, and operates through referrals by police, prosecutors, judges and correctional officials to community organizations which facilitate restorative conferences and other restoratively oriented processes. More than five years of NSRJ experience with thousands of cases has led to a considerable rethinking of restorative justice theory andpractice in relation to governing policies, standards for program implementation and responses to controversial issues. The purpose of this paper is to explore the significance of the Nova Scotia experience to date for sustaining restorative justice beyond the pilot project stage, where a vision of community-based justice is institutionalized with the support ofconsiderable state resources. The first part of the paper explains the genesis, structure, theoretical goals and empirical evaluation of the program to date. The second part examines some of the challenges ofinstitutionalizing comprehensive restorative justice. The paper concludes with general observations about the broader implications for restorative justice theory and practice of the Nova Scotia experience.

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)0.007
metaresearch head score (Gemma)0.015
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 score0.089
Threshold uncertainty score0.646

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0140.016
Scholarly communication0.0090.002
Open science0.0020.007
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0010.000

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 head0.037
GPT teacher head0.338
Teacher spread0.300 · 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
Published2006
Admission routes1
Has abstractyes

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