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Record W4395059445 · doi:10.29173/alr2689

Criminal Justice Reform: A Transformative Agenda

2022· article· en· W4395059445 on OpenAlexaffvenue
Terry Skolnik

Bibliographic record

VenueAlberta Law Review · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicCriminal Justice and Corrections Analysis
Canadian institutionsYouth Research and Evaluation eXchangeUniversity of Ottawa
Fundersnot available
KeywordsTransformative learningCriminal justicePolitical scienceEconomic JusticeCriminologyLaw and economicsLawSociology

Abstract

fetched live from OpenAlex

Few of the criminal justice system’s problems are new. Indigenous and racialized persons continue to be over-represented in the criminal justice system. Pretrial detention rates have increased significantly during the past 30 years. The criminal law is still used to regulate social problems — poverty, homelessness, and substance use — that it cannot fix. Although law reform happens with some frequency, these underlying problems persist. This article advances a transformative agenda for criminal justice reform. It argues that law reform fails to address three mutually reinforcing features of the criminal justice system that exacerbate its persisting problems. First, reform efforts accord insufficient importance to rehabilitation and reintegration. Second, reform initiatives do not address the growth of police powers that lack adequate transparency and oversight. Third, existing reforms ignore how the justice system increasingly allocates power towards prosecutors and the police, while removing that power from judges. This article’s core argument is that the criminal justice system must be completely transformed in order to address its underlying issues. It contends that meaningful criminal justice reform must take place across four dimensions: (1) substantive criminal law reform; (2) sentencing reform; (3) criminal procedure reform; and (4) institutional reform. It concludes by providing an agenda for criminal justice reform, which includes a set of concrete proposals in each of these four dimensions. Ultimately, this article shows why transformative law reform is necessary to treat individuals with greater dignity, foster rehabilitation and reintegration, and combat the criminal justice system’s worst tendencies.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.929
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.047
GPT teacher head0.351
Teacher spread0.303 · 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.

Study designNot applicable
Domainnot available
GenreOther

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

Citations2
Published2022
Admission routes2
Has abstractyes

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