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Record W4396686688 · doi:10.29173/mlj1253

Chapter 15 – Rehabilitation, Intervention, and Parole for the Toronto 18: Dead Ends and Silver Linings

2021· article· en· W4396686688 on OpenAlexaboutno aff
Reem Zaia

Bibliographic record

VenueManitoba Law Journal · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicCriminal Justice and Corrections Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsIntervention (counseling)MilestoneCriminologyCriminal justiceSentencePolitical scienceRehabilitationState (computer science)PsychologyEconomic JusticeLawWork (physics)TerrorismEngineeringPsychiatryHistoryComputer science

Abstract

fetched live from OpenAlex

This chapter assesses the spectrum of intervention measures (on a state and non-state level) available to offenders who plan to, or have, committed terrorism-related offences. The author does so with a view to determining whether intervention measures or rehabilitative efforts are sufficiently mitigating for the purpose of sentencing or parole. The author begins by surveying various intervention programs in Canada for persons at the “pre-charge” stage and highlights their practical shortcomings. Relying on this information, she emphasizes that evidence of rehabilitation efforts or work with intervention groups can prove insufficient for the purpose of mitigating a sentence of incarceration or granting parole. The author argues that this phenomenon results in a dead-end at every milestone of the criminal justice system for offenders convicted for terrorism-related offences. Even in cases where offenders have shown an ability to rehabilitate, the weight of their rehabilitative efforts is often questioned by courts and the National Parole Board by virtue of the crime they committed.

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
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.889
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.024
GPT teacher head0.311
Teacher spread0.287 · 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 designOther design
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

Citations1
Published2021
Admission routes1
Has abstractyes

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