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Record W7071259963

Sentencing chronic offenders: 30 strikes and you're out?

2011· article· en· W7071259963 on OpenAlexaboutno aff

Bibliographic record

VenueArca (British Columbia Electronic Library Network) · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicCriminal Justice and Corrections Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsLegislationProportionality (law)CommitDenialCriminal lawSentenceCulpabilitySentencing guidelines
DOInot available

Abstract

fetched live from OpenAlex

Canadian legislation surrounding sentencing has been prefaced by a statement of the purposes and principles of sentencing since 1996. This legislation identifies proportionality as the fundamental principle in sentencing, and states that sentences should be proportional to the gravity of the offence and the degree of responsibility of the offender. Although prior criminal record may be considered as an aggravating factor by the judiciary when deciding upon an appropriate sentence, our current legislation does not mirror other sentencing systems such as those seen in the United States, where a criminal record may at times form the sole basis for the increasing length of incarceration. The Canadian experience with the sentencing of chronic offenders is an important indicator of sentencing policy in practice. If proportionality is the primary goal of sentencing, how are Canadian judges handling those chronic property offenders who commit dozens or even hundreds of offences over their criminal history? Are sentences strictly controlled by the gravity of the instant offence or are they being inflated by the offender’s criminal history? The aim of this study is to examine if indicators of sentence inflation can be observed in the sentencing patterns for one such group of chronic offenders. In general, the results appear mixed, as some increasing severity outside of the nature of the offence can be seen in terms of denial of bail and imposition of a custodial sentence. However, analysis of the length of the custodial sentences does not clearly demonstrate substantial inflation over those that would be expected solely on the basis of proportionality even for the most incorrigible offenders. What this creates, however, is a revolving door for many of these offenders. The difficulty comes with trying to balance the needs of the public in terms of protection from such chronic offenders (Street Crime Working Group, 2005), while still adhering to the legislated purposes and principles of sentencing.

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)0.001
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.609
Threshold uncertainty score0.787

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0040.002
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.021
GPT teacher head0.225
Teacher spread0.204 · 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 designObservational
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
Published2011
Admission routes1
Has abstractyes

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