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Record W2579139332 · doi:10.29173/alr783

The Case for a New Compassionate Release Statutory Provision

2017· article· en· W2579139332 on OpenAlexaffvenueabout
Adelina Iftene

Bibliographic record

VenueAlberta Law Review · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicCriminal Justice and Corrections Analysis
Canadian institutionsSocial Sciences and Humanities Research CouncilYork University
Fundersnot available
KeywordsStatutory lawPrisonContext (archaeology)Set (abstract data type)PopulationCompassionate UsePolitical scienceCriminologyBusinessLaw and economicsPublic relationsPsychologyLawSociologyMedicineHistoryEnvironmental health

Abstract

fetched live from OpenAlex

In the last decade there has been a steady growth in the number of federally incarcerated people aging in prisons. These individuals have a long list of medical needs while they present a low risk to communities. However, this category of people tends to spend more time in prison than their younger counterparts and face difficulties in being released. Using original empirical data, as well as the existing literature, I argue that a high number of these individuals need to be released through a compassionate release mechanism. This article has two purposes. One is to show that compassionate release does not really exist in Canada. Section 121 of the Corrections and Conditional Release Act — parole by exception — is the closest Canada has to release on humanitarian grounds, but it fails to fulfill this role. The second purpose is to argue that the lack of a functional compassionate release provision is unacceptable, particularly in the context of the increase among the prison population of medical conditions associated with aging. I maintain that a system which is not flexible enough to consider extreme post-incarceration circumstances of an offender, and does not allow for a modification of the place where individuals serve their sentence based on these circumstances, is disconnected from any medical, penological, humanitarian, or constitutional requirements. Finally, I provide a set of recommendations for the redrafting of section 121.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.947
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0050.000
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 head0.047
GPT teacher head0.381
Teacher spread0.335 · 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
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

Citations4
Published2017
Admission routes3
Has abstractyes

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