MétaCan
Menu
Back to cohort
Record W2313970999 · doi:10.1177/1462474514539538

Aboriginalising the parole process: ‘Culturally appropriate’ adaptations and the Canadian federal parole system

2014· article· en· W2313970999 on OpenAlexaboutno aff
Sarah Turnbull

Bibliographic record

VenuePunishment & Society · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicCriminal Justice and Corrections Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsRepresentation (politics)Diversity (politics)Ethnic groupCriminologyAdaptation (eye)Cultural diversityProcess (computing)SociologyLinguistic diversityPolitical scienceLawPsychologyPoliticsLinguistics

Abstract

fetched live from OpenAlex

The increasing ‘diversity’ of penal populations in most western countries over the past three decades raises questions as to the fairness and appropriateness of established penal programmes and practices. In some jurisdictions, penal policy-makers and administrators are being forced to deal with the implications of offender diversities, including race, ethnicity, gender, culture and religion, in policy and planning. In Canada, the pervasive over-representation of Aboriginal individuals in prisons has led to calls for change in how the corrections and parole systems deal with Aboriginal prisoners. This article examines the advent of one ‘culturally appropriate’ adaptation of the parole process, the Elder assisted hearing, introduced in 1992 by the Parole Board of Canada as a means of (1) addressing the problem of over-representation and (2) being responsive to Aboriginal difference. It shows that the ‘Aboriginalisation’ of parole hearing formats is by no means a straightforward process, and is illustrative of the broader challenges that racial, cultural and gender differences pose to contemporary penality.

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.258
Threshold uncertainty score0.996

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 studies0.0060.000
Scholarly communication0.0010.000
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 head0.012
GPT teacher head0.269
Teacher spread0.257 · 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 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

Citations7
Published2014
Admission routes1
Has abstractyes

Explore more

Same venuePunishment & SocietySame topicCriminal Justice and Corrections AnalysisFrench-language works237,207