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Record W2534793601

'Considering Aboriginal disadvantage ' in sentencing decisions

2014· article· en· W2534793601 on OpenAlexaboutno aff
Chris Charles

Bibliographic record

VenueBulletin (Law Society of South Australia) · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicCriminal Justice and Corrections Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsAppealHigh CourtDisadvantageSentenceLawPolitical scienceCriminologySentencing guidelinesSociologyPhilosophy
DOInot available

Abstract

fetched live from OpenAlex

In October last year, the High Court handed down a unanimous decision on a sentencing appeal from the New South Wales Court of Criminal Appeal (NSWCCA). Bugmy v R was decided on the very narrow ground that the NSWCCA had wrongly allowed a prosecution appeal as to the inadequacy of Mr Bugmy's sentence, without actually deciding that his sentence was manifestly inadequate. For that reason his appeal was allowed. The High Court also held that the CCA had erred in holding that the degree to which his deprived background as an Aboriginal person could be taken into account in sentencing, diminished with time and repeat offending. In allowing the appeal, the High Court said much on the topic of sentencing Aboriginal people and reaffirmed existing precedents. The 1982 High Court decision of Neal v R and the NSW decision of Fernando were reaffirmed and consideration was given to various Canadian decisions on sentencing Aboriginal people. They raised the question of the degree to which grossly disproportionate incarceration rates can or cannot be considered in sentencing discretions.

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)0.017
metaresearch head score (Gemma)0.049
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.318
Threshold uncertainty score0.632

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.049
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0240.008
Scholarly communication0.0080.003
Open science0.0030.006
Research integrity0.0110.011
Insufficient payload (model declined to judge)0.0040.000

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 head0.046
GPT teacher head0.346
Teacher spread0.300 · 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 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

Citations1
Published2014
Admission routes1
Has abstractyes

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