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Record W2150441375 · doi:10.7202/017251ar

La négociation des sentences du point de vue des avocats de la défense

2005· article· en· W2150441375 on OpenAlexvenueno aff
Robert A. Poirier

Bibliographic record

VenueCriminologie · 2005
Typearticle
Languageen
FieldHealth Professions
TopicHealthcare Systems and Practices
Canadian institutionsnot available
Fundersnot available
KeywordsPleaSentencePolitical scienceObject (grammar)LawNegotiationCriminal lawCriminal trialPsychologyPhilosophyLinguistics

Abstract

fetched live from OpenAlex

This article discusses the findings of empirical research into the working habits of defence attorneys. Contrary to what is implied by the current expression “plea bargaining”, it is not the plea but the sentence which is the real object of the negotiations taking place between the prosecution and the defence. When no agreement is reached between the Crown prosecutor and the defence attorney, they resort to formal representations made before the judge during a sentencing hearing and argue for their conflicting recommendations. Hence, it is not a criminal trial but a formal sentencing hearing, where both parties argue their case, which is the outcome of a failure of the Crown and defence attorney to reach a negotiated agreement on the fate of a defendant.

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)0.015
metaresearch head score (Gemma)0.164
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 score0.015
Threshold uncertainty score0.081

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.164
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0040.006
Scholarly communication0.0080.005
Open science0.0010.004
Research integrity0.0040.007
Insufficient payload (model declined to judge)0.0040.001

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 head0.525
GPT teacher head0.553
Teacher spread0.028 · 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

Citations10
Published2005
Admission routes1
Has abstractyes

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