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Record W4398221148 · doi:10.1177/00220183241251920

Double Jeopardy and Successive Prosecutions Based on the Same Prohibited Conduct: Equivalence of Approaches to Determining the Same Offence Dilemma in Comparative Perspective

2024· article· en· W4398221148 on OpenAlexaboutno aff
Ger Coffey

Bibliographic record

VenueThe Journal of Criminal Law · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Law and Human Rights
Canadian institutionsnot available
Fundersnot available
KeywordsDouble jeopardyDilemmaEquivalence (formal languages)Perspective (graphical)Law and economicsPolitical scienceLawSociologyMathematicsEpistemologyComputer sciencePhilosophyArtificial intelligenceDiscrete mathematics

Abstract

fetched live from OpenAlex

Post-acquittal retrials for substantially the same offence are possible in jurisdictions that have provided statutory modifications to the common law double jeopardy principle. The pleas in bar of prosecution, autrefois acquit (previously acquitted) and autrefois convict (previously convicted), are predicated on a final verdict of acquittal or conviction by a court of competent criminal jurisdiction for substantially the same offence. Differentiating similarities between the increasing volume of overlapping offences is the most litigated aspect of the double jeopardy principle. Seminal common law jurisdictions have adopted variations of the same elements approach that examines whether two or more offences arising out of the same prohibited conduct are the same based on an assessment of whether there is an element in one offence not in the comparable offence. Through doctrinal analysis of superior court jurisprudence in the Unites States, England and Wales, Canada, Australia and New Zealand, this article evaluates judicial formulations for determining the sameness of offences in comparative perspective. While the analysis is intrinsic to each jurisdiction, judicial formulations may nonetheless shed light on similar issues coming before courts of criminal justice in cognate jurisdictions.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.326
Threshold uncertainty score0.412

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 studies0.0010.001
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 head0.300
GPT teacher head0.390
Teacher spread0.090 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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
Published2024
Admission routes1
Has abstractyes

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