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Record W2789812690

Developing the Law of Evidence: a Proposal

2011· article· en· W2789812690 on OpenAlexaboutno aff
Martin L. Friedland

Bibliographic record

VenueTSpace (University of Toronto) · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicJury Decision Making Processes
Canadian institutionsnot available
Fundersnot available
KeywordsLawPolitical science
DOInot available

Abstract

fetched live from OpenAlex

Parliament should enact a clear and comprehensive statement of the rules of evidence.The present case-by-case method of developing the law of evidence contributes to confusion, to lengthy trials, and to delayed justice.Canada was close to enacting such a statement in the 1980s, but the effort was abandoned and has for the most part been forgotten.It is time to renew efforts to produce a legislative statement of the rules of evidence.This paper suggests that the Supreme Court of Canada could play a role in developing the rules outside its normal judicial process, perhaps using the auspices of the Canadian Judicial Council or the National Judicial Institute.This is the technique now successfully used by the Supreme Court of the United States to develop the Federal Rules of Evidence, which Congress accepts unless there is a negative vote to reject the changes. Le Parlement devrait dicter un nonc clair et complet des rgles de preuve. La mthode actuelle d'laboration des rgles de preuve au cas par cas engendre la confusion, les procs interminables et des retards dans le processus judiciaire. LeCanada a presque dict un tel nonc dans les annes 80, mais l'initiative a depuis t abandonne et oublie par plusieurs.Il est temps de ressusciter les travaux pour produire un nonc lgislatif concernant les rgles de preuve.Dans cet article, l'auteur suggre que la Cour suprme du Canada joue un rle dans le processus d'laboration de ces rgles en dehors de son cadre judiciaire normal, peut-tre mme sous les auspices du Conseil canadien de la magistrature ou de l'Institut national de la magistrature.Cette technique est utilise avec succs par la Cour suprme des tats-Unis pour l'laboration de leurs rgles fdrales de preuve, que le Congrs accepte moins qu'il n'y ait un vote ngatif visant rejeter les modifications.

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)0.154
metaresearch head score (Gemma)0.174
Version: metacan-v3-hybrid-931329e0061cValidation 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: Methods · Consensus signal: none
Teacher disagreement score0.154
Threshold uncertainty score0.816

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1540.174
Meta-epidemiology (narrow)0.0020.003
Meta-epidemiology (broad)0.0020.007
Bibliometrics0.0090.004
Science and technology studies0.0080.029
Scholarly communication0.0280.043
Open science0.0090.016
Research integrity0.0700.037
Insufficient payload (model declined to judge)0.0100.006

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 head0.182
GPT teacher head0.360
Teacher spread0.178 · 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 designTheoretical or conceptual
Domainnot available
GenreMethods

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

Citations0
Published2011
Admission routes1
Has abstractyes

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