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Record W2245648687

'Canada' in Electronic Evidence

2010· article· en· W2245648687 on OpenAlexaffabout
Steve Coughlan

Bibliographic record

VenueeYLS (Yale Law School) · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicCriminal Law and Evidence
Canadian institutionsDalhousie University
Fundersnot available
KeywordsAppealLawPolitical scienceCivil law (Civil law)Supreme courtCommon lawCivil procedureFederal Rules of Civil ProcedureCivil codePublic law
DOInot available

Abstract

fetched live from OpenAlex

Canada is a bilingual and bi-jurisdictional country. Most provinces and territories are mainly English speaking and have common law as the basis for their legal system. The exception is the province of Quebec which is governed by civil law and where the majority speaks French. However, it must be noted that Quebec civil law has been substantially affected by common law, in particular with respect to discovery rules. The latter are closer to common law discovery rules than they are from, for instance, French civil law. Another important factor for the review of the management of digital evidence in Canada is the existence of different jurisdictions within each province. Canada has a federal system, with a national court system and court systems in each province and territory. The federal courts have limited authority and focus mainly on immigration, intellectual property, maritime and other 'national concerns'. The courts of appeal, the superior (or supreme, depending on the province or territory) courts, the provincial courts and administrative tribunals in each province hear the bulk of the cases. Provincial laws dictate the practice of civil litigation, and discovery is governed by rules of civil procedure or, in Quebec, the Code of Civil Procedure (C.C.P.).

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.966
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.022
GPT teacher head0.297
Teacher spread0.275 · 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 designNot applicable
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
Published2010
Admission routes2
Has abstractyes

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