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Record W2790393806 · doi:10.29173/alr1273

The Odhavji Decision: Old Ghosts and New Confusion in Canadian Courts

2005· article· en· W2790393806 on OpenAlexvenueaboutno aff
Michael E. Bodner

Bibliographic record

VenueAlberta Law Review · 2005
Typearticle
Languageen
FieldSocial Sciences
TopicLegal principles and applications
Canadian institutionsnot available
Fundersnot available
KeywordsTortSupreme courtLawConfusionEstateStatement (logic)Political scienceTort reformSociologyLiabilityPsychology

Abstract

fetched live from OpenAlex

The tort of misfeasance in public office was recently examined by the Supreme Court of Canada in Odhavj Estate v. Woodhouse. While the case provided a statement on the law in this area, it also left many questions unanswered. This article lays out the factual background of the case, the elements of the tort as laid down by the Court and the tort's relationship with other aspects of Canadian tort law. Further, the author critically examines the ambiguities and additional problems that have arisen in the wake of the decision and how the lower courts have been dealing with the tort in subsequent cases. The author ultimately concludes that it is very likely that the Supreme Court of Canada will need to revisit this area of tort law in the years to come.

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)0.006
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.211
Threshold uncertainty score0.915

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0050.006
Science and technology studies0.0260.026
Scholarly communication0.0170.003
Open science0.0020.003
Research integrity0.0050.006
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 head0.024
GPT teacher head0.332
Teacher spread0.308 · 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 designNot applicable
Domainnot available
GenreCommentary

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
Published2005
Admission routes2
Has abstractyes

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