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Record W2799918838

THE CANADIAN DEFAMATION ACTION

2017· article· en· W2799918838 on OpenAlexaboutno aff
Hilary Young

Bibliographic record

VenueThe Canadian Bar Review · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicLegal principles and applications
Canadian institutionsnot available
Fundersnot available
KeywordsPunitive damagesPlaintiffDamagesTortLiabilityLawCause of actionPolitical scienceQuarter (Canadian coin)Action (physics)BusinessHistory
DOInot available

Abstract

fetched live from OpenAlex

This article presents the results of a quantitative study of Canadian defamation law actions, focusing on reported decisions between 1973 and 1983 and between 2003 and 2013. It aims to contribute to debate about defamation law reform, to contribute to scholarly work in defamation law or in tort law and remedies more generally, and to inform lawyers who are involved in defamation litigation. Its findings include: that damages have almost doubled when adjusted for inflation between these two periods; that corporate defamation cases make up about a third of defamation cases; that plaintiffs established liability much less often between 2003 and 2013 than between 1973 and 1983; that punitive damages are awarded much more often to corporations than to human plaintiffs, and in higher amounts; that punitive damages were awarded in about a quarter of cases in both periods; and that the rate of liability is greater for publications on the internet (including email) than publications in other media.

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)0.003
metaresearch head score (Gemma)0.015
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.087
Threshold uncertainty score0.634

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0070.011
Science and technology studies0.0090.002
Scholarly communication0.0040.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0080.001

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 head0.128
GPT teacher head0.399
Teacher spread0.271 · 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
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

Citations0
Published2017
Admission routes1
Has abstractyes

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