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Record W4389583348 · doi:10.5040/9781509967032

Landmark Cases in the Law of Punitive Damages

2023· book· en· W4389583348 on OpenAlexaboutno aff

Bibliographic record

VenueHart Publishing eBooks · 2023
Typebook
Languageen
FieldSocial Sciences
TopicLegal principles and applications
Canadian institutionsnot available
Fundersnot available
KeywordsPunitive damagesJurisdictionDamagesTortLawPolitical scienceCommon law

Abstract

fetched live from OpenAlex

<JATS1:p>Punitive damages are private law’s most controversial remedy. This book traces the development of the jurisdiction from the foundational decisions of Huckle v Money and Wilkes v Wood in England, to leading modern cases such as Harris v Digital Pulse Pty Ltd in Australia, Whiten v Pilot Insurance Co in Canada, Couch v AG (No 2) in New Zealand, PH Hydraulics &amp; Engineering Pte Ltd v Airtrust (Hong Kong) Ltd in Singapore and Mathias v Accor Economy Lodging, Inc and State Farm Mutual Automobile Insurance Co v Campbell in the United States. Many of the decisions addressed are not only landmarks regarding punitive damages but are among the most important judgments delivered concerning private law more generally.</JATS1:p> <JATS1:p>The essays, which are written by leading scholars from a wide range of jurisdictions, cast new light on the cases covered. They do so by examining their historical antecedents and the impact that they have had on the development of the law. The full spectrum of issues regarding punitive damages is addressed including the insurability of punishment, constitutional constraints on the remedy’s availability and whether the award should be confined to particular causes of action. The collection will be of interest to all scholars and students of private law. It concentrates on common law cases although civilian perspectives, drawn from France and Germany, are also offered.</JATS1: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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.836
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.090
GPT teacher head0.331
Teacher spread0.241 · 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
GenreOther

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
Published2023
Admission routes1
Has abstractyes

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