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Record W3122822935

What the United States Taught the Commonwealth About Pure Economic Loss: Time to Repay the Favor

2011· article· en· W3122822935 on OpenAlexaboutno aff
Bruce Feldthusen

Bibliographic record

VenuePepperdine Digital Commons (Pepperdine University) · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Policy and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsCommonwealthLawPolitical scienceActuarial scienceEconomics
DOInot available

Abstract

fetched live from OpenAlex

This paper deals with a discussion of the comparative treatment of the recovery of pure economic loss in negligence, a topic that has dominated my scholarship for more than thirty years.'My purpose is more to discuss how my research in this area has been informed by comparative study than to articulate the relevant rules and principles themselves.Some of the points of substance I will make will be contentious, and I will leave those debates to other publications and other times.I hope this makes today's topic more interesting.Many American tort lawyers would not recognize "economic loss" as an organizing principle for tort law; or if they did, they might not restrict the topic to negligence law.In what I will loosely call the Commonwealth-England, Canada, Australia, and New Zealand-most lawyers would understand this subset of negligence law to include cases of the following types: 2 1. Negligent misrepresentation brought, for example, where a nonprivity third party sues for losses suffered from investments made in reliance on negligently prepared corporate financial statements.2. Negligent performance of professional services where perhaps a frustrated beneficiary sues the solicitor who negligently drafted an impugned will., 3. Relational economic loss brought by a plaintiff who suffers

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.478
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.001
Scholarly communication0.0010.001
Open science0.0030.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.019
GPT teacher head0.228
Teacher spread0.209 · 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
Published2011
Admission routes1
Has abstractyes

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