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Record W3149696435

Personal liability, vicarious liability, non-delegable duties and protecting vulnerable people

2016· article· en· W3149696435 on OpenAlexaboutno aff
Todd Smd

Bibliographic record

VenueUniversity of Canterbury Research Repository (University of Canterbury) · 2016
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicInsurance and Financial Risk Management
Canadian institutionsnot available
Fundersnot available
KeywordsVicarious liabilityLiabilityBusinessStrict liabilityLiability insuranceTortLawActuarial sciencePolitical scienceFinance
DOInot available

Abstract

fetched live from OpenAlex

A policy concern underlying the imposition on defendants of a liability in tort which influences the courts, sometimes expressly and sometimes implicitly, is a need to protect and assist persons who may be seen to have been in a vulnerable position at the time they suffered injury or harm. Leading decisions concerning the imposition on defendants of a duty of care in negligence, of vicarious liability in respect of the deliberate or negligent actions of another person, and of a duty which cannot be delegated to another person, all have given expression to, and support for, a concept of plaintiff vulnerability. Indeed, recent decisions in the United Kingdom, Canada and Australia concerning the abuse of children by persons in a position of power and authority and which significantly extend the reach of vicarious liability provide particularly apt examples. The aim of this article is to show how the three different kinds of claim can provide a remedy for vulnerable people and to identify any links and overlaps between them. Certainly it is apparent that the idea of vulnerability can provide helpful guidance for a court faced with a novel or borderline question of liability.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.310
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.000
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 head0.023
GPT teacher head0.210
Teacher spread0.186 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2016
Admission routes1
Has abstractyes

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