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Record W4417383891 · doi:10.5040/9781509937820

Medical Negligence and the Duty to Advise

2025· book· W4417383891 on OpenAlexaboutno aff
Kumaralingam Amirthalingam

Bibliographic record

VenueHart Publishing eBooks · 2025
Typebook
Language
FieldSocial Sciences
TopicLegal principles and applications
Canadian institutionsnot available
Fundersnot available
KeywordsTortAutonomyDutyDoctrineArgument (complex analysis)Agency (philosophy)DamagesSupreme courtMedical malpracticeMedical law

Abstract

fetched live from OpenAlex

This book argues that patient autonomy and medical negligence make for strange bedfellows. The emphasis on autonomy has distorted orthodox negligence principles, contributing to uncertainty and angst amongst healthcare professionals while eroding trust in the doctor-patient relationship. This work takes the current discourse beyond autonomy – which focuses on therightsof the patient, to agency and shared decision-making – which focus on therelationshipbetween doctor and patient. The core argument is built on a review of the theoretical foundations of negligence and the philosophical conceptions of autonomy. Provocatively, this work argues against a rights-based approach to negligence – which can be confrontational – in favour of a human obligations approach, which is collaborative and thus well suited to the doctor-patient relationship. Drawing on the theoretical analysis, the book identifies doctrinal anomalies in the duty of care, standard of care, causation, and damage. It critically analyses landmark UK Supreme Court cases, includingChester v Afshar,Montgomery v Lanarkshire Health Board, andMcCulloch v Forth Valley Health Board, arguing that the law is increasingly detached from the realities of medical practice and reasonable expectations of patients. Primarily based on UK law, the work also discusses Australian, Canadian, and Singaporean law. The book is aimed at the medical and legal fraternities as well as students and scholars of tort law. Doctors and lawyers will gain fresh insights into medical negligence; scholars will find an alternative perspective to orthodoxy with rich material to rethink theory and doctrine in negligence.

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)0.002
metaresearch head score (Gemma)0.008
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: Other · Consensus signal: Other
Teacher disagreement score0.011
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0040.019
Scholarly communication0.0040.005
Open science0.0010.003
Research integrity0.0090.007
Insufficient payload (model declined to judge)0.0070.001

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 head0.021
GPT teacher head0.297
Teacher spread0.276 · 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
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
Published2025
Admission routes1
Has abstractyes

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