MétaCan
Menu
Back to cohort
Record W2253747404 · doi:10.5040/9781472565198.ch-007

A Common Law Prescription for a Medical Malaise

2014· book-chapter· en· W2253747404 on OpenAlexaboutno aff

Bibliographic record

VenueHart Publishing eBooks · 2014
Typebook-chapter
Languageen
FieldSocial Sciences
TopicLegal principles and applications
Canadian institutionsnot available
Fundersnot available
KeywordsMalaiseMedical prescriptionLawMedicinePolitical scienceInternal medicinePharmacology

Abstract

fetched live from OpenAlex

The Medical Methods Exception (MME) has always seemed remarkable. It presently excludes technologies applied on or in the body from patentability, claiming to protect medical practitioners treating patients from liability for patent infringement. The exception’s existence seems to argue that the medical profession’s work is significant enough to society to warrant special rules in patent law. In so doing, the MME contradicts the technology-neutral, morally agnostic stance of patent law which leaves the regulation of polycentric disputes to other fora. More remarkable, however, is how the MME became an integral part of patent law doctrine and now the European Patent Convention (EPC), and what that process tells us about the common law. Its evolution demonstrates that the common law is not monolithic and self-contained, but relies on mixed legal and professional communities of reception to shape its content. These communities may transcend national boundaries. As a result, informal common law principles may reveal themselves to be better rooted than the seemingly clearer and more certain statutory sources of law, which thus become secondary. This chapter considers the origins of the common law rule followed by the nature and international dimensions of the legal and medical community that received and practised the rule, in particular of Commonwealth courts and Canadian physicians. I will illustrate through the history of the MME the hybrid nature of the common law as part rule and part custom, inaccurately modeled by either legal positivism or as merely the reception of customary norms.

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)0.018
metaresearch head score (Gemma)0.031
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.018
Threshold uncertainty score0.095

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.031
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0090.086
Scholarly communication0.0100.014
Open science0.0020.007
Research integrity0.0170.025
Insufficient payload (model declined to judge)0.0080.003

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 head0.043
GPT teacher head0.302
Teacher spread0.259 · 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 designTheoretical or conceptual
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

Citations12
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueHart Publishing eBooksSame topicLegal principles and applicationsFrench-language works237,207