MétaCan
Menu
Back to cohort
Record W183380630 · doi:10.1155/2004/561492

The Case of Dr George Gale V. the College of Physicians and Surgeons of Ontario: A Legal Analysis

2004· article· en· W183380630 on OpenAlexaffabout
Matthew Wilton

Bibliographic record

VenuePain Research and Management · 2004
Typearticle
Languageen
FieldHealth Professions
TopicMedical Malpractice and Liability Issues
Canadian institutionsGolder Associates (Canada)
Fundersnot available
KeywordsGeorge (robot)MedicinePsychologyMedical educationArtArt history

Abstract

fetched live from OpenAlex

On March 15, 2002, anaesthetist and pain practitioner, Dr George Gale, had his license to practice medicine in Ontario revoked by a decision of the Discipline Committee of the College of Physicians and Surgeons of Ontario (CPSO) (1,2). To that point, Dr Gale had practiced medicine as an anaesthetist in Ontario without incident. The CPSO Discipline Committee hearing had taken place over 22 days in 2001 and 2002. The focus of the CPSO prosecution against Dr Gale was his pain practice conducted at a well‐known pain clinic in Toronto, Ontario. By an Ontario Divisional Court decision dated October 10, 2003, the CPSO Discipline Committee decision was set aside on appeal (3). Most importantly, the Ontario Divisional Court held that the penalty of revocation levied against Dr Gale was unfair and based on several serious errors made by the Discipline Committee. A closer examination of the decisions of both the Discipline Committee and the Ontario Divisional Court will hopefully illustrate both the medical standards of practice issues for pain practitioners, and some of the perils created by the self governing activities of the CPSO. To put the Gale decision in proper context, it will be necessary for us to briefly examine the function of the CPSO and its Discipline Committee.

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)0.006
metaresearch head score (Gemma)0.017
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: Empirical · Consensus signal: none
Teacher disagreement score0.922
Threshold uncertainty score0.591

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.017
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.004
Science and technology studies0.0290.016
Scholarly communication0.0060.002
Open science0.0030.004
Research integrity0.0210.010
Insufficient payload (model declined to judge)0.0050.000

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 head0.073
GPT teacher head0.447
Teacher spread0.373 · 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
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
Published2004
Admission routes2
Has abstractyes

Explore more

Same venuePain Research and ManagementSame topicMedical Malpractice and Liability IssuesFrench-language works237,207