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Record W2146235412 · doi:10.1136/jme.2003.005181

Better governance in academic health sciences centres: moving beyond the Olivieri/Apotex Affair in Toronto

2004· article· en· W2146235412 on OpenAlexaffabout
Lorraine E. Ferris, Peter Singer, C. David Naylor

Bibliographic record

VenueJournal of Medical Ethics · 2004
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicPharmaceutical industry and healthcare
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCorporate governancePublic relationsSociologyPolitical scienceManagementEconomics

Abstract

fetched live from OpenAlex

The Toronto experience suggests that there may be several general lessons for academic health sciences complexes to learn from the Olivieri/Apotex affair (OAA) regarding the ethics, independence, and integrity of clinical research sponsored by for profit enterprises. From a local perspective, the OAA occurred when there already was a focus on the complex and changing relationships among the University of Toronto, its medical school, the fully affiliated teaching hospitals, and off campus faculty because of intertwined interests and responsibilities. The OAA became a catalyst that accelerated various systemic reforms, particularly concerning academic/industry relations. In this article, the evolving governance framework for the Toronto academic health sciences complex is reviewed and these policy and process reforms discussed. These reforms have created collaborative activity among research ethics boards and contract research offices of the partner institutions, and allowed the joint university/hospital ethics centre to play a role in governance and policy, while respecting the missions and mandates of the involved institutions. Although few of the policies are dramatically innovative, what is arguably novel is the elaboration of an overarching governance framework that aims to move ethics to a central focus in the academic complex. Time alone will tell how sustainable and effective these changes are.

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)0.025
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity, Insufficient payload (model declined to judge)
Consensus categoriesResearch integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.727
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0250.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0020.023
Insufficient payload (model declined to judge)0.0010.000

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 head0.426
GPT teacher head0.611
Teacher spread0.185 · 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; both teacher heads agree on what is shown here.

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

Citations11
Published2004
Admission routes2
Has abstractyes

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