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Record W2092891424 · doi:10.2190/hs.38.3.h

Clinical Trials in Canada: Whose Interests are Paramount?

2008· article· en· W2092891424 on OpenAlexaffabout
Joel Lexchin

Bibliographic record

VenueInternational Journal of Health Services · 2008
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicPharmaceutical industry and healthcare
Canadian institutionsYork University
Fundersnot available
KeywordsClinical trialHarmonizationPharmaceutical industryPublic relationsPublic healthMedicineDrug trialBusinessPolitical scienceNursingPharmacology

Abstract

fetched live from OpenAlex

More than 80 percent of clinical drug trials in Canada are funded by the pharmaceutical industry. This article evaluates the overall state of clinical trials in Canada and looks at the interplay between public and private interests. Health Canada has adopted standards developed by the International Conference on Harmonization, a body that is heavily influenced by industry. Commercial interests are increasingly involved in recruiting patients into clinical trials and in running these trials. It is in industry's interests to conduct drug tests on people for which it is easiest to see benefits. These interests are not fundamentally challenged by Health Canada's policy of issuing nonmandatory guidelines on who should and should not be included in clinical trials. The outcome of clinical trials is heavily influenced by commercial sponsorship, with the result that trials may favor corporate interests rather than the interests of the public. How Health Canada deals with that possibility is not known, because of its strict policy of treating clinical trial data as private property. If clinical trials are to serve the purpose for which they are designed, developing reliable and objective information about new drugs, then commercial interests cannot be allowed to take precedence over health interests.

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)0.012
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.296
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
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 head0.738
GPT teacher head0.673
Teacher spread0.065 · 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.

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

Citations7
Published2008
Admission routes2
Has abstractyes

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