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Record W4408523441 · doi:10.1177/27551938251325801

Information About Canadian Patient Groups’ Conflicts of Interest and Industry Funding—Incomplete, Inconsistent, and Unreliable: A Cross-Sectional Study

2025· article· en· W4408523441 on OpenAlexaffabout
Joel Lexchin

Bibliographic record

VenueInternational Journal of Social Determinants of Health and Health Services · 2025
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicPharmaceutical industry and healthcare
Canadian institutionsYork UniversityUniversity of Toronto
Fundersnot available
KeywordsTransparency (behavior)LegislationPaymentAgency (philosophy)BusinessConflict of interestAccountingPharmaceutical industryHealth careIndependence (probability theory)Public relationsFinanceEconomicsMedicinePolitical scienceLawEconomic growth

Abstract

fetched live from OpenAlex

Patient groups play an important role in health care. At the same time, the majority of Canadian groups receive payments from pharmaceutical companies, which calls into question whether they speak for the best interests of their membership or the companies that fund them. Canada lacks any mandatory reporting by either patient groups or pharmaceutical companies regarding payments between groups and companies. There are three potential sources of information on the topic of payments: ( a ) declarations made by groups when they file submissions to the Canadian Agency for Drugs and Technologies in Health, an organization created and funded by Canada's federal, provincial and territorial governments, about whether the agency should recommend public funding for the new drug; ( b ) patient groups’ websites; and ( c ) voluntary disclosures by pharmaceutical companies on their websites. This study investigates the data available in all three sources and finds that they are incomplete and inconsistent, making any conclusions about patient groups’ conflicts of interest and funding unreliable. Although increased transparency is no guarantee of independence, it is an important and necessary first step. However, relying on voluntary disclosure is not sufficient. Legislation, such as the bill passed in the province of Ontario but never implemented, mandating disclosure by companies of payments that they have made is necessary.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.042
Threshold uncertainty score0.988

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.346
GPT teacher head0.562
Teacher spread0.216 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations1
Published2025
Admission routes2
Has abstractyes

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Same venueInternational Journal of Social Determinants of Health and Health ServicesSame topicPharmaceutical industry and healthcareFrench-language works237,207