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Record W2108943797 · doi:10.12927/hcpol.2015.24209

Regulating Direct-to-Consumer Drug Information: A Case Study of Eli Lilly’s Canadian 40over40 Erectile Dysfunction Campaign

2015· article· en· W2108943797 on OpenAlexaffvenueabout
Jean‐Christophe Bélisle‐Pipon, Bryn Williams–Jones

Bibliographic record

VenueHealthcare policy · 2015
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicPharmaceutical industry and healthcare
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsDirect-to-consumer advertisingErectile dysfunctionPromotion (chess)BusinessPharmaceutical industryDrug industryAdvertisingMedicineMarketingPharmacologyBiotechnologyPolitical scienceLawSurgeryMedical prescription

Abstract

fetched live from OpenAlex

Like most jurisdictions, Canada prohibits direct-to-consumer advertising (DTCA) of prescribed drugs. However, direct-to-consumer information (DTCI) is permitted, allowing companies to inform the public about medical conditions. An analysis of Eli Lilly's 40over40 promotion campaign for erectile dysfunction (ED), which included a quiz on ED, shows that DTCI, like DTCA, can be an effective means of drug familiarization. The pharmaceutical industry is "playing by the rules" currently in effect in Canada. Regulators should thus seriously consider whether existing rules permitting DTCI actually meet stated objectives of protecting the public from marketing campaigns (i.e., DTCA) that may deliver misleading information.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.672
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
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 head0.413
GPT teacher head0.546
Teacher spread0.133 · 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 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

Citations10
Published2015
Admission routes3
Has abstractyes

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