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Record W3035623376 · doi:10.1177/0020731420932109

Drug Promotion in India Since 2000: Problems Remain

2020· article· en· W3035623376 on OpenAlexaff
Joel Lexchin

Bibliographic record

VenueInternational Journal of Health Services · 2020
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicPharmaceutical industry and healthcare
Canadian institutionsYork UniversityUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsPromotion (chess)HarmGovernment (linguistics)Health promotionValue (mathematics)Pharmaceutical industryPublic relationsMedicineBusinessMarketingNursingPolitical sciencePublic healthPharmacologyPolitics

Abstract

fetched live from OpenAlex

Pharmaceutical companies engage heavily in promoting their products worldwide, and India is no exception. This article begins with an analysis of the therapeutic value of medications on the Indian market because, by definition, if a drug has no therapeutic value or has a negative benefit-to-harm ratio, then any promotion of that drug is inappropriate. It then examines 2 Indian case studies: drug promotion in Mumbai and the misuse of the World Health Organization logo in promotion. Next it describes specific types of promotion: advertisements in medical journals, brochures, and pamphlets; the actions of sales representatives; and the content of continuing medical education courses and medical conferences. The next sections examine medical students' and trainees' exposure to promotion and their attitudes about promotion; the attitudes of doctors about their interactions with the pharmaceutical industry; and whether promotion has an influence on prescribing. The article concludes with a critique of the existing industry, professional, and government regulatory regimes in India.

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)0.007
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.061
Threshold uncertainty score0.121

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.007
Science and technology studies0.0040.007
Scholarly communication0.0080.005
Open science0.0020.003
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0070.002

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 head0.304
GPT teacher head0.539
Teacher spread0.235 · 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 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

Citations9
Published2020
Admission routes1
Has abstractyes

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