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Record W2970765139 · doi:10.1111/bioe.12619

Conflicts of interest in e‐cigarette research: A public good and public interest perspective

2019· article· en· W2970765139 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBioethics · 2019
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicPharmaceutical industry and healthcare
Canadian institutionsDalhousie University
Fundersnot available
KeywordsPublic interestPerspective (graphical)Conflict of interestGeneral interestPublic relationsPolitical scienceSociologyPsychologyEpistemologyLawComputer sciencePhilosophy

Abstract

fetched live from OpenAlex

The tobacco industry's involvement in the electronic cigarette research that informs public health policy is controversial. On the one hand, some are concerned that their involvement presents conflicts of interest that bias research outputs and invalidate the policies that use them. On the other hand, some have argued that the tobacco industry may support valid research and contribute to the goals of public health, for instance, if the interests of the e-cigarette industry could be part of a tobacco smoking cessation policy. We approach this debate from the ethical perspective of the public interest and the public good, considering how legitimate researchers can square their expert opinion with validating tobacco industry-funded research, given the perfidy of the tobacco industry and paucity of robust, conclusive evidence on the public health impacts of liberalizing e-cigarette use.

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.

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)0.005
metaresearch head score (Gemma)0.002
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.808
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.007
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 head0.922
GPT teacher head0.645
Teacher spread0.276 · 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