Perceptions of industry responsibility and tobacco control policy by US tobacco company executives in trial testimony
Bibliographic record
Abstract
OBJECTIVE: Trial testimony from the United States provides a unique opportunity to examine strategies of the American tobacco industry. This paper examines congruence between the arguments for tobacco control policy presented by representatives of the American tobacco industry at trial and the stages of responsibility associated with corporate social responsibility principles in other industries. DATA SOURCES: Trial testimony collected and coded by the Deposition and Trial Testimony Archive (DATTA). STUDY SELECTION: All available testimony was gathered from representative senior staff from major tobacco companies: Brown & Williamson, Philip Morris, RJ Reynolds, and Liggett. DATA EXTRACTION: Transcripts from each witness selected were collected and imported in text format into WinMax, a qualitative data program. The documents were searched for terms relating to tobacco control policies, and relevant terms were extracted. A hand search of the documents was also conducted by reading through the testimony. Inferred responsibility for various tobacco control policies (health information, second-hand smoking, youth smoking) was coded. DATA SYNTHESIS: The level of responsibility for tobacco control policy varied according to the maturity of the issue. For emerging issues, US tobacco company representatives expressed defensiveness while, for more mature issues, such as youth smoking, they showed increased willingness to deal with the issue. This response to social issues is consistent with corporate social responsibility strategies in other industries. CONCLUSION: While other industries use corporate social responsibility programmes to address social issues to protect their core business product, the fundamental social issue with tobacco is the product itself. As such, the corporate nature of tobacco companies is a structural obstacle to reducing harm caused by tobacco 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.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".