Criteria for evaluating tobacco control research funding programs and their application to models that include financial support from the tobacco industry
Bibliographic record
Abstract
Much has been discussed and written about the purposes, outcomes and ethics related to tobacco industry funding of research.1–9 The issue is controversial because of tobacco industry funding mechanisms that have been used by the tobacco industry to gain credibility and to advance the industry’s interests, which may come at the expense of public health;6 at the same time others have argued that, given the scarcity of funding from other sources, tobacco industry support may be defensible, at least under some circumstances.10 These concerns raise the question of whether there could be a model of tobacco company funding that would be acceptable to the tobacco control research community. This paper presents a set of criteria for evaluating funding models and applies them to four diverse models. While tobacco consumption and prevalence rates have declined in many developed countries over the past 40 years, the projections are that worldwide tobacco-related deaths will increase in the 21st century.11 Despite the disproportionate toll tobacco use takes, there remains only a modest investment in research to better understand tobacco products, tobacco product marketing, addiction, treatment and consumer behaviour. For example, in the USA, where tobacco causes almost 30% of all cancer deaths, only 2.3% of the National Cancer Institute’s 2003 budget was spent on tobacco-related research funding.12 This level of research investment is inadequate relative to the magnitude of the damage caused by tobacco use.13 14 At the same time, the tobacco industry has funded tobacco and health related research at universities. In the current context of limited funding, individuals and institutions may welcome additional sources of support. However the evidence is now clear that the tobacco industry participated in a long-standing conspiracy to defraud the public regarding the health risks of smoking. In 2006, the …
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.485 | 0.649 |
| Meta-epidemiology (narrow) | 0.006 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.011 |
| Bibliometrics | 0.036 | 0.031 |
| Science and technology studies | 0.007 | 0.011 |
| Scholarly communication | 0.021 | 0.016 |
| Open science | 0.011 | 0.015 |
| Research integrity | 0.011 | 0.007 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".