Generating news media interest in tobacco control; challenges in an advanced policy environment
Bibliographic record
Abstract
OBJECTIVE: To determine the efficacy of using media releases for tobacco control advocacy in Australia's advanced policy environment. METHODS: Between February and August 2010, news releases that summarised either newly published but unpublicized research findings, or local developments in tobacco control, were sent to NSW media outlets. Reports arising from the releases were tracked using commercial services Media Monitors and Factiva, as well as Google and Google News. Other tobacco control related news items during the same period were also tracked and recorded. RESULTS: Twenty-one news releases generated 93 news items across all news media, with a quarter of these related to a story of porcine haemoglobin in cigarette filters. By comparison, 'live' policy issues (especially plain packaging and a significant tobacco tax increase) covered in this period attracted 1,033 news stories in the Australian media. Press releases describing recently published, but underpublicized research were issued in weeks where no major competing tobacco control news occurred. Results of this project indicate that in environments with advanced tobacco policy, media opportunities related to tobacco control advocacy are limited, as many objectives have been achieved. CONCLUSION: The media can still play a key advocacy role in such environments, and advocates need to be particularly vigilant for opportunities that do arise. The paper also highlights the increasingly important role of internet-based media, including opportunities presented by social media for tobacco control.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 | 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".