Social marketing campaigns aimed at preventing drunk driving
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.
Bibliographic record
Abstract
Abstract Purpose – The purpose of this paper is to examine the role of social marketing programs in preventing drunk driving, and how protection motivation theory (PMT) can be used to create effective anti drunk driving communications. Design/methodology/approach – Communication and program materials aimed at reducing drunk driving were identified and gathered from English‐language websites from the USA, Canada, UK, Australia, and New Zealand, and a qualitative review was conducted. Findings – The review provides a description of the key themes and messages being used in anti drunk driving campaigns, as well as target population, campaign components, and sources of funding. A key facet of this review is the examination of the use of PMT in social marketing campaigns designed to prevent drunk driving. Originality/value – The review presents social marketing campaigns aimed at preventing drunk driving in English‐speaking countries, and shows that PMT can be successfully used in this context. The paper provides a guide for future initiatives, as well as recommendations for social marketing practitioners.
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 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 | 0.005 | 0.001 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.014 | 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 it