Public health branding : applying marketing for social change
Bibliographic record
Abstract
PART ONE: THEORY AND CONCEPTUAL FOUNDATIONS 1. Public health branding: recognition, promise, and delivery of healthy lifestyles 2. What is a public health brand? 3. Evaluation of public health brands: design, measurement, and analysis 4. Addressing the competition: societal implications of commercial marketing PART TWO: PUBLIC HEALTH BRANDING CASE STUDIES 5. HELP: A European public health brand in the making? 6. Branding play for children: VERB It's What You Do 7. Case studies of youth tobacco prevention campaigns from the United States: truth and half-truths 8. High brand recognition in the context of an unsuccessful communication campaign: The National Youth Anti-Drug Media Campaign 9. Branding through cultural grounding: the keepin' it REAL curriculum 10. Branding down under: case studies from Australia PART THREE: PRACTICE AND APPLICATIONS OF PUBLIC HEALTH BRANDING 11. Public health brands in the developing world 12. Branding of international public health organizations: applying commercial marketing to global public health 13. The intersection between tailored health communication and branding for health promotion 14. Challenges and limitations of applying branding in social marketing 15. Future directions for public health branding
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.013 |
| Scholarly communication | 0.009 | 0.011 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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 source (direct Gemma or distilled Codex), 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".