MétaCan
Menu
Back to cohort
Record W628398100

Public health branding : applying marketing for social change

2008· book· en· W628398100 on OpenAlexaff
James Hersey, Jonathan L. Blitstein, W. Doug Evans

Bibliographic record

VenueOxford University Press eBooks · 2008
Typebook
Languageen
FieldBusiness, Management and Accounting
TopicGlobal Public Health Policies and Epidemiology
Canadian institutionsWorkplace Health, Safety and Compensation Commission
Fundersnot available
KeywordsPublic healthHealth promotionCorporate brandingPublic relationsSocial marketingContext (archaeology)Health educationInternational healthHealth policyPolitical scienceHealth communicationBusinessAdvertisingBrand equityMarketingMedicineGeography
DOInot available

Abstract

fetched live from OpenAlex

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

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.430
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.201
GPT teacher head0.286
Teacher spread0.085 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations74
Published2008
Admission routes1
Has abstractyes

Explore more

Same venueOxford University Press eBooksSame topicGlobal Public Health Policies and EpidemiologyFrench-language works237,207