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Record W2158142575 · doi:10.1093/heapro/daq028

Evaluating the implementation of the WHO Healthy Cities Programme across Germany (1999-2002)

2010· article· en· W2158142575 on OpenAlexaboutno aff
K. D. Plumer, Lynne Kennedy, Alf Trojan

Bibliographic record

VenueHealth Promotion International · 2010
Typearticle
Languageen
FieldHealth Professions
TopicSchool Health and Nursing Education
Canadian institutionsnot available
FundersWageningen University and ResearchBundeszentrale für gesundheitliche Aufklärung
KeywordsCharterGermanDocumentationPromotion (chess)Political scienceHealth promotionStrengths and weaknessesWork (physics)Public administrationPublic healthPoliticsPublic relationsMedicineEconomic growthPsychologyNursingGeographyEngineering

Abstract

fetched live from OpenAlex

The WHO Healthy Cities Project (1988) is a well-known example of the setting-based approach to health promotion. Developed as a framework for translating the key principles of the Ottawa Charter for Health Promotion (1986) into practice, it is best characterized as a process for successfully encouraging healthy public policy. In 2001, the German Healthy Cities Network (HCN) commissioned a survey of the 52 local Healthy Cities programme Coordinators (HCC) to monitor progress and identify strengths and weaknesses associated with its implementation. Most (90%; 47/52) HCC participated in the survey. Several positive aspects of the Health Cities Programmes (HCP) in Germany were identified: during the first 5 years, it expanded rapidly; project coordinators felt highly engaged, despite limited resources; a combination of traditional and innovative approaches was adopted and applauded; and almost 75% of HCC felt that their efforts had been beneficial. Nonetheless, the following shortcomings were identified: increased resources required; greater clarification of concepts and strategies at the local level; stronger commitment to the Nine-Point Programme of Action; greater integration within the national HCN and the local political administrative system (PAS); better programme documentation and evaluation. In conclusion, the HCN in Germany has expanded and developed since its inception 20 years ago. German HCP will only improve if professionalism and quality of local work are improved, particularly in terms of strengthening their influence on the local PAS and on public policies.

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)0.005
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.443
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.199
GPT teacher head0.595
Teacher spread0.396 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations27
Published2010
Admission routes1
Has abstractyes

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