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Record W4200578783 · doi:10.1093/heapro/daab120

Towards healthy One Planet cities and communities: planetary health promotion at the local level

2021· article· en· W4200578783 on OpenAlexaff
Trevor Hancock

Bibliographic record

VenueHealth Promotion International · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate Change and Health Impacts
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsHealth promotionSocial determinants of healthHealth policyGlobal healthHealth equityPublic healthEquity (law)Environmental healthBusinessEconomic growthHealth carePublic relationsPolitical scienceMedicineEconomicsNursing

Abstract

fetched live from OpenAlex

Health promotion has paid a lot of attention to the social determinants of health and to health equity but much less attention to the ecological determinants. Yet the most fundamental determinants of health are the natural systems that make the Earth liveable and are the source of our air, water, food, fuels and materials. Yet they are threatened by the very economic and social development that we have created to meet the social determinants of health. Moreover, the benefits and burdens of that development are inequitably distributed, resulting in both ecological and social injustice. In the past few years the new field of planetary health-'the health of human civilization and the state of the natural systems on which it depends'-has emerged, while WHO has confirmed that 'the source of human health [is] nature'. So arguably the most important task facing health promotion in the 21st century is to turn its attention to planetary health: health promotion workers must become planetary health promoters. Local health promotion in the 21st century needs to incorporate the concept of planetary health promotion and its application in the creation of healthy 'One Planet' communities and must become part of the emerging network of community organizations and individuals working to create sustainable, just and healthy communities.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.640
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0100.000

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 head0.216
GPT teacher head0.367
Teacher spread0.151 · 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

Citations19
Published2021
Admission routes1
Has abstractyes

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