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Record W2547241128 · doi:10.1108/ijhg-08-2016-0041

Governance for health in the Anthropocene

2016· article· en· W2547241128 on OpenAlexaff
Trevor Hancock, Anthony Capon, U. Dietrich, Rebecca Patrick

Bibliographic record

VenueInternational Journal of Health Governance · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate Change and Health Impacts
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsAnthropoceneCorporate governanceEarth system sciencePolitical scienceEnvironmental ethicsOriginalityEnvironmental resource managementEnvironmental planningBusinessGeographyEcologyEconomicsLawBiology

Abstract

fetched live from OpenAlex

Purpose The purpose of this paper is to explore the pressing issues facing health and health systems governance in the Anthropocene – a new geological time period that marks the age of colossal and rapid human impacts on Earth’s systems. Design/methodology/approach The viewpoint illustrates the extent of various human induced global ecological changes such as climate change and biodiversity loss and explores the social forces behind the new epoch. It draws together current scientific evidence and expert opinion on the Anthropocene’s health and health system impacts and warns that many these are yet unknown and likely to interact and compound each other. Findings Despite this uncertainty, health systems have four essential roles in the Anthropocene from adapting operations and preparing for future challenges to reducing their own contribution to global ecological changes and an advocacy role for social and economic changes for a healthier and more sustainable future. Practical implications To live up to this challenge, health services will need to expand from a focus on health governance to one on governance for health with a purpose of achieving equitable and sustainable human development. Originality/value As cities and local governments work to create more healthy, just and sustainable communities in the years ahead, health systems need to join with them as partners in that process, both as advocates and supporters and – through their own action within the health sector – as leading proponents and models of good practice.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.877
Threshold uncertainty score0.372

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
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 head0.052
GPT teacher head0.390
Teacher spread0.337 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations21
Published2016
Admission routes1
Has abstractyes

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