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Record W2784085438 · doi:10.1136/jech-2017-210082

Public health guide to field developments linking ecosystems, environments and health in the Anthropocene

2018· article· en· W2784085438 on OpenAlexaff
Chris G. Buse, Jordan Sky Oestreicher, Neville Ellis, Rebecca Patrick, Ben Brisbois, Aaron Jenkins, Kaileah McKellar, Jonathan Kingsley, Maya Gislason, Lindsay P. Galway, R. A. McFarlane, Joanne Walker, Howard Frumkin, Margot W. Parkes

Bibliographic record

VenueJournal of Epidemiology & Community Health · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate Change and Health Impacts
Canadian institutionsLakehead UniversityPublic Health OntarioUniversity of TorontoSimon Fraser UniversityUniversity of Northern British Columbia
Fundersnot available
KeywordsPublic healthAnthropoceneSustainabilityTerminologyField (mathematics)SituatedEnvironmental planningPolitical scienceEnvironmental resource managementEnvironmental ethicsEngineering ethicsSociologyEcologyGeographyMedicineEngineeringComputer scienceEnvironmental scienceBiology

Abstract

fetched live from OpenAlex

The impacts of global environmental change have precipitated numerous approaches that connect the health of ecosystems, non-human organisms and humans. However, the proliferation of approaches can lead to confusion due to overlaps in terminology, ideas and foci. Recognising the need for clarity, this paper provides a guide to seven field developments in environmental public health research and practice: occupational and environmental health; political ecology of health; environmental justice; ecohealth; One Health; ecological public health; and planetary health. Field developments are defined in terms of their uniqueness from one another, are historically situated, and core texts or journals are highlighted. The paper ends by discussing some of the intersecting features across field developments, and considers opportunities created through such convergence. This field guide will be useful for those seeking to build a next generation of integrative research, policy, education and action that is equipped to respond to current health and sustainability challenges.

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)0.049
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.280
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0490.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.374
GPT teacher head0.470
Teacher spread0.096 · 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

Citations138
Published2018
Admission routes1
Has abstractyes

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