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Record W2755298929 · doi:10.47339/ephj.2017.76

Environmental health officers and climate change adaptation in British Columbia

2017· article· en· W2755298929 on OpenAlexfundvenueaboutno aff
Laura McKelvey, Environmental Health BCIT School of Health Sciences, Helen Heacock

Bibliographic record

VenueBCIT Environmental Public Health Journal · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate Change and Health Impacts
Canadian institutionsnot available
FundersBritish Columbia Institute of Technology
KeywordsClimate changeDescriptive statisticsPublic healthAdaptation (eye)PerceptionDemographicsGeographyEnvironmental resource managementEnvironmental healthSocioeconomicsPsychologyMedicineEnvironmental scienceSociologyDemographyEcologyStatistics

Abstract

fetched live from OpenAlex


 Background: The average annual temperatures in British Columbia have been steadily increasing in recent history and are expected to continue to rise. Climate change impacts have a significant effect on public health, and adaptation to these changes is necessary. Environmental health officers (EHOs) are in a position to deliver climate change adaptation programs in public health. The purpose of this study was to assess EHO perception of climate change adaption and identify knowledge or policy gaps. Methods: A self-administered online survey created used Google Forms was distributed through e-mail and social media to EHOs in BC. The survey asked for demographics information, beliefs about climate change, adaption, and public health. Chi-square tests and descriptive statistics were used to analyze results. Results: There was a significant association found between working in a mixed urban and rural environment and the incorporation of climate change adaptation into practice and the belief that climate change has impacted public health in BC. No association was found between years of experience and incorporation of adaptation. Conclusion: While EHOs generally recognize the public health impacts of climate change, there are many barriers preventing EHO involvement in climate change adaptation.

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, Scholarly communication, 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 score0.428
Threshold uncertainty score1.000

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 studies0.0030.000
Scholarly communication0.0010.002
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.096
GPT teacher head0.304
Teacher spread0.208 · 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

Citations1
Published2017
Admission routes3
Has abstractyes

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