MétaCan
Menu
Back to cohort
Record W4402501891 · doi:10.1080/14693062.2024.2395920

Bolstering community resilience through health-focused climate change adaptation: moving from talk to action in Western Canadian communities

2024· article· en· W4402501891 on OpenAlexaffabout
Desiree Rose, S. Jeff Birchall

Bibliographic record

VenueClimate Policy · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate Change and Health Impacts
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsClimate changeResilience (materials science)Community resilienceClimate change adaptationAction (physics)Psychological resilienceAdaptation (eye)Environmental resource managementPolitical scienceCollective actionEnvironmental planningBusinessGeographyPsychologyEconomicsSocial psychologyPoliticsEcology

Abstract

fetched live from OpenAlex

The impacts of climate change have been recognized as a global health emergency. Worsening climate stressors are resulting in injury, illness and death. As this threat to health grows, so does the need to adapt. Climate change adaptation has been noted to reduce the risk of disease transmission, chronic illness exacerbation, physical trauma, and the mental health impacts associated with climate change. Cities across Western Canada have initiated the process of implementing health-focused climate change adaptation; however, progress has been slow, leaving communities vulnerable to health threats. Exploring five case study communities in Western Canada, this research sheds light on factors that enable and constrain progress on health-focused climate change adaptation. Research objectives are addressed through analysis of 16 key actor interviews (with experts in public health, planning, local governance, and other related fields), and a scan of relevant strategic planning documents. Results indicate that political will, expertise, and awareness has resulted in the development of health-focused climate change adaptation policy/ plans. However, implementation of these plans lags in practice. This lag stems from a lack of implementation detail in climate change adaptation plans, limited understanding of the impact of climate change on health, and jurisdictional confusion.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.770
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.245
GPT teacher head0.400
Teacher spread0.155 · 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

Citations4
Published2024
Admission routes2
Has abstractyes

Explore more

Same venueClimate PolicySame topicClimate Change and Health ImpactsFrench-language works237,207