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Record W3046030383 · doi:10.1080/23748834.2020.1778844

COVID-19 and climate change: an integrated perspective

2020· article· en· W3046030383 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCities & Health · 2020
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicCOVID-19 Pandemic Impacts
Canadian institutionsRoyal Roads UniversityUniversity of the Fraser Valley
Fundersnot available
KeywordsSustainabilityPreparednessPandemicCoronavirus disease 2019 (COVID-19)Vulnerability (computing)Climate changePerspective (graphical)Diversification (marketing strategy)Community resiliencePsychological resilienceResilience (materials science)Environmental planningCollective actionAdaptive capacityPolitical scienceOutbreakEnvironmental resource managementEconomic growthBusinessGeographyEconomicsEcologyPsychologyEngineeringInfectious disease (medical specialty)MedicineSocial psychologyComputer scienceComputer securityMarketing

Abstract

fetched live from OpenAlex

The COVID-19 outbreak has revealed multiple vulnerabilities in community systems. Effectively addressing these vulnerabilities and increasing local resilience requires thinking beyond solely pandemic responses and taking more holistic perspectives that integrate sustainability objectives. Pandemic preparedness and climate action in particular share similarities in terms of needs and approaches for community sustainability. This paper reflects on what the outbreak has illustrated regarding community vulnerability to crises, with a focus on local economy and production, economic diversification, and social connectivity. The paper argues for integrated approaches to community development that increase our capacity to respond to both public health and climate crises.

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.

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)0.001
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 score0.777
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.147
GPT teacher head0.342
Teacher spread0.195 · 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