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Record W4385368360 · doi:10.3390/atmos14081204

Wildfire Smoke and Protective Actions in Canadian Indigenous Communities

2023· article· en· W4385368360 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueAtmosphere · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsIndigenousSmokeThreatened speciesThematic analysisPopulationTraditional knowledgeNarrativeGeographyEnvironmental planningEnvironmental resource managementEnvironmental healthEnvironmental scienceQualitative researchEcologySociologyMedicineHabitatSocial scienceMeteorology

Abstract

fetched live from OpenAlex

In Canada, Indigenous populations are disproportionately threatened by wildfire smoke and the associated adverse health impacts. This paper presents the results of a narrative review of 51 academic and related resources which explored protective action decision making during wildfire smoke events within Indigenous communities in Canada. A search of scholarly articles and other relevant sources yielded resources which were subject to thematic analysis and described in order to present a narrative review of current knowledge and gaps in research. A small and growing literature provides insights into protective actions taken by the general population during wildfire smoke events, but very little is known about protective actions taken by Indigenous peoples in Canada during wildfire smoke events. This lack of understanding hinders the capacity of decision makers to improve emergency management and minimize community health impacts of wildfire smoke.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.741

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.017
GPT teacher head0.232
Teacher spread0.215 · 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