MétaCan
Menu
Back to cohort
Record W4387705423 · doi:10.1177/10860266231201993

Does Wildfire Exposure Influence Corporate Disaster Preparedness? A Study of Natural Resources Extraction Firms in Canada

2023· article· en· W4387705423 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

VenueOrganization & Environment · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsCanadian Forest ServiceNatural Resources CanadaMcMaster University
Fundersnot available
KeywordsPreparednessClosenessPerceptionEnvironmental resource managementBusinessRisk perceptionNatural disasterEmergency managementNatural resourceEnvironmental planningPsychologyGeographyEnvironmental sciencePolitical science

Abstract

fetched live from OpenAlex

Managers must make critical disaster preparation decisions to protect firm assets from the threat of wildfire activity. Prior literature stresses the importance of past disaster experience as a key driver of disaster preparation. The article finds that, while experience with disasters is a critical condition, it is insufficient to explain disaster preparation activities by firms. Managerial perceptions including belief in anthropogenic climate change and the perception of increasing wildfires can substitute for direct negative wildfire experience. The article builds configural theory to explain how the psychological “closeness” of wildfire hazards can influence managerial decisions to prepare for disasters in the presence of key organizational characteristics. This study adopts a qualitative comparative analytical approach, drawing on manager surveys and biophysical wildfire data from 20 Canadian mining and resource extraction sites. The article also contrasts manager perceptions of wildfire risk with those of experts and captures a gap in risk perception.

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 score0.239
Threshold uncertainty score0.615

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.004
GPT teacher head0.178
Teacher spread0.173 · 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