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Record W6889007664 · doi:10.25316/ir-17875

Exploring homeowner wildfire mitigation adoption in British Columbia’s Cariboo Region

2023· other· en· W6889007664 on OpenAlexaboutno aff

Bibliographic record

VenueVIURRSpace (Vancouver Island University) · 2023
Typeother
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsnot available
Fundersnot available
KeywordsFocus groupAdaptation (eye)Work (physics)Risk managementClimate changeQualitative research

Abstract

fetched live from OpenAlex

British Columbia must adapt to a rise in wildfire disasters. Homeowner wildfire mitigation should be a part of this adaptation and is advocated by FireSmart. However, adoption remains low. This qualitative research project explored the adoption of wildfire mitigation activities by homeowners using field studies, interviews, and a focus group with participants from four communities in BC’s Cariboo Region. The research found that all participants were interested in wildfire mitigation. However, they varied in how they prepared their homes. Participants described being involved in three different wildfire mitigation processes. These processes were related, but had different motivations, considerations, and goals. Engagement with these processes over time resulted in reduced wildfire risks but could be impeded in several ways. The results indicate that supporting these different processes in different ways, and with consideration to how they are impeded, may lead to greater overall success with supporting community wildfire risk reduction.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.087
Threshold uncertainty score0.175

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.002
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.014
GPT teacher head0.174
Teacher spread0.160 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2023
Admission routes1
Has abstractyes

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Same venueVIURRSpace (Vancouver Island University)→Same topicFire effects on ecosystems→French-language works237,207→