Wildfire risk mitigation and recreational property owners in Cypress Hills Interprovincial Park-Alberta
Bibliographic record
Abstract
Recreational property (cottage) owners represent a growing segment of population living at the wildland–urban interface. Land managers may find it particularly difficult to engage these landowners in wildfire management initiatives. This paper examines support for wildfire management, perceived wildfire risk and wildfire mitigation actions among cottage owners in Cypress Hills Interprovincial Park-Alberta. Data were collected from 165 cottage owners using a mail survey. Results showed that these owners had a high level of support for fuel reductions on the landscape and a high level of interest in participating in a cooperative wildfire mitigation program; they had taken action to reduce their risk. However, they seemed reluctant to do substantial tree pruning, or to install fire-resistant siding or screen eaves, decks and vents. Results found that perceived risk was not correlated with mitigation action. Awareness, perceived effectiveness of firefighters, days spent at the cottage and value of the cottage were correlated positively with mitigation action, whereas perceived efficacy, aesthetic effects and cost of mitigation were correlated negatively. These findings suggest that mitigation programs for cottage owners may be effective by providing public education on the efficacy of mitigation, lessening the effects of impediments such as cost, and alleviating concerns about aesthetics.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".