Risk, knowledge, and trust in managing forest insect disturbance
Bibliographic record
Abstract
Understanding perceptions of risks, awareness, and trust in management agencies is critical to effective management of large-scale forest insect disturbance. In this study, we examined regional variation in public perceptions of risk, compared public and land managers’ perceptions, and examined knowledge and trust as factors in shaping public perceptions of a mountain pine beetle (MPB) ( Dendroctonus ponderosae Hopkins) infestation. Survey data were collected from residents (n = 1303) in three regions of Alberta and from land managers (n = 43) responsible for MPB management. Results showed that residents had moderate or great concern for MBP risks, they were not well informed about MPB, and they showed slight trust in the provincial government and forest industry to manage the beetle. There was regional variation in perceptions of risks, knowledge, and trust. Land managers were less concerned about nontimber effects and had higher trust than the public. A positive correlation between trust and risk perceptions appears to contradict the risk literature. This relationship may be influenced by an intervening effect of knowledge. These results call for more attention to the content of risk messaging and the effects of trust and knowledge on the general public who take up these messages.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".