Factors influencing public support for managing the mountain pine beetle epidemic
Bibliographic record
Abstract
The mountain pine beetle (MPB) epidemic is the largest recorded outbreak in British Columbia’s history currently covering almost 10 percent of British Columbia’s 9.2 million hectares of forest. The problems it poses are not merely ecological but also social and economic. An evaluation of the public’s perceptions of mountain pine beetle management alternatives provides decision-makers with information needed to reduce conflicts, identify communication priorities, and make balanced decisions concerning the use and recovery of affected areas. A survey was administered to 312 respondents, half in Prince George, a more forest-dependent community, and half in Kelowna, a less forest-dependent one. While this research found considerable public support for increased harvesting, it did not vary by location even though the residents of Prince George, the more forest-dependent community, were more concerned about the economic impact of the MPB than the residents of Kelowna. Concern for the economic impact of the MPB was not associated with support for harvesting. In contrast, the residents of Prince George reported greater knowledge, which was associated with support for harvesting. Finally, holding an ecological modernization viewpoint was not associated with location but it was associated with support for harvesting. Although respondents in the two study areas were concerned with the economic impact of the mountain pine beetle, the driver for supporting increased harvesting appeared to be a belief that human intervention can solve environmental problems. This research demonstrates the value of an examination of the social determinants of public support for strategies for managing natural disturbances in the policy making process.
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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 | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".