Salient values, social trust, and attitudes toward wolf management in south-western Alberta, Canada
Bibliographic record
Abstract
SUMMARY Shared values, public trust in an agency, and attitudes can influence support for successful conservation initiatives. To understand these relationships, this paper examines the role of social trust as a partial mediator between salient values similarity and attitudes toward wolves in south-western Alberta, Canada. Rural residents in this area face increasing wolf depredation on livestock. Data were obtained from a mail questionnaire (n= 566 respondents, response rate = 70%) sent to rural residents in three municipal districts in south-western Alberta. Attitudes were predicted to directly influence behavioural intention to support or oppose wolf management. Most respondents held slightly similar values as the management agency and minimally trusted the agency to effectively manage wolves. As predicted, social trust in the agency served as a partial mediator between salient value similarity and attitudes toward wolves. Salient value similarity was also a strong predictor of attitudes toward wolves. Attitudes toward wolves predicted behavioural support. Thus, social trust of the management agency can influence attitudes and management preferences concerning a species. When dealing with human-wildlife conflict, social trust should be examined to understand the context of the problem.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".