Public opinion toward a misunderstood predator: what do people really know about wolverine and can educational programs promote its conservation?
Bibliographic record
Abstract
Among the least known of Canada’s large predators, the wolverine’s status as threatened, or endangered throughout its eastern range, makes it a candidate for conservation programs. A lack of public support, however, can dramatically reduce the chances of such programs being successful. To assess the current state of support for wolverine conservation, knowledge and perceptions toward this species among the public, adults visiting the St. Félicien zoo were surveyed. Knowledge among participants was generally low and misconceptions were abundant, even among repeat visitors to the zoo. Attitudes, however, were mostly positive. To assess how exposure can influence perceptions, children were surveyed who had or had not attended a 5-day camp at the zoo. Both groups demonstrated similar levels of knowledge about wolverine. However, children who had attended the camp demonstrated a greater aesthetic appreciation and fewer negative associations with wolverines. These results suggest that while the wolverine is not a well-known species, people’s perceptions toward this species are not necessarily negative. Additionally, information provided by zoos, in a variety of forms, may not always be acquired by visitors, but may still have a positive influence on how the public perceives cryptic misunderstood species such as the wolverine.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".