Bear viewing in the K'tzim-a-deen inlet: Effects on grizzly bear behaviour and visitor perceptions of impact.
Bibliographic record
Abstract
Wildlife viewing has positive economic impacts for communities, but potentially negative impacts for wildlife. I researched boat-based, bear-viewing tourism in the K'tzim-a-deen Inlet by: 1) investigating grizzly bear behavioural reactions to boats, and 2) assessing visitor satisfaction and perceptions of impact. I observed a high degree of variation within and among bears in response to vessels. Paired t-tests and Kruskal-Wallis analyses revealed increases in vigilance and traveling for some individual bears while other bears showed no significant behavioural changes. Visitor satisfaction with bear viewing was high and attributable to bear related aspects of the tour. Visitors perceived mainly positive impacts of tourism related to increased knowledge and awareness, which would lead to support of bear conservation efforts. Based on data from bear behaviour and visitor surveys, I provide 13 recommendations for area management. Management plans should prioritize grizzly bear conservation and minimize potential habitat displacement events, while maintaining visitor satisfaction.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".