Perceptions of moose-human conflicts in an urban environment.
Bibliographic record
Abstract
Urban expansion produces obvious and deleterious ecological effects on wildlife habi- tat. Land development plans continue to be approved in Prince George, British Columbia, both within and on proximate land that is occupied by moose (Alces alces). We surveyed 100 residents of Prince George to determine how they perceive potential conflicts with moose and compared those perceptions with available local data. The majority (~75%) indicated that there were <50 moose-human encoun- ters within Prince George in any given year; however, 222 moose-related reports occurred from April 2007-March 2008. This discrepancy indicates that the public probably underestimates both the pres- ence of moose and moose-human conflicts in Prince George. We did not find that outdoor enthusiasts were more knowledgeable than others about managing moose-human conflicts, suggesting that broad public education and awareness programs are warranted. Understanding how to respond to moose and developing a Moose Aware program were two suggested strategies to reduce conflict. The vast major - ity of residents (92%) enjoy moose and want moose to remain part of the Prince George environment; only 9% were in favour of euthanasia or sharp-shooting to resolve conflicts. Because 40% indicated that the best option was leaving moose alone, managers will need to develop more effective strategies to minimize and manage moose-human conflicts.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".