HUNTER AND TOURIST OUTFITTER PREFERENCES FOR REGULATING MOOSE HUNTING IN NORTHEASTERN ONTARIO
Bibliographic record
Abstract
It is important for managers to understand preferences of moose ( Alces alces ) hunters and other stakeholders regarding options for harvest management. We determined harvest preferences of resident moose hunters and tourist outfitters in 2013 in northeastern Ontario, Canada through surveys that provided 5 management options. We tested 2 hypotheses: 1) that moose hunters will support options that are least impactful to them, and 2) that tourist outfitters will support restrictive calf harvest regulations more than resident hunters. We found little support for the first hypothesis as resident hunters and tourist outfitters ranked the status quo as the second least and least preferable option, respectively. Resident hunters and tourist outfitters preferred shortened seasons for adult moose and less than a week long season for calves that would result in major departure from the status quo. We contend that this support arises because the hunters and outfitters are responding to the expectation of increased opportunities to hunt adult moose if they accept more restrictive regulations. Consistent with the second hypothesis, tourist outfitters preferred options focused on restricting calf hunting opportunities more than resident hunters because clientele of tourist outfitters generally have low demand for calf hunts. Resident hunters from areas where adult moose hunting opportunities were scarcer were surprisingly, less supportive than other hunters of change from an open to controlled hunt for calf moose. Individuals in both groups that responded by mail, versus online, had stronger support for the status quo.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".