Psychological commitment of freshwater anglers and its relation to their preferences for stocking and other management actions
Bibliographic record
Abstract
Understanding stakeholder diversity can help natural resource managers tailor activities to achieve greater stakeholder satisfaction. Stakeholder diversity can be described by the concept of recreational specialization. Centrality-to-lifestyle, one subdimension of specialization that measures the psychological importance of a recreational activity to an angler, has been shown to explain many human dimensions and behaviors of recreational fishers and to correlate with preferences for management actions. We surveyed 9911 anglers in Florida, USA to examine how centrality-to-lifestyle relates to preferences for stocking and other management tools. We found that most anglers support stocking and that anglers of greater centrality-to-lifestyle had more positive views toward stocking than less central anglers. Participants, regardless of level of centrality-to-lifestyle, generally preferred stocking of one species, Florida largemouth bass ( Micropterus salmoides), and they preferred habitat management above stocking, with no relation to centrality. The results suggest stocking can improve the satisfaction of anglers of all commitment levels, but habitat improvement could do so even more. Managers might consider prioritizing habitat management over stocking in systems where natural recruitment is ample to increase overall angler satisfaction, and where the anglers will, on average, support such actions independent of the degree of centrality.
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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 | 0.004 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".