Catching sharks: recreational saltwater angler behaviours and attitudes regarding shark encounters and conservation
Bibliographic record
Abstract
Abstract With the increasing popularity of recreational angling around the world, there is a need to better understand the potential contribution of recreational fishing to reported shark population declines. However, the nature and perception of shark encounters – a fundamental precursor to future research, management and conservation measures aimed to increase shark survival – is not well documented in recreational fisheries. Five hundred and ninety recreational saltwater anglers responded to the survey and reported their experiences targeting or incidentally catching sharks, as well as their attitudes toward sharks, shark fishing techniques, and shark conservation and management. The survey found sharks were caught regularly, with 57% of respondents commonly targeting sharks and 93% of respondents having caught a shark at least once. Eighty‐eight percent of the respondents released the last shark that they caught and most respondents often or always practised catch‐and‐release when catching sharks. The survey revealed that avid anglers have positive attitudes toward sharks and shark conservation and have a desire to handle and release sharks in ways that will increase their likelihood of survival. However, the survey also revealed that there are a variety of situational factors (e.g. target fish, fishing platform) that influence the choices that anglers make while fishing, which may influence adherence to catch‐and‐release methods. Based on their positive attitudes toward sharks, recreational anglers may be strong allies for the development, dissemination, and adoption of species and situational‐specific best practice catch‐and‐release guidelines for this group of fishes within the wider recreational saltwater angling community. Copyright © 2015 John Wiley & Sons, Ltd.
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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 | 0.002 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".