Exploring the hidden connections between information channel use and pro-environmental behavior among recreational anglers of the shore-based shark fishery in Florida, United States
Bibliographic record
Abstract
Introduction Shore-based shark fishing in Florida is a relatively low-cost and easy-access fishery which attracts a wide variety of experienced and inexperienced anglers leading to concerns about proper handling methods of captured fish that are released either voluntarily or to comply with regulations. Proper handling methods can help reduce post-release mortality among sharks, many of which are threatened with extinction. Therefore, we considered proper handling methods as a pro-environmental behavior, which has been linked with the use of different information channels to increase conservation knowledge. Methods We used data from an online questionnaire to understand where anglers of this fishery obtain information about fishing skills with a particular focus on fish handling techniques and best practices for catch-and-release. Then we included their main information channels in a series of hierarchical regression models with perceived conservation knowledge and support for fishery management to explain pro-environmental behavior regarding shark conservation. Results We found that most anglers learned about shore-based shark fishing through interpersonal communications with friends and family, but typically use the internet to learn more about fishing skills. While information channel use was not significantly associated with pro-environmental behavior, it was significantly associated with support for fisheries management, which in turn was associated with pro-environmental behavior among respondents. Discussion These findings can inform public educational outreach efforts to spread awareness of proper handling techniques and reduce instances of post-release mortality in sharks.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".