Recommendations for the future of recreational fisheries to prepare the social‐ecological system to cope with change
Bibliographic record
Abstract
Abstract This paper presents conclusions and recommendations that emerged from the 7th World Recreational Fishing Conference ( WRFC ) held in Campinas, Brazil in September 2014. Based on the recognition of the immense social and economic importance of recreational fisheries coupled with weaknesses in robust information about these fisheries in many areas of the world, particularly in many economies in transition, it is recommended to increase effort to build effective governance arrangements and improve monitoring and assessment frameworks in data‐poor situations. Moreover, there is a need to increase interdisciplinary studies that will foster a systematic understanding of recreational fisheries as complex adaptive social‐ecological systems. To promote sustainable recreational fisheries on a global scale, it is recommended the detailed suggestions for governance and management outlined in the United Nations Food and Agricultural Organization Technical Guidelines for Responsible Fisheries: Recreational Fisheries are followed.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".