Des « beaux bars » aux racontars – mondes et mythes de la pêche de loisir sur la côte d’Opale
Bibliographic record
Abstract
Les mondes de la pêche de loisir se partageant dans la plupart des cas les mêmes espaces maritimes et littoraux que ceux de la pêche professionnelle, certaines pratiques entrent en concurrence. Le monde de la pêche de loisir est pluriel, des pratiques sociales se distinguent de par leurs représentations de la mer, les ressources pêchées ou les techniques de pêche, mais surtout, de par les intérêts qu’ils défendent respectivement. C’est dans ce contexte des Hauts-de-France que le concept de « mythe » est exploré à partir d’analyses des discours de pêcheurs et de leurs pratiques récoltées au plus près des acteurs locaux interrogés. Cet article met en exergue les divergences existantes entre les mondes de la pêche de loisir et professionnelle et leurs légitimités respectives à occuper le Domaine Public Maritime, tout particulièrement dans ce que cela implique du point de vue normatif (quotas, pratiques tolérées, etc.).
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.028 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".