Entre temps collectif et temps individuel, les espaces de la pêche à la ligne
Bibliographic record
Abstract
With a comparison of several amateur angling techniques, this contribution shows that fishing activities are not limited to solitary practice or small groups. Moreover, fishermen’s conceptions of time and space do not solely consist of reclaiming for oneself a time and a space freed from constraints. Interviews and observations carried out in different places and with enthusiasts practicing various fishing techniques show that this leisure activity links collective and public activities with more private individual activities. Dedicated to the transmission of knowledge based on methods used by trade guilds as well as the setting up of community links, the collective activities take place in constricted and wintry spaces, and then in spring spaces with the start of the fishing season. As the fishing trips are individual in nature and situated in mobile or fixed spaces, they allow the fishermen the opportunity for introspection while fostering an intimate relationship with the animal, based on domination and comfort. The fishing trips also offer the fishermen the possibility to construct themselves as an autonomous subject. If the institutionalization and the intensity of the collective and individual fishing activities depend on the complexity of the techniques applied, their coordination allows the fishermen to constitute themselves as members of a community and as autonomous subjects.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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".