Bibliographic record
Abstract
In this chapter I analyse why and how, through the development of a fly-fishing recreation culture, English anglers have developed a deep association with, and understanding of, the aquatic insects that provide the focus of their enthusiasm. Today, that understanding combined with the substantial economy of recreational fly-fishing and its socially powerful 'disciples' means that the environmental needs of the insects figure in the conservation and management of fisheries just as much as the needs of the trout themselves. This extraordinarily intense association with insects that mainstream society eschews (but which spread rapidly to the United States, Canada, Australia, Chile, Scandinavia and to Japan) is extremely unusual and unique so its development is all the more important to understand (see Franklin 1996; 2002). This essay develops a textual analysis of the history of this association with insects and the nexus with trout through a reading of the rich literature of fly-fishing, beginning in the medieval period and stretching through to the contemporary period. It can be seen that although it has the appearance of an ancient practice, its essential properties and knowledge are actually a very recent development and relate more to modern than traditional practices with nature.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".