Fishy Pleasures: Unsettling Fish Hatching and Fish Catching on Pacific Frontiers
Bibliographic record
Abstract
In debates over Puget Sound salmon recovery, the Wild Steelhead Federation, a settler sportfishing advocate, argues that hatchery-raised steelhead lack fighting spirit, and figures them as unnatural. The Northwest Indian Fisheries Commission and its member tribes operate hatcheries as strategy for maintaining fish runs until degraded habitats can be restored, and figure hatcheries as one of many sites of making relations. Although the genetic science mobilized on all sides of this debate is fairly new, settler discourses that, on the one hand, blame tribal harvest for salmon decline and, on the other hand, construe sportfishing as central to settler family-making and masculinities, have roots going back to the notion of the frontier itself. As a slantwise intervention in this debate, I consider sportfishing as a site and strategy for making settler sexualities, by examining visual archives that document historical practices of sportfishing and the technologies on which contemporary salmon and trout sportfishing depends: the reservoir, the fish hatchery, and the fishing pole. Tracing arguments about Nature and settler masculinities back to the origins of fish culture in hatcheries through the writing of George Perkins Marsh, I argue labeling either normative settler sexualities and gender relations or the flooded spawning grounds beneath reservoirs as unnatural threatens co-constituted settler sexualities and reworkings of “natural” landscapes.
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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 | 0.000 |
| Science and technology studies | 0.009 | 0.027 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".