Salmon propagation and settler colonialism in California: the United States Fish Commission, the McCloud River Hatchery, and the dispossession of the Winnemem Wintu
Bibliographic record
Abstract
Congress created the United States Fish Commission (USFC) in 1871 to investigate the causes of fish diminution on the Atlantic seaboard, but the USFC’s remit soon expanded from study to intervention. In settler California, the USFC set up one of its first hatcheries for chinook salmon propagation on the McCloud River, a tributary of the Sacramento. In so doing, the USFC dispossessed and subordinated the Winnemem Wintu people who lived on the river, a sad story of colonial violence that has been downplayed in existing historiography. The USFC distributed the products of this hatchery – millions of chinook salmon eggs and juvenile fish – across America and to foreign nations interested in fish ‘acclimatization’, the contemporary term for non-native species introductions. New Zealander and Australian acclimatization societies contracted with the USFC in the 1870s and 1880s to introduce chinook salmon there in hopes of aggressively remaking waters to better suit the culinary tastes and angling preferences of European-descended settlers. Over time, the salmon productivity of the river declined, ceasing entirely with the Shasta Dam’s construction in the 1940s. But in an exemplar of Indigenous resilience and environmental stewardship, today the Wintu are leading efforts to restore chinook salmon to the river.
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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 | 0.009 | 0.007 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".