The Struggle for Fishing Resources in the Pacific Northwest in the Late Twentieth Century
Bibliographic record
Abstract
From the beginnings of the European penetration of the areas eventually to comprise the United States and Canada, first explorers, then resource seekers, and finally settlers commonly reported enthusiastically about the abundant riches and enormous extent of the lands they encountered. Nothing in their experiences in Europe prepared them for the overwhelming size of the land, forests that seemed to stretch endlessly westward, abundant animal life, rivers and lakes that drained an immense interior, and richly fertile soils. Almost immediately, a belief blossomed in the minds of early settlers that America was blessed with “inexhaustible resources.” As settlement moved inland and up river valleys during the colonial period, farmers found fresh soils to exploit for tobacco and wheat, and plentiful fur resources lured men beyond the Appalachians. After independence, as settlement moved westward, Americans found rich soils in the Old Northwest and Old Southwest, vast expanses of prairie lands, enormous forests of pine, and mineral wealth beyond most people's imagination: gold, silver, iron, copper, and finally oil. While Native peoples had occupied these lands for thousands of years, these resources, which so amazed Europeans, had been only lightly exploited. Indeed, one can argue that much of the extraordinary wealth and economic power accumulated in the United States by the early twentieth century can be explained by the aggressive exploitation of the cheap, abundant, and hardly-used resources available in North America.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".