A Voyage to the North West Side of America
Bibliographic record
Abstract
James Colnett, a veteran of James Cook’s second voyage to North America, was an early participant in the maritime sea otter trade. Between 1786 and 1789 his two-vessel expedition traversed the Northwest Coast from Prince William Sound to Vancouver Island and wintered on the Hawaiian Islands. Along the way, he and his crew had some remarkable encounters with Native peoples of the Northwest Coast and the Hawaiian Islands: they were the first Europeans to encounter the Tsimshian and the southern Heiltsuk peoples as well as the first to land on the southern Queen Charlotte Islands. Colnett’s journal of this expedition is published here for the first time. Editor Robert Galois provides extensive annotations, along with an introductory essay addressing the geopolitical context of the voyage and the intellectual background that shaped the writing of the journal. Galois supplements Colnett’s writings with extracts from a second journal -- also previously unpublished -- by Andrew Bracey Taylor, third mate on one of the ships under Colnett’s command. Also included are illustrations from Colnett’s journals and a variety of maps, both contemporary and historical. This fascinating and informative account offers a new understanding of the early European presence in the Northwest and of Native responses to these developments. It will interest historians, geographers, and ethnographers of the Northwest Coast and beyond.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.016 | 0.002 |
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".