Bibliographic record
Abstract
“Furs is what brings us,” remarked an early trader in the Oregon Country, adding, however, that “the difficulty of getting the necessary supplies will continue to operate against it,” located as it was, “on the worst side of the Rocky Mountains.” Fortunately, the discovery in 1805 by Lewis and Clark that the Columbia River was navigable by canoe or boat to the Pacific led to the logistical linking of the New Caledonia and Columbia Districts by means of the Fraser-Columbia brigade system. First used in 1811 by the North West Company, this transport system of North canoes, Indian pack horses, and Columbia batteaux eventually became the lifeline of the fur trade of the Hudson’s Bay Company’s Columbia Department until 1847, when the route was severed by the extension of the Canada-US border along the forty-ninth parallel to the Pacific. In The Lifeline of the Oregon Country, James Gibson compellingly immerses the reader in one of the most intractable problems faced by the Hudson’s Bay Company: how to realize wealth from such a remote and formidable land. The personalities, places, obstacles, and operations involved in the brigade system are all described in fascinating detail, stretch by stretch from Fort St. James, the depot of New Caledonia on the upper reaches of the Fraser River, to Fort Vancouver, the Columbia Department’s entrepôt on the lower Columbia River, and back. Never before has such a rich collection of primary information concerning the fur trade supply system and the constraining role of logistics been so meticulously assembled. The Lifeline of the Oregon Country will prove indispensable to historians, researchers, and fur trade enthusiasts alike, and is an important contribution to our understanding of the economic history of the Pacific Slope.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.062 | 0.008 |
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".