Bibliographic record
Abstract
Using unused or little-known documents, Keith fills in gaps and corrects inconsistencies in previous information about the company. North of Athabasca not only includes the extensively annotated texts of eleven North West Company documents but Keith's introductory essay amplifies what is known about the context of the fur trade. His biographical notes provide personal details about the proprietors and clerks involved in the fur trade as well as the engagés and aboriginal trading leaders. A sketch of the trading activities of every Native mentioned in the journals is included. Engagés are shown to be more than labouring drones - Keith demonstrates that men such as Jean-Baptiste LaPrise were as important in furthering the interests of the North West Company north of Athabasca as any of the clerks or proprietors who kept the accounts and wrote the journals included here. The journals, often in fractured English or colloquial Canadian French, and incorporating aboriginal terminology, make intriguing reading. A glossary is provided to assist with some of the more arcane terms. North of Athabasca fills an important void in the literature on this period and region. Readers interested in fur trade history as well as students of exploration, genealogy, ethnography, and Native studies will find this a welcome addition to the literature on a fascinating topic.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.067 | 0.009 |
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".