Examining Patterns of Food Exchange and Dependency at Moose Fort, 1783-1785
Bibliographic record
Abstract
Many historians studying the fur trade have argued or assumed that Indigenous peoples swiftly became dependent on the fur trading posts in North America for their survival. In order to gain insight into native-newcomer relations but also particuarly to address the question of dependency, this paper examines patterns of food exchange between Hudson’s Bay Company men employed at Moose Fort and the James Bay Cree homeguard that lived near the Fort from October 1783 to September 1785. It finds that the flow of foodstuffs from Indigenous peoples to Moose Fort greatly outweighed the flow of food from the Fort to Iindigenous peoples. Furthermore, this paper will argue that the traders of Moose Fort were consistently reliant upon these provisions supplied by Indigenous hunters, trappers and fishers, as periods when most Indigenous providers were absent from the area resulted in conditions of food crises at the Fort. Thus, the relations of food exchange at Moose Fort provided mutual benefits to both parties, but it was ultimately the Fort itself that was much more dependent upon this relationship. Overall, this evidence calls for more nuanced and less one-sided theoretical models of dependency in the history of the fur trade.
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 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".