Inuit and Newcomers: Trade and Animal Resources in the Kivalliq, 1900-1945
Bibliographic record
Abstract
Between 1900 and 1945, Qallunaat newcomers, predominantly whalers and fur traders, increased their physical and economic presence in the Kivalliq region, bringing them into closer contact with local Inuit groups. These newcomers worked closely with Inuit partners, as the commercial success of their animal-centric ventures relied on the knowledge and skills of Inuit hunters and trappers. While the newcomers relied on Inuit lifeways for success, they also inadvertently and intentionally brought significant changes to the region in the forms of new technology, ideas, economic systems, ways of living, and viral diseases. This thesis argues that despite the changes brought to the Kivalliq by newcomers, Inuit in this period were able to draw what they desired from these developments, while still maintaining a strong hunting lifeway based on a deep connection with the land and the animals that inhabited it. Drawing on both the written records of Qallunaat whalers and fur traders, and the oral testimonies of Inuit people, it explores how the ventures of whalers and traders were successful because they were compatible with the pre-existing beliefs, lifestyles, and skills of Inuit partners. Thus, attempts to modify Inuit lifestyles largely met with only limited success, as Inuit were able to be selective about which Western technologies and cultural elements they accepted, and generally adopted those that were compatible with pre-existing hunting lifeways.
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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 | 0.002 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".