Bibliographic record
Abstract
Inuit employment in the mining industry has received very little attention from historians, although mining has been in the Arctic since the 1950s. Using the Polaris mine (1982-2002) on Little Cornwallis Island, Nunavut, as a case study, this article focuses on the Canadian government’s shift away from supporting mining developments in the late 1970s to early 1980s, on Inuit employment in the mining industry, and on the difficulties of Inuit from Resolute Bay in obtaining employment at Polaris. Previous to Polaris, the federal government saw Arctic mines, particularly Rankin Inlet (1951-1962) and Nanisivik (1976-2002), as a path to modernisation for the Inuit. However, as these earlier Arctic mines failed in this particular goal, the State became disillusioned and weary of providing financial support by the time Cominco began planning the Polaris mine in 1973. The federal government did not require Cominco to sign a formal agreement for Inuit employment, leaving the company responsible to develop its own hiring agenda. Unfortunately for the people of Resolute Bay, the company agenda did not include hiring locals as a priority, and bypassed and marginalised Resolute Bay Inuit who were keen on working at the mine. As mining has been the largest industry in the Canadian northern economy and is currently growing and beginning new development projects, it is important to understand the historical dynamics between mining companies, the State, and local communities.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.032 | 0.004 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".