“With Iron We Conquer”: Deindustrialization, Settler Colonialism, and the Last Train out of Schefferville, Quebec
Bibliographic record
Abstract
The Iron Ore Company of Canada announced the closure of its mine in Schefferville, Quebec, on 2 November 1982, throwing the town’s future in doubt. Its slow agony made headlines across Canada for weeks, months, and even years. This article considers how the politics of deindustrialization got bound up in the national project of the settler-colonial state and the political ambitions of politicians, given that the company was led by Brian Mulroney, who became Canada’s prime minister soon thereafter. Due to its perceived symbolic importance, a Quebec parliamentary commission of inquiry was named to inquire into the fate of the town, offering us the opportunity to consider the ways in which race and settler colonialism structured the process and how white residents and politicians as well as Indigenous leaders understood the significance of what was going on. The mine’s closure had devastating economic consequences for the Innu and Naskapi communities, as well as the white residents, but it also marked a recentring for Indigenous people displaced from the socio-economic and political periphery to the centre of what remained behind in deindustrialization’s aftermath.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.007 |
| Science and technology studies | 0.015 | 0.014 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".