‘Born in an atomic test tube’: landscapes of cyclonic development at Uranium City, Saskatchewan
Bibliographic record
Abstract
Drawing together insights from neo‐Innisian geography and environmental history, this paper explores the landscape and environmental changes engendered by ‘cyclonic’ patterns of development associated with uranium production at Uranium City, Saskatchewan. Strong postwar demand for uranium led to the establishment and rapid expansion of Uranium City on the north shore of Lake Athabasca as a ‘yellowcake town’, dedicated to producing uranium oxide concentrate to supply federal government contracts with the US military. In spite of optimistic assessments for the region's industrial future, the new settlement remained inherently unstable, tied to shifting institutional arrangements and external markets, and haunted by the spectre of resource depletion. The planning and development of the townsite at Uranium City reflected both neocolonial desires to open the north to Euro‐Canadian settlement and efforts by the state to buffer the stormy effects of resource dependency. Ultimately, however, quixotic government efforts to implant an outpost of industrial modernity in the Athabasca Region failed to forestall the inevitable winds of change, which left in their wake destructive legacies of social dislocation and environmental degradation, already evident with the near‐collapse of the uranium export market by the early 1960s.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".