MétaCan
Menu
Back to cohort

‘Born in an atomic test tube’: landscapes of cyclonic development at Uranium City, Saskatchewan

2010· article· en· W1918686860 on OpenAlexaffvenueabout
Arn Keeling

Bibliographic record

VenueCanadian Geographies / Géographies canadiennes · 2010
Typearticle
Languageen
FieldEngineering
TopicMining and Resource Management
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsUraniumUranium oxideShoreGovernment (linguistics)Settlement (finance)Resource (disambiguation)BusinessGeologyOceanography

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.149
Threshold uncertainty score0.300

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0060.005
Scholarly communication0.0040.001
Open science0.0010.003
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.000

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.

Opus teacher head0.005
GPT teacher head0.169
Teacher spread0.164 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations48
Published2010
Admission routes3
Has abstractyes

Explore more

Same venueCanadian Geographies / Géographies canadiennesSame topicMining and Resource ManagementFrench-language works237,207