“The Disease that Knowledge Must Cure”? Sites of Uncertainty and Imagined Futures of Baker Lake, Nunavut
Bibliographic record
Abstract
After nearly eight years of formal environmental review, in July 2016, the Canadian federal government rejected the French multinational AREVA’s proposal to construct a uranium mine 80 kilometers west of Qamani’tuaq/Baker Lake, a small inland and mainly Inuit hamlet in the Kivalliq region of Nunavut. The decision not to grant a license for resource development was based on a technical uncertainty, that is, AREVA was not able to provide a start-date for the mining project due to the depressed uranium market. Yet, as this thesis will demonstrate, this controversy underlies a far more complex and ongoing negotiation with uncertainty. In order to explore diverging engagements with uncertainty, this thesis develops the concept of sites of uncertainty, which are spaces —physical, temporal, emotional, material, discursive and so on—that are occupied by a “state of not knowing” (Cameron, 2015: 34). Drawing on qualitative fieldwork conducted in Baker Lake in November and December of 2016, this thesis will identify key sites of uncertainty where AREVA, government officials, Inuit organizations, and community residents constructed, negotiated, expressed, transformed, experienced, and responded to uncertainty. The analysis of these sites reveals diverse, dynamic, and conflicting conceptualizations of self-sufficiency, well-being, and ultimately identity, which, this thesis argues, led to muddy responses to AREVA’s proposal as well as imagined futures of Baker Lake. Moreover, this thesis explains how local residents’ calls for improvements in education are reflective of an intermeshing of Inuit and western epistemologies. While Inuit ways of knowing and being have persisted, flourished, and creatively adapted to contemporary resource development controversies, they do so largely by conforming to western norms and knowledge systems.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.038 | 0.040 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".