Welcome waste – interpreting narratives of radioactive waste disposal in two small towns in Ontario, Canada
Bibliographic record
Abstract
After briefly reviewing the production of nuclear energy and waste in Canada, this paper uses two small Ontario towns as case studies to examine the treatment of low-level radioactive waste and the communities’ responses and narratives to it. Both towns, Port Hope and Kincardine, have long histories of dealing with such waste. Using interviews, relevant websites and past accounts, this paper employs a discourse analysis to understand the differences in risk perceptions and living with the presence of these materials. Ideas from landscape narratives are employed to show that responses in Port Hope are dominated by death, elegy and crime, whereas those in Kincardine are predominately linked to progressivism and optimism. We explore the characteristics of each case to highlight the reasons for these differences. We conclude by emphasizing the potential role of narrative analysis in informing policymaking.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.034 | 0.015 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| 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".