Bibliographic record
Abstract
This chapter will describe the history of nuclear weapons/power in Canada and then move on to how nuclear waste is being managed. This management involves overall aims and objectives and the implementation of these aims and objectives. However, it is important to see these processes as distinct as there is always contingency and slippage between governance aims and objectives and place-based implementation. This is because governance is never a straight-forward process or cycle of conceiving, planning, and implementing, but a far more iterative and recursive process ( Cotton 2017 ). Also, as Bickerstaff (2012) argues, whenever a government, as in the United Kingdom or Canada, conceives a shiny new plan, there is an implicit exorcism of the sins and mistakes of the past and an attempt to present a new beginning, or baseline. This is an aspect of forgetting and presenteeism this book has encountered again and again: however, in peripheralised communities, history and remembering are fundamental to identity and acts of agency and power.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.009 | 0.003 |
| Scholarly communication | 0.009 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.046 | 0.009 |
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".