The Ontario nuclear power dispute: a strategic analysis
Bibliographic record
Abstract
Abstract Background The Graph Model for Conflict Resolution methodology is used to formally investigate the nuclear power dispute that took place in the Canadian province of Ontario in order to obtain strategic insights into its resolution. This flexible systems methodology is used to study the nuclear conflict at two key points in time, 2008 and 2010. Results The results of the 2008 analysis show that the only decision makers involved in the conflict who hold real power are the Federal and Ontario governments, although at the beginning of the investigation other organizations had also been considered as participating decision makers. According to a strategic analysis carried out for the conflict as it existed in 2010, the equilibria or potential resolutions of the 2008 analysis are found to be transitional states leading to the 2010 resolution. Moreover, a negative attitude by the Federal Government can cause an outcome to occur that is not highly preferred by either the Federal Government or the province of Ontario. Conclusions By closely following the decision makers’ actions, a detailed analysis of the nuclear dispute in Ontario is carried out. Stability, sensitivity, and attitude analyses are performed, and the results are closely correlated with what happened in reality.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".