Application of the oppression remedy: The "reasonable expectation" test
Bibliographic record
Abstract
The adoption of the oppression remedy in Canada empowers the corporation stakeholders to bring an action against the corporation when the conduct of the corporation has an effect that is oppressive, unfairly prejudicial, or unfairly disregards the interests of a stakeholder. However, according to S.241 of the CBCA, it provides a wide scope of the oppression and gives a court a wide power in defining the specific oppression case. Although there is no clear guidance in the application of the oppression remedy in Canada, it has been widely recognized that courts gravitate towards using a test of "Reasonable Expectation" of the complaint in the judicial application of the oppression remedy. The purpose of the thesis is to briefly introduce the evolvement of the test and focus on the determination of the "reasonableness" in the judicial exercise of the discretion.
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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 | 0.031 | 0.085 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.033 |
| Scholarly communication | 0.010 | 0.008 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.015 | 0.013 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".