Bibliographic record
Abstract
The Ontario Court of Appeal decision in Miglin v. Miglin has been the topic of much discussion. The Court of Appeal held that courts could override separation agreements where there had been a material change in circumstances. In this article, we seek to think through the Miglin issue, namely the threshold upon which courts should override the spousal support provisions of valid separation agreements. The central difficulty, in our view, of abandoning the Pelech trilogy standard is determining what should replace it. We begin our discussion of the Miglin issue with an overview of the Miglin case itself. We then attempt to unravel three important strands of the complex debate that Miglin has generated: 1) why departing from the Pelech trilogy elicits strong responses, 2) the problems that arise in contracting about spousal support, and 3) difficult issues that further complicate the task of crafting an override standard, specifically the problems of shifting norms and inconsistent statutory standards. In the final part of the article, we turn to the challenge of crafting an appropriate override standard. In our view, a standard that assesses the substantive fairness of the agreement, either at the time it was entered into or at the time at which the application to overrides is brought, represents the most promising approach.
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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 | 0.025 | 0.031 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.014 | 0.044 |
| Scholarly communication | 0.015 | 0.015 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.013 | 0.013 |
| Insufficient payload (model declined to judge) | 0.003 | 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".