Post-Separation Increases in Payor Income and Spousal Support
Bibliographic record
Abstract
In 2016, Brian Burke and Joanna Hunt wrote a very helpful article on the subject in the Canadian Family Law Quarterly.1 Why so much litigation? Because most recipients (and their lawyers) can understand that, if they can make the payor's income go up, the SSAG range can be increased, and maybe spousal support too. [...]the resolution of this issue - like so many others under the SSAG - reflects our understanding of the law of spousal support entitlement.2 To date, judges (and lawyers) who understand compensatory support get the post-separation analysis right and find the requisite "link" for full or substantial sharing. The Court of Appeal held that the husband's post-separation income increase had been properly shared, given the compensatory foundation of the support order and the lower court's finding of "a causal link between her relative disadvantage and the marriage".5 Tranmer J. had described the $12,000 a month support as "just below the low end of the [SSAG] range" on their higher 2016 incomes, $632,827 for him and $110,114 for her, both up from their 2008 incomes of $414,664 and $76,115.6 By the date of termination, the compensatory entitlement would no longer exist. [...]on the basis of the evidence, I do not find that the Respondent has made the type of sacrifices that the courts have required in order to justify such an award.14 On appeal, this ruling was upheld, even though "the reasons leave much to be desired".15 Again, there was an explicit appellate reference to the motions judge's use of the principles in Thompson, but nothing more.16 From the skimpy reasons at both levels, we might surmise a weaker compensatory claim, and it was a delayed request for increased retroactive and prospective spousal support.17 Even if the outcome might be right on the merits, more analysis was warranted at both levels of court.
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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 | 0.002 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".