The Year in Spousal Support: Appeals, Material Changes and More
Bibliographic record
Abstract
At last year’s Family Law Summit, after reviewing the 2016 appeal cases, I focussed my presentation on two SSAG issues: location in the ranges for amount and duration; and the SSAG exceptions. 2016 was a big year for SSAG cases in the Ontario Court of Appeal, notably the decision in Mason v. Mason, 2016 ONCA 725. Mason joins the three other “must-read” SSAG appeal decisions: Fisher v. Fisher, 2008 ONCA 11; Cassidy v. MacNeil, 2010 ONCA 218; and Gray v. Gray, 2014 ONCA 659.\n2016 was also the year of the release of the Revised User’s Guide, an updated user’s guide to the Spousal Support Advisory Guidelines (April 2016). The “official” Guidelines document is still the final version of the SSAG, released by Justice Canada back in July 2008. The R.U.G. should be read with the 2008 SSAG document. The Revised User’s Guide updates the case law to February 2016 and offers lots of practical tips and ideas for the use of the SSAG. It is regularly cited by the courts (over 60 citations across Canada, over 30 in Ontario alone).\nIn 2016, Mason reminded us all not to default to the mid-point on amount, but to explain location in the range. A number of other 2016 appeals addressed “location”: Wharry v. Wharry, 2016 ONCA 920; Berger v. Berger, 2016 ONCA 884; and Elmgreen v. Elmgreen, 2016 ONCA 849.\nIf 2016 was “the year of location” in the Court of Appeal for Ontario, what about 2017? No such coherence is to be found, but there were a couple of important appeal decisions and a few baffling ones.\nMy other theme for 2017 and 2018 is the courts’ continuing struggle over what is or is not a “material change” on variations or motions to change. Here Ontario is not alone, as it has become a cross-Canada problem, and this only a few years after the Supreme Court of Canada restated the law on variation in L.M.P. v. L.S., 2011 SCC 64.
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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 | 0.010 | 0.047 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.013 | 0.004 |
| Scholarly communication | 0.017 | 0.009 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.007 | 0.009 |
| Insufficient payload (model declined to judge) | 0.049 | 0.010 |
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".