Transforming spousal support from the ground up: Carol Rogerson and the development of the spousal support advisory guidelines
Bibliographic record
Abstract
It is not an exaggeration to say that Carol Rogerson has been instrumental in shaping Canadian family law. Along with Rollie Thompson of the Schulich School of Law at Dalhousie University, Carol created the Spousal Support Advisory Guidelines (SSAGs), a set of informal and non-binding guidelines that have fundamentally reshaped the Canadian law of spousal support. The importance of the SSAGs is impossible to overstate; they have given coherence and structure to an area of law that had become uncertain and unpredictable. The SSAGs have made spousal support orders more consistent and more principled, and the clarity that they provide has also improved access to justice by encouraging negotiation and settlement. Through her ground-breaking work on the SSAGs, Rogerson not only transformed the law, but she also improved the process for all Canadians involved in spousal support claims.
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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 | 0.027 | 0.061 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.032 | 0.042 |
| Scholarly communication | 0.015 | 0.009 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.011 | 0.021 |
| Insufficient payload (model declined to judge) | 0.003 | 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".