Bibliographic record
Abstract
This Article examines and critiques the global binary debate surrounding opt-in versus opt-out legal regimes for regulating unmarried cohabitants’ financial obligations upon separation. Using Canadian jurisdictions as a case study, it challenges the prevailing academic consensus that endorses opt-out systems as superior policy, based on assumptions that they are fairer, sufficiently preserve autonomy, enhance certainty, and particularly benefit women. Drawing on empirical research, the Article explores how couples engaged with British Columbia’s opt-out scheme. In-depth interviews suggest that default rules operate as quasi-mandatory, with opting out proving remarkably difficult. Moreover, the law often falls short of achieving the anticipated certainty and struggles to accommodate the diverse interests of women. The analysis cautions against transformative reforms to cohabitation law based on unexamined or overly broad assumptions and highlights shortcomings in the dominant binary policy debate between opt-in and opt-out models. Given these limitations, the Article evaluates various conceptual approaches for reform. While acknowledging the promise of bolder anti-exceptionalist visions departing from existing paradigms, it concludes that, at present, modest refinements to opt-out models are more feasible and offer viable pathways to engender incremental improvements.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.007 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.018 | 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".