A History of Preferential Share in Ontario: Intestacy Legislation and Conceptions of the Deserving or Undeserving Widow
Bibliographic record
Abstract
Ontario’s current method for trying to ensure the fair distribution of an intestate’s estate, or the estate of an individual without a valid Last Will and Testament, is outlined in the Succession Law Reform Act. Specifically, section 45(1) outlines the foundational concept of a “preferential share,” which entitles the surviving spouse to a prescribed financial interest in the estate which is prioritized above all other heirs.The concept of a preferential share stands in sharp contrast with historical English common law methods of devolving intestate estates in which legal entitlements were heavily influenced by an individual’s gender and marital status. In light of the historical influence of gender and marital status on intestacy legislation, this paper investigates the origins and development of the preferential share provision. This paper uses an analytical framework emphasizing the historically gendered experiences of widows and widowers, and how their gender informed the nature of their legal interests under intestacy. In addition, this essay frames its analysis within historical commentary that demonstrates a sharp conceptual dichotomy between the “good wife and deserving widow” or the “bad wife and undeserving widow,” and how such categorization impacted perceptions of what a fair and reasonable devolution entailed.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.028 | 0.026 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".