‘First Among Equals’: Breaking the Deadlock in Parental and Sibling Funeral Disputes
Bibliographic record
Abstract
Family disputes over a loved one’s funeral arrangements are increasingly frequent, with courts intervening if consensus cannot be reached. In many common law jurisdictions, the law favours the executor where the deceased made a will and the highest ranking next-of-kin where the deceased died intestate. But what if two or more people fall within the same kinship tier and have equal rights to determine the deceased’s fate—who has the final say? Adopting a uniquely comparative approach which draws the authorities together for the first time, this article analyses the factors devised by judges in Australia and England, and contrasts them with the discrete statutory tests adopted in parts of Canada and the United States. Having evaluated the various approaches, the article proposes its own hybrid legal solution for breaking the deadlock in so-called ‘equal kinship disputes’.
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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 | 0.040 | 0.066 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.014 | 0.057 |
| Scholarly communication | 0.009 | 0.013 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".