The presumption of resulting trust and beneficiary designations: What’s intention go to do with it?
Bibliographic record
Abstract
When opening an RRSP or RRIF, investors typically designate a beneficiary. We expect that, when making this choice, most investors intend that their designated beneficiary will indeed benefit from the investment on their death. And further, if there is a dispute between the designated beneficiary and the investor’s estate, we expect investors intend that their choice of beneficiary will prevail. Surprisingly, this is not the case in many provincial appellate courts, which in fact favour the estate in such disputes. More specifically, most Canadian courts apply the presumption of resulting trust to beneficiary designations: they assume, absent other evidence, that the designated beneficiary holds the proceeds of the RRSP or RRIF in trust for the deceased investor’s estate. Only Saskatchewan has taken a contrary position. The Alberta Court of Queen’s Bench in Morrison v Morrison recently weighed both options and endorsed the approach that applies the presumption of resulting trust.In the present article, we analyze the doctrine of resulting trust, its rationale as presented by several leading cases, and empirical evidence evaluating the intentions of Canadian investors. We conclude that applying the presumption of resulting trust to beneficiary designations betrays both the theory and purpose of the presumption. It also runs counter to the intentions of most Canadians and creates uncertainties in millions of beneficiary designations. Finally, we present several solutions for bringing the law in line with the intentions of investors, and indeed common sense.
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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 | 0.015 | 0.039 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.011 | 0.038 |
| Scholarly communication | 0.014 | 0.012 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.007 | 0.011 |
| Insufficient payload (model declined to judge) | 0.004 | 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".