Fiduciary Law’s ‘Holy Grail’: Reconciling Theory and Practice in Fiduciary Jurisprudence
Bibliographic record
Abstract
Fiduciary law has experienced tremendous growth over the past few decades. However, its indiscriminate and generally unexplained use, particularly to justify results-oriented decision making, has created a confused and problematic jurisprudence. Fiduciary law was never intended to apply to the garden variety of cases. Rather, it was established for use only where the laws of contract, tort and unjust enrichment were silent or deficient. Yet, even in those circumstances, it applied solely in regard to socially or economically important or necessary interactions of high trust and confidence creating implicit dependency and peculiar vulnerability. This Article lays the foundation for developing a more sound fiduciary jurisprudence by identifying the “holy grail” that unites the theory of fiduciary obligations with its practical application. It demonstrates how fiduciary law may properly facilitate situationally-appropriate justice in ways that the ordinary laws of civil obligation cannot. Further, it establishes an enhanced understanding of fiduciary law that both complements the laws of contract, tort, and unjust enrichment and is consistent with fiduciary law’s historical and theoretical foundations.
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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 | 0.046 | 0.045 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.009 | 0.131 |
| Scholarly communication | 0.016 | 0.020 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.011 | 0.016 |
| Insufficient payload (model declined to judge) | 0.002 | 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".