Bibliographic record
Abstract
Fiduciary duties are critical to the integrity of a remarkable variety of relationships, including those between trustee and beneficiary, director and corporation, agent and principal, lawyer and client, doctor and patient, parent and child, and guardian and ward. Notwithstanding their variety, all fiduciary relationships are presumed to enjoy common characteristics and to attract a core set of demanding legal duties, most notably a duty of loyalty. Surprisingly, however, the justification for fiduciary duties is an enigma in private law theory. It is unclear what makes a relationship fiduciary and why fiduciary relationships attract fiduciary duties. This article takes up the enigma. It assesses leading reductivist and instrumentalist analyses of the justification for fiduciary duties. Finding them wanting, it offers an alternative account of the juridical justification for fiduciary duties. The author contends that the fiduciary relationship is a distinctive kind of legal relationship in which one person (the fiduciary) exercises power over practical interests of another (the beneficiary). Fiduciary power is a form of authority derived from the legal capacity of the beneficiary or a benefactor. The duty of loyalty is justified on the basis that it secures the exclusivity of the beneficiary’s claim over fiduciary power so understood.
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 | 0.024 | 0.043 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.009 | 0.041 |
| Scholarly communication | 0.008 | 0.010 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.013 | 0.013 |
| Insufficient payload (model declined to judge) | 0.005 | 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".