Bibliographic record
Abstract
Abstract In a variety of familial, commercial, and professional contexts, the law imposes fiduciary duties. A clear delineation of their content and scope is crucial for guiding fiduciaries and safeguarding beneficiaries. Yet common law has fostered two entirely distinct conceptions of the “fiduciary.” According to the proprietary conception, fiduciary law stops short at protecting the beneficiary’s proprietary interests. In contrast, the interpersonal conception views fiduciary law as tasked with regulating the fiduciary–beneficiary relationship. By examining case law on four fiduciary relationships—doctor–patient, parent–child, director–company, and lawyer–client—in leading common-law jurisdictions (the UK, US, Australia, and Canada), this chapter uncovers these underlying conceptions. Recognizing these distinctions aids in resolving disputes and refining debates about fiduciary law’s role. The chapter further demonstrates that specific jurisdictions consistently apply one of these conceptions across different fiduciary relationships. This finding highlights the importance of fiduciary law as a focal point of interface between various fields of law.
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 | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.005 | 0.062 |
| Scholarly communication | 0.012 | 0.008 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.004 | 0.007 |
| 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".