Bibliographic record
Abstract
How well do we truly understand the legal concepts we regularly use and discuss? Truly understanding a legal concept necessitates understanding why it exists, what it was constructed to accomplish, and the purpose or purposes it was intended to facilitate. A lack of attentiveness to that raison d’être results in the loss of connection between the concepts and their underlying rationales. The divorce between legal concepts and their philosophical foundations renders the former susceptible to manipulation and misuse as they lose their connection to their philosophical and doctrinal foundations and subsequently become more and more unintelligible. As it presently sits, fiduciary jurisprudence is one of the most confused and least understood areas of contemporary law. This is not a new development, but one of long standing. Jurisprudence and legal commentary indicate that both lawyers and judges misuse fiduciary principles for reasons inconsistent with fiduciary law’s conceptual foundation. The primary purpose of this article is to enhance the understanding of fiduciary duties and relationship fiduciarity by promoting a more robust understanding of the fiduciary concept centred upon its foundational raison d’être. In the process of establishing a stronger philosophical and doctrinal base for the fiduciary concept, the article will also contemplate the contributions provided by of one of the more recent additions to fiduciary law scholarship, authored by Remus Valsan and published in a recent issue of this same law journal.
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 | 0.011 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.007 | 0.048 |
| Scholarly communication | 0.012 | 0.020 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 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".