Bibliographic record
Abstract
This article seeks to elucidate the dual conceptions or theories of fault that exist in the domain of medical liability law. The first of these is often characterized as "descriptive" or "customary," as appears from a survey of relevant jurisprudential and doctrinal sources, However, this predominant understanding of medical malpractice is increasingly facing scrutiny as a second conception emerges. This alternative perspective is manifested through the development, across various jurisdictions, of a normative lexicon—specifically the term "reasonableness"—which delineates the legal standard anticipated of a physician's conduct, In addition to the oversight exercised by the exclusion of customary practices that may exhibit evident deficiencies or hazards, contemporary courts have also been entrusted with the critical function of acting as "guatekeepers " of the quality of scientific evidence required to evaluate the propriety of medical practices. This article further delves into specific concerns and ambiguities related to the evidentiary aspects of establishing a customary standard. Such uncertainties, we conlude, will in turn perpetuate a standard that is still essentially grounded in established custom and clinical practices.
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 | 0.015 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.005 | 0.070 |
| Scholarly communication | 0.012 | 0.013 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.013 | 0.011 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".