Bibliographic record
Abstract
Abstract Shared Decision Making (‘SDM’) is one of the most significant developments in Western health care practices in recent years. Whereas traditional models of care operate on the basis of the physician as the primary medical decision maker, SDM requires patients to be supported to consider options in order to achieve informed preferences by mutually sharing the best available evidence. According to its proponents, SDM is the right way to interpret the clinician‐patient relationship because it fulfils the ethical imperative of respecting patient autonomy. However, there is no consensus about how decisions in SDM contexts relate to the principle of respect for autonomy. In response, I demonstrate that in order to make decisions about what treatment they will or will not receive, patients will be required to meet different conditions depending on the approach proponents of SDM take to understanding personal autonomy. Due to the fact that different conceptions of autonomy yield different obligations, I argue that if physicians and patients satisfied all the conditions described in standard accounts of SDM, then SDM would undermine patient autonomy.
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 | 0.054 | 0.056 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.065 |
| Scholarly communication | 0.010 | 0.011 |
| Open science | 0.002 | 0.013 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".