Bibliographic record
Abstract
The patient-physician relationship is of primary importance for medical ethics, but it also teaches broader lessons about ethics generally. This is particularly true for the philosopher Emmanuel Levinas whose ethics is grounded in the other who "faces" the subject and whose suffering provokes responsibility. Given the pragmatic, situational character of Levinasian ethics, the "face of the other" may be elucidated by an analogy with the "face of the patient." To do so, I draw on examples from Martin Winckler's fictional physician narratives. In addition, I explore how the standpoint of the physician conceals a related but often unacknowledged dimension of care: the obligation to nurse. For both nurse and physician, one question encapsulates Levinas' medical ethics: "What does the patient say?" Using this as my guiding question, I examine the context within which physician, nurse, and patient meet in order to highlight their shared vulnerability and the care relationship that binds them together.
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 | 0.012 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.088 |
| Scholarly communication | 0.008 | 0.010 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.010 | 0.009 |
| Insufficient payload (model declined to judge) | 0.002 | 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".