Terminology and Praxis: Clarifying the Scope of Narrative in Medicine
Bibliographic record
Abstract
Until about thirty years ago, narrative and narrative theory were the province of those disciplines that have traditionally formed the accepted core of the humanities: literary, cultural, religious, and, to a lesser extent, philosophical studies.researchers in these fields-whether hardcore narratologists or narrative ethicists-tend not to produce narratives, but to receive them.Their work involves commenting analytically on that reception, looking at the determinants, operations, and semantics of individual narratives or of narrative as a genus.narrative theory now populates new and rather different territories-those fields that support narrative production as well as consumption, including history and historiography, ethnography, law, therapy, and of course, medicine.1 our interest lies specifically in the theoretical and practical uses of narrative in the medical field, and we began with a review of the relevant literature that generated some surprising results.We expected the influence of narrative in medicine, which had captured the interest of physicians and scholars, to be legible in medical and humanities publications.moreover, we had observed the ways in which popular culture reflected that interest in media, ranging from print publications such as The Atlantic Monthly and The New York Times to television series such as House, M.D. 2 We were nonetheless surprised by the sheer volume of articles, essays, and editorials we discovered when we conducted a search in medical and humanities journals using the keywords "narrative and medicine."our search returned no fewer than 7,000 related writings, raising the question of precisely how narrative was being employed by its various proponents, for the remarkable quantity of this research alone does not give one a sense of the range
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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 | 0.043 | 0.077 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.010 | 0.081 |
| Scholarly communication | 0.014 | 0.038 |
| Open science | 0.003 | 0.014 |
| Research integrity | 0.005 | 0.012 |
| Insufficient payload (model declined to judge) | 0.002 | 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".