Contrasting epistemologies: Biomedicine, narrative medicine and indigenous story medicine
Bibliographic record
Abstract
BACKGROUND: Narrative Medicine (NM) and Indigenous Story Medicine both use narrative to understand and effect health, but their respective conceptualizations of narrative differ. AIMS: I contrast the concept of narrative in NM with that of Indigenous Story Medicine. MATERIALS AND METHODS: The article relies Western narrative theorists as well as Indigenous epistemologists to frame a discussion-by-contrast of the Judeo-Christian creation myth with a Haundenosaunee Creation Story. RESULTS: I demonstrate that the deficiencies of Narrative Medicine exist because the latter's use of narrative is a mere application in an otherwise reductive field, whereas Indigenous epistemologies rely on story as medicine itself. DISCUSSION: OMIT. CONCLUSION: I call for more scholars to take up different narratives to further investigate the ethical space between NM and Indigenous Story Medicine.
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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 | 0.017 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.063 |
| Scholarly communication | 0.010 | 0.011 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.003 | 0.004 |
| 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".