Bibliographic record
Abstract
Abstract: Standardized Patient Programs (SPPs) enlist actors to roleplay the symptoms of various diseases and disorders, and to embody a range of personalities. These simulations are used to help improve the communicative practices and professional competencies of future healthcare workers. Focusing on the use of these programs for medical students and doctors, this article establishes a kairology of the SPP to better understand the shifting terrains of patient representation. A kairological account focuses on “historical moments as rhetorical opportunities” (Segal, 2005, p. 23) and, in the case of medicine, illustrates how “changes in [medical] practice are importantly reciprocal with changes in the terms of practice” (Segal, 2005, p. 22). I trace the SPP through various linguistic iterations to reveal how the shifting language of simulated patienthood reflects different orientations towards medical pedagogy and patient populations at significant junctures in time. I conclude my kairology with an examination of the Indigenous Simulated Patient Program, a 2011 pilot program that has the potential to better represent and serve Indigenous peoples in medical pedagogy and practice.
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 | 0.013 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.011 | 0.041 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 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".