Fundamental components of a curriculum for residents in health advocacy
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
PURPOSE: To develop components of a curriculum for teaching and evaluating Residents as health advocates. METHOD: Modeled on the Delphi technique, the first step involved a multidisciplinary panel of 10 Queen's University health care providers with expertize in education and patient advocacy. In the context of four Advocacy questions: What is it?, Who does it?, How to teach it?, and How to evaluate it?, they discussed a curriculum framework including graded education, scholarly activity, role modeling, and case examples. In the second step, 24 faculty experts addressed two goals: (1) to identify attributes discussed by the expert panel in step 1 and corresponding measurable behaviours and (2) to refine the curriculum framework proposed in step 1 with emphasis on content and evaluation. RESULTS: Six attributes of a health advocate were identified; knowledgeable, altruistic, honest, assertive, resourceful, and up-to date. Behaviours that reflect these attributes were identified as desirable or undesirable and means of teaching were matched to the attributes. For most residents, skills would be developed in a graded fashion, progressing from advocating for the individual to society as a whole. CONCLUSIONS: This study provides a general framework from which specialty-specific curriculums for training health advocates can be developed.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it