From the Clinic to the Community
Bibliographic record
Abstract
PURPOSE: The integration of health advocacy activities into medical training has been controversial and challenging from theoretical and practical standpoints. In part, this may be because it is unclear how such activities could be incorporated into the everyday practices of most physicians. This study explored the breadth of advocacy activities described by physicians engaged in health advocacy in order to articulate a set of activities that might be enacted regularly by all physicians. METHOD: From October 2012 to June 2013, 10 physician advocates from British Columbia were interviewed. Using transcriptions from semistructured interviews, the authors identified all advocacy activities described by participants. Employing an iterative process of individual and group analysis, the authors developed conceptual categories building on previously developed frameworks to represent the types of activities participants articulated. RESULTS: Physician participants identified five main categories of advocacy activities: clinical agency, paraclinical agency, practice quality improvement, activism, and knowledge exchange. These were enacted at one of three levels: individual patient, practice, and community/system. They also identified a wide range of abilities and perspectives that they employed across all levels and activities. CONCLUSIONS: Most activities described by health advocates at the patient and practice level (clinical agency, paraclinical agency, practice quality improvement) might reasonably be incorporated into the professional lives of all physicians if training incorporated some reorientation of perspective. Many activities at the system level (activism and knowledge exchange) perhaps require more elaborate skill development and support, which could be provided for those interested in pursuing further advocacy training.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.004 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.043 | 0.006 |
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".