Bibliographic record
Abstract
We wish to thank Boya Abudu for the thoughtful reply to our article.1 In the letter, the author highlights the importance of community engagement as a critical means of reducing socioeconomic disparities. We agree wholeheartedly that the most sustainable solutions to system- and community-level concerns come from communities themselves. For instance, in their “Framework for Building Primary Care Capacity to Address the Social Determinants of Health,” Drs. Pinto and Bloch2 emphasize patient and community engagement as a core pillar in the attempts to directly intervene on the social determinants of health (SDOH). In their context, this is done through hiring a community engagement specialist as part of their family health team (FHT) and engaging patient advisors on their FHT’s SDOH committee. The author of the letter describes community-based participatory research (CBPR) as a means of addressing community concerns. CBPR has a long and rich history in fields like HIV, but its role in medical education is still nascent.3 CBPR allows for patient and community engagement at all levels of research design and study, and important lessons can be transferred to curriculum design, development, and evaluation. It is important to remain critical and reflective on the nature of such endeavors, however, to ensure that as institutions and providers we are avoiding reproducing power differentials and inequities in our very attempts to address these concerns at the societal level. Critical theoretical perspectives may be employed to help educators “see” differently, uncovering how undertakings like addressing the SDOH or engaging patients can succumb to problematic patterns like tokenism, and providing ways to avoid such pitfalls.4 We thank the author, and we are pleased to be continuing this dialogue. Malika Sharma, MD, MEdMedical director, Casey House, Toronto, Ontario, Canada; [email protected] Andrew Pinto, MD, MScAssistant professor, Department of Family and Community Medicine, Faculty of Medicine and Dalla Lana School of Public Health, University of Toronto, and clinician–scientist, Centre for Urban Health Solutions, Li Ka Shing Knowledge Institute, St. Michael’s Hospital, Toronto, Ontario, Canada. Arno K. Kumagai, MDProfessor and vice chair of education, Department of Medicine, University of Toronto, and FM Hill Chair in Humanism Education, Women’s College Hospital, University of Toronto, Toronto, Ontario, Canada.
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 | 0.006 | 0.067 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.031 | 0.056 |
| Insufficient payload (model declined to judge) | 0.010 | 0.008 |
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".