Bibliographic record
Abstract
We thank our colleagues from the University of British Columbia (UBC) and the University of Toronto for engaging with our article “Beyond the Lamppost: A Proposal for a Fourth Wave of Education for Collaboration.”1 We are grateful for Nasmith and colleagues’ letter, which provides information about types of interprofessional collaboration and education that are currently happening at UBC. This pioneering work is clearly more institutionally stable than the historical activities we reviewed in our article. We used the case of UBC to illustrate the underpinning logic behind interprofessional education (IPE) in the 1960s and early 1970s, which we called “the first wave.” Contemporary models, rhetoric, and practices have certainly evolved; a contemporary case study would be valuable, and we encourage the authors to conduct one. We agree with Tassone and colleagues that the focus of our article was on undergraduate IPE, and indeed we were very explicit that we targeted IPE’s large-scale, undergraduate forms with our comments. We used the example of the University of Toronto’s Centre for Interprofessional Education not to criticize how it implements IPE but, rather, to illustrate a very specific point: that the coordination efforts of large-scale IPE interventions are intense, intricate, and … unavoidable. Our colleagues’ description of the large array of activities they coordinate furthers our argument. We acknowledge that our piece focused only on certain activities of the Centre, which unto themselves are extremely complicated to organize. The added layers of complexity articulated by our colleagues support our point: The logistics of such a curriculum are immense and commendable. We want to conclude by noting that we sincerely regret if our comments about the wizardry of IPE were read as dismissive of our colleagues who administer and run the very programs that make academic medicine possible—in this case, IPE events. We rely on immensely capable staff whose work we admire and respect, and without whom we wouldn’t be able to have the academic careers that we do. The aim of the wizardry metaphor was to celebrate the magic that staff make happen while we, as academics, are given space to reflect and write about the programs that we often—let us be honest—impose onto them without sufficiently seeking their insights and advice. We recognize research as one of several important aspects of academic medicine, and are immensely indebted to the staff that continue to choose to work with us on educational activities and on research. Elise Paradis, MA, PhDAssistant professor, Leslie Dan Faculty of Pharmacy, Department of Anesthesia, and Department of Sociology, University of Toronto, and scientist, Wilson Centre, Toronto, Ontario, Canada; [email protected] Cynthia R. Whitehead, MD, PhDAssociate professor, Department of Community and Family Medicine, University of Toronto, director and scientist, Wilson Centre, and vice president for education, Women’s College Hospital, 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 | 0.014 | 0.150 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.009 |
| Scholarly communication | 0.009 | 0.015 |
| Open science | 0.007 | 0.006 |
| Research integrity | 0.055 | 0.081 |
| Insufficient payload (model declined to judge) | 0.013 | 0.011 |
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".