Bibliographic record
Abstract
Here at JCIPE, another semester has flown by. And again, the Center has been busy expanding and integrating our programs on campus and beyond. This fall, as we welcomed our tenth cohort into the Jefferson Health Mentors Program, we introduced a revised curriculum which is more heavily focused on the social determinants of health and integrates the Social Ecological Model. We also added an eighth profession, Medical Laboratory Sciences, to the mix, expanding our total student enrollment to more than 1400 students! Building on this foundation, this fall we also expanded our more advanced interprofessional TeamSTEPPS® training program. During the course of four workshops, the Center and 16 volunteer interprofessional facilitators from four different professions led 554 students from five professions through simulated case scenarios through which they applied their TeamSTEPPS® skills. Though reportedly pushed outside their comfort zones, students described learning valuable lessons about teamwork, effective communication, leadership, experiential learning and the value of working with other professions. They also reported feeling better prepared for clinicals and “real-world” scenarios. Check out some student feedback in this edition! As many of you know from having joined us, we hosted our fifth biennial conference on October 28 and 29. One hundred seventy attendees hailed from Canada, Israel and 27 different states. Our keynotes addressed issues of global interprofessional education and practice; the history of Medicare and its impact on our ability to deliver patient-centered, interprofessional care; and the importance of teams in maximizing value in healthcare. A range of oral and poster presentations showcased the advancement of interprofessional education and practice, with innovative pilots becoming integrated with more depth and breadth. Along the lines of this theme, the Journal of Interprofessional Education & Practice (JIEP) plans to publish a special conference edition this spring featuring works from the conference and John H. V. Gilbert, C.M., Ph.D., LLD (Dalhousie), FCAHS as guest editor. Finally, many congratulations to Deirdre Yarosh, MA, a Jefferson Pharmacy student, who received JIEP’s Student Award for her peer paper presentation “Examining Health Mentor Perceptions of Student Teamwork.”
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 | 0.002 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.456 | 0.370 |
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".