Response to “Education Solutions to the Medical-Dental Divide.” A Novel Approach to Creating Unifying Organizational Cultures in Medicine and Dentistry
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
We appreciate the perspective presented in Rasmussen and colleagues' "Education Solutions to the Medical-Dental Divide" and the call for "purposeful educational unity" between medicine and dentistry.In addition to educational reform, unifying the fields 1 requires changes to organizational culture (OC), which includes shared assumptions, beliefs, and values.Overcoming organizational separation also requires investment in interprofessional education (IPE), such that IPE does not become "something I did once in graduate school."Implementing IPE requires diverse groups of professionals to collaborate, support, contradict, and adjust in the face of omnipresent complexity and uncertainty.Successful collaboration requires competence-trust and openness-trust within organizations. 2 A novel solution we propose is the use of improvisational (improv) theater techniques, which have been conventionally used to create unscripted performances.Medical improv is the application of improv techniques to improve communication and collaboration in the health professions. 3Medical improv has been used to teach interprofessional students empathy and develop personal and social competencies in a dynamic and practical way, and students have reported its positive impact on their capacity to cultivate quality interprofessional relationships. 4 Within the business literature, teaching agreement and collaboration through improv games has been used to foster an OC of effective communication and team building. 5dical improv is a promising solution to the medical-dental educational divide, and training curricula could be developed for students, faculty, and staff as a way to start changing OC by focusing on fostering collaborations within a safe learning and working environment.If we fail to address OC, it might take another 182 years to achieve educational unity between medicine and dentistry.
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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 | 0.020 | 0.050 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.009 |
| 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