An interprofessional socialization framework for developing an interprofessional identity among health professions students
Bibliographic record
Abstract
Although health professional educational programs have been successful in equipping graduates with skills, knowledge and professionalism, the emphasis on specialization and profession-specific education has enhanced the development of a uniprofessional identity, which has been found to be a major barrier to interprofessional collaborative person-centred practice (IPCPCP). Changes within healthcare professional education programs are necessary to enable a shift in direction toward interprofessional socialization (IPS) to promote IPCPCP. Currently, there is a paucity of conceptual frameworks to guide IPS. In this article, we present a framework designed to help illuminate an IPS process, which may inform efforts by educators and curriculum developers to facilitate the development of health professions students' dual identity, that is, an interprofessional identity in addition to their existing professional identity, as a first step toward IPCPCP. This framework integrates concepts derived from social identity theory and intergroup contact theory into a dual identity model of IPS.
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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 | 0.007 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.008 | 0.019 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".