Bibliographic record
Abstract
This article focuses on the description of an educational initiative, the Interdisciplinary Population Health Project (IPHP) conducted in the academic year of 2006-2007 with a group of nursing and health care students. Inspired by population health, community development, critical pedagogy, and the inequalities imagination model, students participated in diverse educational activities to become immersed in the everyday life of an underserved urban neighborhood. A sample of convenience composed of 158 students was recruited from 4 health disciplines in a Western Canadian university. Data were collected using a modified version of the Parsell and Bligh's Readiness of Health Care Students for Interprofessional Learning Scale. A one group pretest-posttest design was used to assess the outcomes of the IPHP. Paired t tests and one-way analyses of variance were used to compare the responses of students from different academic programs to determine if there were differences across disciplines. Findings suggest that students' readiness to work in interprofessional teams did not significantly change over the course of their participation in the IPHP. However, the inequalities imagination model may be useful to enhance the quality and the effectiveness of fieldwork learning activities as a means of educating culturally and socially conscious nurses and other health care professionals of the future.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.018 | 0.038 |
| Scholarly communication | 0.021 | 0.019 |
| Open science | 0.002 | 0.023 |
| Research integrity | 0.005 | 0.011 |
| Insufficient payload (model declined to judge) | 0.013 | 0.004 |
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".