<i>Perceived Roles, Benefits, and Supports</i>For Dietetic Internship Preceptors
Bibliographic record
Abstract
Evaluation of university-run dietetic internship programs will improve preceptors' experience and, ultimately, increase the capacity for training future dietitians. We attempted to identify preceptors' perceptions of their roles, benefits, and supports, as well as of the skills/traits that students need for internship, and suggested improvements for the internship program. Fifteen of 39 current program preceptors who had supervised more than one intern consented to participate in an ethics-approved research methodology. They responded anonymously to a series of questions posted in an online discussion group, and provided feedback on the subsequent reports. While no consensus emerged, more than 50% of participants perceived their role as providing a supportive learning experience for interns. Benefits noted most frequently were personal academic growth and contributions to their organizations from intern research projects. Effective supports included conventional communication methods and website materials. Participants identified self-motivation, independence, and communication skills as most important for interns. They also provided several suggestions for program improvements. The study methods and results could be helpful to other university-run internship programs seeking improvement and growth.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".