Evaluation of a Media Training Workshop for Nutrition Students and Trainees in Nova Scotia
Bibliographic record
Abstract
Gaps in communication training have been identified in Canadian and international academic and practicum dietetics programs. A workshop was developed to pilot supplementary media training to nutrition students/trainees studying in Nova Scotia. Students, interns, and faculty from two universities participated in the workshop. Data on perceived learning, media knowledge/skill use, and workshop feedback were collected immediately post-workshop using a mixed-form questionnaire. A modified questionnaire was administered eight months post-workshop to obtain information on utility of the perceived acquired knowledge/skills. Closed-ended responses underwent descriptive analysis, while open-ended responses underwent thematic analysis. Twenty-eight participants completed the questionnaire post-workshop, and six completed it at follow-up. All participants rated the workshop positively (7-point Likert scale) and reported learning something new (perceived). Perceived learning emphasized general media knowledge/skills and communication skills. Follow-up data suggested participants had applied perceived media knowledge/skills in message development and media and job interviews. These data suggest that nutrition students/trainees may benefit from supplementary communications and media training and provide a stimulus for ongoing curriculum review and discussion.
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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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".