Brain development, mental health and addiction: a podcast series for undergraduate medical education
Bibliographic record
Abstract
Purpose – The purpose of this paper is to describe the process of developing the early brain and biological development and addictions podcast series for first and second year medical students. This paper also presents the findings from an evaluation of the introductory podcast in this series of 13 podcasts. Design/methodology/approach – Three focus groups were held with a total of 19 participants representing ten universities across Canada as well as one college and one foundation. Each focus group was audiotaped and then transcribed verbatim. The coding process consisted of grouping the common codes together to form themes based on the W(e)Learn framework. Findings – Findings suggested that most participants were enthusiastic regarding the potential of the podcast project not only for the intended audience but also for all medical students and residents as well as continuous healthcare education. However, findings also suggest that other participants were not as fervent about the potential of the program. Many participants provided suggestions for how to further improve the podcast. These suggestions have already been implemented into the program design in an attempt to meet end-users' needs and expectations. Originality/value – This research shares an innovative approach to supporting healthcare education in undergraduate education. Podcasting has become a cost-effective and convenient pedagogical tool for distributing educational information. Podcasts are effective teaching tools since listening is an active, engaging and creative process on interpreting content and creating meaning from auditory cues.
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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 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.015 | 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".