MEDTalks: a student-driven program to enhance undergraduate student understanding and interest in medical schools in Canada
Bibliographic record
Abstract
Given the lack of programs geared towards educating undergraduate students regarding medical school, the purpose of this study was to evaluate whether medical student-driven initiative program, MEDTalks, enhanced undergraduate student understanding of medical school in Canada and stimulated interest in pursuing medicine. The MEDTalks program that ran between January and April 2018 in the University of Ottawa consisted of 5 teaching sessions, each including large-group lectures, small group case-based learning, physical skills tutorials, and anatomy lab demonstrations, to mimic the typical Medical School curriculum. At the end of the program, undergraduate student learners were invited to complete a feedback questionnaire. Twenty-nine participants provided feedback. Twenty-five reported that MEDTalks allowed them to gain exposure to the University of Ottawa Medical Program; 27 said that it gave them a greater understanding of the teaching structure; and 25 responded that it increased their interest in attending medical school. The MEDTalks program successfully developed greater understanding of medical school and helped stimulate interest in pursuing medical studies in undergraduate students.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".