A classroom exercise for improving mentor/mentee relationships
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Responsible Conduct of Research (RCR) courses seek to heighten awareness of the importance of mentor/mentee interactions and other topics, but questions remain - e.g., how best to train mentors/mentees to establish such relationships. DESCRIPTION OF EXERCISE: This paper proposes an approach as a model to strengthen RCR education by more fully, and actively, rather than passively, engaging trainees. A classroom activity was developed that can enhance instructors' abilities to improve mentor/mentee interactions. The instructor divided classes into groups of roughly four trainees, and had them think of a good mentor they have observed, and to list traits/behaviors they liked. Groups then summarized discussions for the class. The instructors recorded and integrated responses. Each group then considered bad mentors, answering the same questions, and repeating the process regarding bad mentees and good mentees. The class then compared the four discussions. Trainees have commonly had both formal and informal mentors, seen both good and bad mentors and mentees, and often themselves served as mentors. Mentees thus connect abstract principles concerning mentorship to personal experiences; and reflect on their own interactions/roles, preferences, and rights/responsibilities. CONCLUSION: This exercise suggests some benefits of recognizing personal/emotional, not just intellectual components in RCR, and has important implications for education, practice, and research.
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Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | Metaresearch Domain: Incentives · Genre: Methods About the Canadian research system: no · About a Canadian topic: no | Not applicable | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Other design | low |
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it