Brewing better connections: Coffee with the dean to enhance admin‐student communication
Bibliographic record
Abstract
Effective communication is pivotal in nurturing a supportive learning atmosphere. At the University of Saskatchewan's College of Dentistry, traditional methods like emails and meetings seemed inadequate in engaging all students. Concerns stemmed from power dynamics and limited dialogue avenues. To bridge this gap, an innovative solution emerged. Introducing "Coffee with the Dean": A bi-weekly event fostering informal discussions between students and the dean. Set in a relaxed ambiance, students openly covered diverse topics. The project aimed to foster transparent communication and bolster a sense of unity. Implemented over six months, the initiative saw significant outcomes. Assessment involved an anonymous survey to DMD students, garnering a 34% response rate. Impressively, 89% acknowledged enhanced communication, with 53% and 23% expressing high and moderate satisfaction in asking questions and providing feedback. Moreover, 67% displayed a likelihood to attend future sessions. A notable 89% appreciated the project's community-building impact. Although challenges emerged, including scheduling and participation constraints, the project achieved its goal. The casual setup facilitated student expression and prompted insightful exchanges. The experience emphasizes the importance of secure dialogue spaces and consistent communication channels. "Coffee with the Dean" stands as a potent tool for heightened student-administration interaction. Its role in elevating communication aligns with the quest for educational excellence, ensuring holistic student 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 | 0.010 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.004 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.022 | 0.006 |
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".