Senior dental students reflective activities involving community-service learning
Bibliographic record
Abstract
Abstract Objective Community service-learning (CSL) placements engage with equity-deserving groups. They receive oral health care and students can critically reflect on their experiences. This study aimed to thematically explore the reflections of senior dental students providing oral health services to equity-deserving communities in British Columbia, Canada. Methods Semi-structured written reflections were collected cross-sectionally from three consecutive graduating cohorts of fourth-year dental students (2022–23, 2023–24, and 2024–25). Reflections were a mandatory component of a community placement course, were approximately 500 words in length, and were prompted as follows: “Describe your personal experience at the assigned community clinic, noting moments of revelation, valuable learning, and/or disappointment for you.” An exploratory thematic analysis was conducted using an iterative coding process to identify and interpret categories and themes. Results From all the three years, 764 reflections were collected (191-625 words each) from 171 students. Of these, 124 reflections were excluded because they consisted solely of descriptions of procedures. Data saturation was reached after in-depth analysis of 205 reflections, yielding four overarching themes, including ‘learning across differences’; and ‘pause-breathe-refine’. These themes were informed by categories highlighting that detrimental impact of overly controlling mentorship styles and observation-only experiences on students’ learning. Conclusion Transformative experiences were observed, while students also reflected on less positive practices. Students emphasized the importance of CSL placements for their education, professional growth, and understanding of underserved populations, while also highlighting implementation challenges. Future research should examine the long-term impact of CSL activities once these challenges are addressed.
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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 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.001 | 0.002 |
| 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".