Undergraduate geriatric education through community service learning
Bibliographic record
Abstract
INTRODUCTION: Despite the exponential growth of the elderly population worldwide, geriatric education has been a formal component of only a few dental schools' curricula. OBJECTIVE: To describe the geriatric community service learning (CSL) component of the professionalism and community service (PACS) module, and to explore a CSL project carried out by a group of first year dental students at a long-term care facility. METHODS: A literature review was performed to present and describe the CSL component of the PACS module. Students' personal reflections were used to illustrate some of the joys and challenges of experiencing a long-term care facility environment. RESULTS: The newly developed PACS module combines community service learning with the long-term care experience. Students develop, apply and evaluate an educational health promotion activity in a long-term care facility. CONCLUSIONS: The PACS module has encouraged students to acquire comprehensive knowledge and awareness of the needs and dynamics of a long-term care as they collaboratively interacted with personnel from the facility to develop their projects. The authors would like to engage other schools in discussing the need to integrate community-based geriatric education into their dental curricula.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 0.003 |
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".