Pro Bono Services in 4 Health Care Professions: A Discussion of Exemplars
Bibliographic record
Abstract
OBJECTIVE: The purpose of this article is to discuss exemplars of pro bono and charity activities in health care professions. METHODS: We searched PubMed and Google Scholar from inception to August 2019 using search terms "pro bono healthcare," "medical volunteerism," "pro bono clinics OR free clinics OR organizations," "pro bono curriculum OR education," "underserved OR uninsured OR underinsured OR disadvantaged OR poor populations." Inclusion criteria were that practitioners, students, or volunteers be involved in pro bono care or education and in any discipline, including medicine, physical therapy, chiropractic, or dentistry. RESULTS: We selected 5 exemplars to review, and determined that students can benefit from participation in pro bono or charity health care such as through a student administered clinic model. Academic curricula can play a role in building confidence and create positive attitudes and behaviors regarding pro bono and charity activities, and nonprofit organizations can help build sustainable models. CONCLUSION: We conclude that the implementation and delivery of health care pro bono or charity services can fill a health care gap and can be applied successfully in the health professions.
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How this classification was reachedexpand
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 | 0.007 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.008 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".