INTERNATIONAL HEALTH EDUCATION: MOVING MEDICAL STUDENTS FROM PASSION TO SKILL.
Bibliographic record
Abstract
Background University of British Columbia medical students interested in international health are able to attend inspirational talks and/or join international volunteer electives with nongovernmental organizations (NGOs). However, within the university, there is a shortage of training to provide students with the skills needed to participate in international health, in particular the skills for sustainable and community based international health work. Methods In 2005, a group of students formed The UBC Medical and Dental Students9 International Health Initiative. With guidance from faculty instructors and NGOs (including Doctors Without Borders [MSF]), students started four components: skill-building workshops and three international health projects in Uganda, India, and Honduras. Workshops were designed to teach medical students the skills needed to make them effective international health workers. Projects provided opportunities for students to practice those skills, in planning, development, or implementation of the projects. All the international health projects strove to address an unmet community need, partner with a local organization in the designated country, and emphasize principles of sustainability. Results Workshops: Two skill-building workshops were held, each led by an MSF field-worker and featuring a case study based on their real-life experiences. Presenters discussed an approach to international health challenges, such as project planning and ethical decision making. Approximately 40 students from diverse faculties, including medicine, nursing, and science, attended each workshop. Workshops were rated 8.2/10 by students. Projects: Ten medical students were involved in initiating international health projects in Honduras, Uganda, and India. Projects included conducting needs assessments, working with local organizations, and delivering public health workshops. Students expressed appreciation of the value and synergy from collaborating with students and health care providers in the local community. Conclusions Student health professionals interested in international health care were very receptive to learning skills directly from NGOs9 field-workers to apply to community-based projects overseas. Students participating in the international projects were inspired and learned from firsthand experience. It is anticipated that the blend of theoretical and practical international health training for students will create skilled future international health workers and develop beneficial partnerships in global communities.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".