Role of Non-Government Organizations in Engaging Medical Students in Research
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The continued decline in medical trainees entering the workforce as clinician-scientists has elevated the need to engage medical students in research. While past studies have shown early exposure to generate interest among medical students for research and academic careers, financial constraints have limited the number of such formal research training programs. In light of recent government budget cuts to support research training for medical students, non-government organizations (NGOs) may play a progressively larger role in supporting the development of clinician-scientists. Since 2005, the Mach-Gaensslen Foundation has sponsored 621 Canadian medical student research projects, which represents the largest longitudinal data set of Canadian medical students engaged in research. We present the results of the pre- and post-research studentship questionnaires, program evaluation survey and the 5-year and 10-year follow-up questionnaires of past recipients. This paper provides insight into the role of NGOs as stakeholders in the training of clinician-scientists and evaluates the impact of such programs on the attitudes and career trajectory of medical students. While the problem of too few physicians entering academic and research-oriented careers continues to grow, alternative-funding strategies from NGOs may prove to be an effective approach in developing and maintaining medical student interest in research.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.020 | 0.351 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 it