Exploring medically-related Canadian summer student research programs: a National Cross-sectional Survey Study
Bibliographic record
Abstract
BACKGROUND: Summer student research programs (SSRPs) serve to generate student interest in research and a clinician-scientist career path. This study sought to understand the composition of existing medically-related Canadian SSRPs, describe the current selection, education and evaluation practices and highlight opportunities for improvement. METHODS: A cross-sectional survey study among English-language-based medically-related Canadian SSRPs for undergraduate and medical students was conducted. Programs were systematically identified through academic and/or institutional websites. The survey, administered between June-August 2016, collected information on program demographics, competition, selection, student experience, and program self-evaluation. RESULTS: Forty-six of 91 (50.5%) identified programs responded. These SSRPs collectively offered 1842 positions with a mean 3.76 applicants per placement. Most programs (78.3%, n = 36/46) required students to independently secure a research supervisor. A formal curriculum existed among 61.4% (n = 27/44) of programs. Few programs (5.9%, n = 2/34) offered an integrated clinical observership. Regarding evaluation, 11.4% (n = 5/44) of programs tracked subsequent research productivity and 27.5% (n = 11/40) conducted long-term impact assessments. CONCLUSIONS: Canadian SSRPs are highly competitive with the responsibility of selection primarily with the individual research supervisor rather than a centralized committee. Most programs offered students opportunities to develop both research and communication skills. Presently, the majority of programs do not have a sufficient evaluation component. These findings indicate that SSRPs may benefit from refinement of selection processes and more robust evaluation of their utility. To address this challenge, the authors describe a logic model that provides a set of core outcomes which can be applied as a framework to guide program evaluation of SSRPs.
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.
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 | 0.029 | 0.184 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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; both teacher heads agree on what is shown here.
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".