A national survey on small research grants and the scholarly productivity of emergency medicine physicians in Canada
Bibliographic record
Abstract
Small research grants can provide a funding source for novice physician-scientists during residency or as junior investigators. However, it is unknown if emergency medicine (EM) grant recipients benefit beyond the immediate monetary infusion of these modest awards (<$5,000). To better understand the role of small grants in EM research, we evaluated the scholarly productivity of previous recipients of a Canadian Association of Emergency Physicians (CAEP) research grant and compared the portion of career researchers among the recipients to all certified Canadian EM physicians. A 27-question online survey was developed and distributed to the recipients to ask about their CAEP grant project and research career productivity. Of the 96 grant recipients, 56 completed the survey (58% response rate). Respondents reported a high rate of project completion (95%) and publication success. Many recipients (85%) held an academic appointment, and 47% had formal research positions. In Canada, 2.5% of all certified EM physicians (n = 3,699) and 9.5% of EM specialists (n = 978) are currently involved in research. CAEP grant recipients are 5-fold and nearly 20-fold more likely than the population of certified EM specialists or all certified EM physicians, respectively, to be involved in research. As there are few funding sources in Canada for small EM-related projects, the finding that a considerably great proportion of physicians who are funded by these small grants (versus the entire pool of EM-trained physicians) commit to research as part of their career suggests that the funds may be meaningful beyond both the monetary support and project completion. The results of our evaluation indicate that modest research grants can support physician-researchers early in their careers, and many of these researchers continue with future research success, including research appointments, funding, and scholarly publications.
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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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.007 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".