Examining the impact of health research facilitated by small peer-reviewed research operating grants in a women's and children's health centre
Bibliographic record
Abstract
BACKGROUND: There has been limited research on the impact of research funding for small, institutional grants. The IWK Health Centre, a children and women's hospital in Maritime Canada, provides small amounts (up to $15,000) of research funding for staff and trainees at all levels of experience through its Research Operating Grants. These grants are rigorously peer-reviewed. To evaluate the impact of these grants, an assessment was completed of several different areas of impact. FINDINGS: An online questionnaire was sent to 64 Principal Investigators and Co-Investigators from Research Operating Grants awarded from 2004 to 2006. The questionnaire was designed to assess five areas of potential impact: (1) research, (2) policy, (3) practice, (4) society and (5) personal. Research impact reported by participants included publications (72%), presentations (82%) and knowledge transfer beyond the traditional formats (51%). Practice impact was reported by 67% of participants, policy impact by 15% and societal impact by 18%. All participants reported personal impact. CONCLUSIONS: Small research grants yield similar impacts to relatively large research grants. Regardless of the total amount of research funds awarded, rigorously peer-reviewed research projects have the potential for significant impact at the level of knowledge transfer and changes in clinical practice and policy. Additional findings in the present research indicate that small awards have the potential to have significant impact on the individual grant holder across a variety of capacity building variables. These personal impacts are particularly noteworthy in the context of developing the research programs of novice researchers.
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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 | 0.080 | 0.188 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".