Improving the Canadian Institute for Health Research's (CIHR) grant applications: An analysis of the policies governing the funding process
Bibliographic record
Abstract
Objectives: This study seeks to examine the effectiveness of IdentificationAn online questionnaire composed of both MethodologyObjectives: This study seeks to examine the effectiveness of the CIHR policy reforms in obtaining their five objectives: to decrease application workload, to alleviate peer review IdentificationAn online questionnaire composed of both qualitative and quantitative questions was administered to health researchers in various Researchers identified through grant success and faculty position decrease application workload, to alleviate peer review burden, to improve peer review consistency, to adapt to the needs of scientific community and to reduce program Identification administered to health researchers in various disciplines.Eligibility criteria included the minimum submission of one grant application faculty position (n = 99).needs of scientific community and to reduce program complexity 1 .Methods: Health researchers in various disciplines were Recruitment minimum submission of one grant application to the CIHR in the last five years.Participants were recruited using convenience and Participants recruited through snowball and Methods: Health researchers in various disciplines were recruited and asked qualitative and quantitative questions via an online questionnaire.The data was analyzed using a Recruitment were recruited using convenience and snowball sampling.The data was analyzed by identifying the strengths, weaknesses, through snowball and convenience sampling (n= 22).via an online questionnaire.The data was analyzed using a SWOT approach and an exploratory policy analysis.Results : Strengths of the reforms include lightened Inclusion Participants excluded identifying the strengths, weaknesses, opportunities and threats of the CIHR grant application and funding process, as perceived Participants screened according to experience Results : Strengths of the reforms include lightened administrative burdens, clarity of application process, communication and the ease of application submission.Inclusion excluded (n = 5).
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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 | 0.343 | 0.478 |
| Meta-epidemiology (narrow) | 0.001 | 0.003 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.016 | 0.024 |
| Science and technology studies | 0.029 | 0.020 |
| Scholarly communication | 0.042 | 0.008 |
| Open science | 0.010 | 0.010 |
| Research integrity | 0.016 | 0.016 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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; the direct Gemma label and the distilled Codex classifier 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".