The impacts of research grants to community colleges. Evidence from the Technological Research Assistance Program in Quebec, Canada
Bibliographic record
Abstract
This article presents the findings of a study on the effects of the Technological Research Assistance Program (TRAP) on the primary activities of Quebec’s College Technology Transfer Centres (CTTCs). A database on the distribution of research grants and the activities of CTTCs has been created for this purpose. Then, panel data analysis techniques have been used to measure the effects of TRAP. The study results indicate that TRAP has a positive effect on the revenue of CTTC research projects. However, the increase in research revenue due to this program is slightly lower than the amount of the grant, which suggests that public funding for research partially crowds out private funding. Furthermore, the study suggests that the wise use of research assistance programs could stimulate research investment and, as a result, accelerate the advancement of knowledge and technological innovation.
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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 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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; 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".