Rewarding Innovation: Improving Federal Tax Support for Business R&D in Canada
Bibliographic record
Abstract
Business innovation is viewed by many as a solution to Canada’s ailing productivity performance. One of the more troubling aspects of Canada’s innovation track record is that businesses spend relatively little on research and development (R&D) despite having access to some of the world’s most generous R&D tax incentives. Canada’s low levels of business R&D have called into question the effectiveness of Canada’s generous R&D tax incentives, particularly the flagship federal Scientific Research and Experimental Development (SR&ED) program. A deeper analysis, however, reveals that tax incentives are effective in stimulating more R&D – that is, Canada would have lower levels of business R&D in the absence of these inducements. Instead, the root cause of Canada’s business R&D deficit appears to stem from structural aspects of the economy and, more importantly, a lack of demand-related pressure to pursue innovation.
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 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 | 0.013 | 0.069 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.018 | 0.009 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.007 | 0.004 |
| Research integrity | 0.036 | 0.027 |
| 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; 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".