The Diffusion and Adoption of Advanced Technologies in Canada: An Overview of the Issues
Bibliographic record
Abstract
The adoption of advanced technologies is a means of fostering productivity improvement. Many theories seek to explain the process of advanced technology diffusion and adoption. Canadian firms generally trail their U.S. counterparts in the adoption of advanced technology. There are many critical gaps in our knowledge and understanding of technological diffusion in Canada. Key gaps include the identification of leading and lagging industries in terms of adoption; key barriers to technological diffusion in Canada including economic-policy-related barriers; appropriate direct policy interventions to overcome specific barriers; the impact of increasing globalization and the economic ascendancy of the large developing countries on diffusion in Canada; and specific challenges small and medium enterprises face in adopting technology. Another issue requiring more research is whether strong R&D performance is a prerequisite for the broad diffusion of technologies. Possible tradeoffs between supporting R&D and supporting diffusion in the presence of limited public funds to promote innovation merit discussion.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.022 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 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".