Innovative activity in Canadian food processing establishments: the importance of engineering practices
Bibliographic record
Abstract
This paper examines the factors contributing to innovative activity in the Canadian food-processing sector. Several factors relating to innovation are considered. Firstly, it focuses not only on the importance of research and development activity but also on advanced business practices used by production and engineering departments. Secondly, it examines the extent to which a larger firm size and less competition serve to stimulate competition - the so-called Schumpeterian hypothesis. Thirdly, the effect of the nationality of a firm on innovation is also investigated. Fourthly, industry effects are examined. The paper finds that business practices are significantly related to the probability that a firm is innovative. This is also the case for R&D. Size effects are significant, particularly for process innovations. Elsewhere, their effect is greatly diminished once business practices are included. Foreign ownership is significant only for process-only innovations. Competition matters, more so for product than for process innovations. Establishments in the "other" food products industry tend to lead the industry average when it comes to innovation, whereas fish product plants tend to lag behind the industry average.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".