REGIONAL INNOVATION SYSTEMS IN THE PERIPHERY: THE CASE OF THE BEAUCE IN QUÉBEC (CANADA)
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
All too often, innovation research emphasizes core regions exemplifying successful innovation systems or "learning regions" such as, Silicon Valley, Route 128, Emilia-Romagna and Baden-Württemberg. However, lessons learned from these regions are seldom applicable elsewhere, in particular to territories where actors strategic to the innovation process are less diversified. The regional innovation system (RIS) in peripheral regions, and the likelihood of their acting as conduits for the innovation system, have seldom been the subjects of discussion. The objective of this paper is to study the way in which innovation occurs, including an investigation of actual innovation activities and capabilities of firms located in a peripheral area, and specific factors affecting their innovation activities. The discussion draws its empirical substance from the case of the Beauce in Québec (Canada). A survey of 45 SMEs was conducted in order to get a better understanding of the key dimensions of innovation activities.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it