Biotechnology Megacentres: Montreal and Toronto Regional Systems of Innovation
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
ABSTRACT Canada hosts two major diversified biotechnology regional systems of innovation in its two largest cities. Similar in many respects, they display some particular characteristics. We review here the main theories on regional innovation systems and innovative clusters and proceed to analyse these two regional systems before concluding on the usefulness of several theories to study biotechnology regional innovation systems. 1. Theory: From Clusters to Regional Innovation Systems The well-documented agglomeration of high-technology companies in a few geographical regions of each industrialized nation has received several competing explanations. Many authors, based on Alfred Marshall (1890) pioneering work in the late nineteenth century, argued that high-tech firms agglomerate around major pools of skilled labour; sometimes, these pools were initiated by the arrival of large foreign- or locally-owned multinational corporations in the region, such as Galway in Ireland, or Ottawa in Canada (OECD, 2001; Niosi, 2000). In other cases, regional higher education institutions were responsible for the development of such a labour pool. Another European tradition, based on the work of François Perroux (1982), underlined that many regional poles were created by the development of ‘engine industries ’ such as large
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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