Evolving industrial districts and changing innovation patterns: the case of Montreal
Bibliographic record
Abstract
Purpose This paper aims to investigate the evolution of the phenomenon of industrial districts and explores the broader regional innovation systems that consist of multiple industrial districts. Design/methodology/approach This paper uses a combination of network analysis and patent analysis techniques to analyze the social structure of Montreal tech agglomeration and its innovation. Findings The findings indicate that the cores of modern regional innovation systems are composed of densely collaborating organizations belonging to different industrial clusters, and these organizations are responsible for the most radical innovations. The analysis also reveals the importance of brokers and international ties in generating radical innovations. Research limitations/implications The findings of our paper extend the initial concept of industrial district and call for the need to no longer focus exclusively on individual clusters, but to take into consideration broader competitive regional innovation systems that are composed of multiple clusters. The current trend of the core of such systems to be composed of organizations from multiple clusters indicates that the traditional understanding of industrial district confined to the borders of specific industry is no longer relevant and there is a need to revise the conceptualization of clusters and further analyze the social fabric of broader regional innovation systems. In future, such intense collaboration within the core of the regional innovation system network may give rise to new industrial and technological configurations. It is important to further investigate these structures, because they have important implications for innovation and are responsible for new innovation patterns. Practical implications To boost innovation in specific localities, policymakers could encourage collaboration between different clusters and support interdisciplinary projects and programs. Those would help the local community generate radical innovations. Social implications Using this research, local policymakers could help local companies understand and explore international markets, as well as focus on attracting multinational firms that are leaders in their respective fields. Finally, local policymakers could further support important cluster intermediaries Originality/value This paper offers original contributions to the studies of industrial districts as it explores a competitive ecosystem composed of multiple industrial districts and analyzes how these industrial districts interact and where the most innovative solutions lie in the social fabric of this big ecosystem.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".