The mechanisms underlying the emergence of innovation ecosystems: the case of the AI ecosystem in Montreal
Why this work is in the frame
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Bibliographic record
Abstract
Scholars have increasingly been using ecosystem as a concept within and beyond social science, but less is known about how ecosystems emerge. In this study, we investigate the context of the Artificial Intelligence (AI) ecosystem in Montreal to understand the mechanisms underlying the emergence of innovation ecosystems. Building on the work of Ostrom and the literature on innovation commons and conducting content analysis and network analyses, we find empirical evidence for a bottom-up approach in the emergence of the AI ecosystem in Montreal. We find that the main mechanism underlying the emergence of innovation ecosystems in Montreal is the articulation of a series of innovation commons by commoners. Our findings have implications for understanding the importance of emerging technologies and the digitalization of industries and for identifying regional innovation capabilities.
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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 | 0.002 | 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 | 0.001 | 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