Innovation Policy Lab Working Paper 2023-01
Bibliographic record
Abstract
A growing literature argues that entrepreneurial ecosystems benefit from intermediary organizations which increase civic capital or connectivity among entrepreneurs, risk capital, knowledge-bearing institutions, sophisticated customers, and complementary service providers. These intermediary organizations, however, are seldom subjected to comparative analysis. Focusing on three regional innovation centres in Waterloo (Communitech), Toronto (MaRS), and Ottawa (OCRI, now Invest Ottawa), we find that all three organizations fostered greater connectivity within their communities, but that they did so in very different ways. Distinguishing among entrepreneur-led “community creators,” institution-led “buzz builders,” and anchor-led “cluster organizers,” we demonstrate how institutional origins and organizational design shape their programming choices and, by extension, the structure of civic capital. While the differences among Communitech, MaRS, and Invest Ottawa have narrowed over time, this analysis suggests that organizations seeking to improve connectivity in immature, entrepreneurial ecosystems face important tradeoffs.
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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 | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.006 | 0.003 |
| Insufficient payload (model declined to judge) | 0.328 | 0.105 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".