Social foundations of regional innovation and the role of university spin-offs: The case of Canada's technology triangle
Bibliographic record
Abstract
offs Abstract (ca. 235 words): Drawing from the literature on the role of universities in promoting technology transfer, this paper will develop a regional conceptualization of spin-off processes, and apply it to a regional case study. In doing this, a typology of spin-off firms will be explored, which is based on the following variables: university sponsorship, university involvement in firm formation, character of knowledge applied, and co-localization of the founders. This enables us to analyze the wider impact of universities on technology transfer and regional development. Extending propositions of organizational ecology, we argue that start-up processes and intra-firm adaptations are not competing against one another for superiority in regional growth or selection processes. The argument is developed that new and existing firms can complement one another in a regional context if they succeed in both developing wider regional networks and trans-regional linkages. Our study will focus on the Kitchener and Guelph metropolitan areas about 100 km west of Toronto, sometimes referred to as Canada’s Technology Triangle (CTT), where a larger number of firms related to information technology (IT) have been successfully launched since the 1970s around the activities of the University of Waterloo. This research will investigate
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".