Entrepreneurship, knowledge and learning in cluster formation and evolution: the Windsor Ontario tool, die and mould cluster
Bibliographic record
Abstract
In this paper, we examine the role of entrepreneurs in the development of the Windsor, Ontario automotive Tool, Die and Mould (TDM) cluster. We assess Feldman et al.'s stage model of entrepreneurial-led cluster formation and their contention that entrepreneurs may be the active creators of institutions of cluster development. We concur with their basic thesis but argue that Feldman et al. do not address the role of tacit and codified knowledge in cluster development and the challenges posed by power asymmetries arising from the development of larger firms within the cluster and its integration into TNC 'knowledge pipelines'. A significant aspect of the current crisis in the Windsor TDM cluster is how tacit and codified knowledge is being recombined in ways favouring larger firms within the cluster. Larger firms have developed stronger associational relationships to protect their intellectual property, threatening to reduce tacit knowledge flows within the cluster.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| 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".