Regional development in sparsely populated areas: The case of Quebec's missing maritime cluster
Bibliographic record
Abstract
The cluster concept has become very popular as a guiding principle for regional development policies. The objective of these policies is usually to support the local job market, and the way this is accomplished is by promoting industrial competitiveness and innovation in local firms. It is believed that policies based on the promotion of industrial clusters will achieve this. However, the formation of clusters requires certain conditions--not least of which are proximity between actors and a certain critical mass--that cannot be met in all regions. In some cases there is a cluster rhetoric that is not reflected in reality. In this article, we set out to examine how the cluster concept has been applied by regional policy makers in Quebec's coastal region. We examine whether certain basic preconditions of cluster formation are met, and whether any particular regional dynamism can be identified for the sectors targeted by this policy. We conclude that there may exist a maritime cluster in and around Rimouski (a regional hub) but that there is no evidence of cluster dynamics leading to regional growth throughout the area covered by the cluster policy.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".