Bibliographic record
Abstract
Innovation is increasingly considered a prerequisite for regional development and it is commonly understood that certain regions are more conducive to innovation than others. Regions that do not possess the required institutional and cultural contexts are often encouraged to work on creating them. However, there is increasing evidence that innovation is also a spatial phenomenon: the propensity of establishments to innovate also varies with their location relative to major and minor metropolitan areas, independent of local context. This article investigates whether the geography of innovation is similar for three different types of manufacturing sectors (high‐tech (HT), medium‐tech,first and second transformation) and across two different types of innovation (product, process). It is shown that, in Québec, to the extent that geography and innovation are connected, it is principally distance from a metropolitan area that plays a role. Our results lend support to McCann's (2007) recent spatial model of innovation and are also compatible with Duranton and Puga's (2003) theory of nursery cities. Our results also show that HT innovators behave differently from other manufacturers, with a tendency to internalize their innovation behaviour (perhaps out of necessity or for reasons of secrecy) in more distant locations.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.007 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".