A Conscious Geography: the Role of Research Centers in the Coordination of Innovation Policy and Regional Economic Development in the US and Canada
Bibliographic record
Abstract
Through a comparison of how a "conscious geography"; has informed the organization of research centers in the US and Canada, this article contributes to the debate about the role of regions in the devolution of national science, technology, and innovation (STI) policy. A "conscious geography" refers to a policy framework in which the spatial distribution (and concentration) of innovation and/or production is explicitly considered. In both countries, Centers of Excellence, either based in, or affiliated with, universities, have become lynchpins of an evolving multi-scalar STI policy. \n \nThe geographic consciousness informing each set of institutional structures, however, varies significantly. Early evidence indicates that the Canadian model, which explicitly takes a geography of production and innovation into account, produces more positive policy outcomes than the US model which employs an ad hoc approach to space. The explicit consideration of the spatial distribution of production appears critical to multi-scalar collaboration, contributing to both horizontally-distributed networks across regions and between researchers and vertically-integrated networks within scales (e.g. the national and regional).
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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 | 0.007 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.011 | 0.017 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".