Innovating in less developed regions: What drives patenting in the lagging regions of Europe and North America
Bibliographic record
Abstract
Abstract Not all economically disadvantaged—“less developed” or “lagging”—regions are the same. They are, however, often bundled together for the purposes of innovation policy design and implementation. This paper attempts to determine whether such bundling is warranted by conducting a regional level investigation for Canada, the United States, on the one hand, and Europe, on the other, to (a) identify the structural and socioeconomic factors that drive patenting in the less developed regions of North America and Europe, respectively; and (b) explore how these factors differ between the two contexts. The empirical analysis, estimated using a mixed‐model approach, reveals that, while there are similarities between the drivers of innovation in North America's and Europe's lagging regions, a number of important differences between the two continents prevail. The analysis also indicates that the territorial processes of innovation in North America's and Europe's less developed regions are more similar to those of their more developed counterparts than to one another.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".