Comparing the innovation performance in Canadian, French and German manufacturing enterprises
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This paper compares pairwise the innovation performance of Canada with France and Germany, respectively. The comparison is based on two ordered probit models with sample selection, one where innovation is measured by the introduction of new-to-the firm products and one where it is measured by the introduction of new-to-the market products. The econometric analysis attempts to explain part of the country differences as the result of the sectoral composition of output, and the effects of size, environment conditions (proximity to basic research and competition) and innovation activities (internal R&D, the number of innovation activities, cooperation and government support). The Canadian firms benefit from being larger and more numerous in receiving government support, but suffer from a lack of competition and internal R&D. These structural effects combined, while informative, are not enough to explain a lot of the basic pattern of innovation revealed by the raw data. If we take the stronger measure of first-to-market innovation as a yardstick of innovation, the observed pairwise country differences are less strong, and our model explains a little bit more of the observed differences.
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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 | 0.001 | 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 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it