Innovation System Effects on Technological Adoption in a Regional Value Chain
Why this work is in the frame
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Bibliographic record
Abstract
This paper examines the technology adoption rates of a sample of enterprises that are nominally members of the transportation equipment value chain. We utilize the regional innovation system (RIS) concept to identify and test key regional and corporate influences on technology adoption. Using data collected from a detailed survey instrument, our analysis considers adoption rates during the very period in which production equipment technologies are known to have grown very suddenly, i.e. the fourth quarter of 1994. Our findings indicate that the most important RIS factors are related to worker training and information spillover effects between proximate firms. In the main, our findings are supportive of policies that work indirectly through the market structure of regional economies and a firm's value-chain, as opposed to directly through regional technology agencies.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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 it