Actors and sectors in technological innovation systems: patterns of knowledge development in the field of second generation biorefineries
Bibliographic record
Abstract
This paper investigates the relationships between a focal technological innovation system (TIS), its surrounding sectors, and other TISs, through a value chain perspective. We examine how firm actors from sectors with different value chain positioning contribute to the function of the knowledge development in an emerging TIS. By assigning patents to value chain steps in the context of second generation biorefinery technologies, our findings indicate that sectors differ in their knowledge generation patterns in the focal TIS, and that multiple sectors can contribute to knowledge development along the whole TIS value chain. We also differentiate four types of TIS actors based on the way they develop new knowledge to approach the focal TIS: (1) actors from existing sectors that directly enter the focal TIS; (2) diversifying actors that enter the focal TIS but also its adjacent TISs; (3) actors dedicated to the innovation niche; and (4) actors that emerge and operate solely in the focal TIS.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".