Knowledge networks and dynamic capabilities as the new regional policy milieu. A social network analysis of the Campania biotechnology community in southern Italy
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
A new definition of regional milieu is emerging from the recent innovation policy framework inspired by the notion of a ‘knowledge economy’. It is grounded in a theoretical context where the emphasis is on the interactive character of innovation, involving the sharing and exchange of different forms of knowledge among the actors. Identifying regional positioning within the global knowledge value chain is a current preoccupation of both policy and empirical research. This study tries to measure the degree of involvement of a (follower) regional community of biotechnology actors in the global knowledge value chain. It applies inductive research and exploratory case studies to analyse local relational behaviour within the knowledge network (KN) structure. Our description of a regional bio-community highlights the distinctiveness of regional knowledge in relation to the distribution of KN capabilities. The critical nodes in the KN structure are the intra-regional actors, represented by public basic research organizations. These actors bridge between local basic research groups and the international scientific community, although the ability of local actors to collaborate can affect the strength of the links among them. This aspect, which is not addressed by regional strategies, should be the focus of new regional policies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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