Proximity, distance and diversity : issues on economic interation [i.e. interaction] and local development
Bibliographic record
Abstract
Contents: Setting The Stage: Proximity, external relations, and local economic development, Arnoud Lagendijk and PAivi Oinas. 'Localization': Clusters, Industrial Districts, And All That - Evidence and Qualifications: Cultural industry cluster building in Sweden, Dominic Power and Daniel Hallencreutz Industrial districts in a transitional economy: the case of Datang Sock and stocking industry in Zhejiang, China, Jici Wang, Huasheng Zhu and Xin Tong Ethnic entrepreneurship and embeddedness: the case of lower Galilee, Michael Sofer and Izhak Schnell Networking and project organization in the Styrian automotive industry, Franz TA dtling and Michaela Trippl. Establishing External Relations: the Search for Specialized or Diverse Competences?: Supplier search in industrial clusters: Sheffield metal working in the 1990s, H. Doug Watts, Andrew M. Wood and Perry Wardle Regional clusters building on local and non-local relationships: a European comparison, Arne Isaksen The evolution of regional packaging machinery clusters in Germany, Ivo MoAYig Glob@lizing the network economy: local advantage for high-technology development, Wen-Cheng Wang Collaboration, innovation and regional networks: evidence from the medical biotechnology industry of Greater Vancouver, Kevin Rees. Economic Interaction On Multiple Scales: The process of innovation in contrasting industrial environments, AsbjA,rn Karlsen and Bjarne LindelA,v Globalization and the dynamics of local embeddedness in the South Hampshire electronics industry, Michael Taylor Mobility versus embeddedness: the role of proximity in major capital projects, Neil Alderman Variety of enterprise adaptation strategies in the emerging post-Socialist governance in Vyborg, Riitta Kosonen. Adding Value: Towards understanding proximity, distance and diversity in economic interaction and local development, PAivi Oinas and Arnoud Lagendijk Index.
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.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.005 | 0.021 |
| Scholarly communication | 0.014 | 0.009 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".