Bibliographic record
Abstract
Proximity relations - elements for an analytical framework, Jean-Pierre Gilly and Andre Torre innovation and proximity - theoretical perspectives, Leon A.G. Oerlemans et al accessibility versus proximity in production networks, Antje Burmeister industrial districts and social capital, Rod B. McNaughton industrial districts - measuring local linkages, Boyoung Lee et al micro business networks in rural Canada - the case of peer lending and micro credit circles, David Bruce and Roger Wehrell organizational clusters in a resource-based industry - empirical evidence from New Zealand, Michele E.M. Akoorie in the flagships' wake - relations, motivations and observations of strategic alliance activity among IT sector flagship firms and their partners, Ben P. Cecil and Milford B. Green the role of external technological services in the innovation performance of small and medium-sized manufacturing firms, Alan D. MacPherson interfirm linkage patterns and the intrametropolitan location of producer services firms, Paul Sabourin.
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.022 | 0.002 |
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".