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
Over the past two decades there has been an international surge of analytical and policy interest in the `knowledge-based economy ' in which firms are engaged in the production and adoption of new technologies, and the innovation and reinnovation of industrial products and processes. Innovation by firms, across the range of technol-ogies from traditional to advanced, is conceived as part of a learning process, which may be incremental or reliant on new developments. Simultaneously, there has been a renewed interest in the geographical clustering of industrial firms in core regions and in major cities within them. This means there has been significant refocusing of research on how agglomeration economies and innovation sustain nodes of industrial activity. Industrial clusters, regional innovation systems, and industrial districts are the most common regional industrial models in use and though they tend to have different applications their developers have focused on bonds between firms and with other institutions within regions. The concept of globalization, however, recognizes the ease with which goods, capital, and ideas move at the international and interregional levels and there is a need to integrate this reality into models of industrial clustering by
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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