Tapping into agglomeration benefits by engaging in a community of practice
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
While a great deal is known in the agglomeration literature regarding the importance of having access to Marshallian externalities for firm performance, less is known about how geographically isolated and remote firms fare with the lack of such access. More recent literature suggests that firms, especially those within geographic proximity, can form a community of practice to facilitate deliberate learning and collectively create a shared repertoire, that is, a set of communal knowledge of procedures, techniques, and standards for best practices. Unlike Marshallian externalities, however, community of practice membership is not necessarily bounded by geography, and as such, isolated firms can also engage in a community of practice and unlock the shared repertoire for their own benefits. The study of the Ontario wine industry (1999–2009) finds that community of practice engagement weakens the detrimental impact of geographic isolation on firm performance, suggesting that isolated firms can tap into agglomeration benefits by engaging in a community of practice.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| 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