Are trade fairs relevant for local innovation knowledge networks? Evidence from Shanghai equipment manufacturing
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
The role of trade fairs in local innovation knowledge networks is studied by combining data on co-patenting networks in the Shanghai equipment manufacturing (machinery) industry with data from the Shanghai Metalworking and CNC Machine Tool Show (MWCS). Three propositions are developed, suggesting that: (1) local firms attending the MWCS are more research and development intensive than other firms; (2) trade fair attendees are linked with each other more closely in co-patenting networks than non-attendees; and (3) participating firms have more local co-patenting linkages than non-participating firms. The results largely support these propositions, confirming that participation in flagship fairs is associated with strong integration in innovation knowledge networks.
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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 | 0.000 |
| 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