1 Innovation Networks and Gatekeepers of Canadian Biotechnology Clusters ±
Bibliographic record
Abstract
This paper studies the importance of collaboration networks for the innovation creation in Canadian biotechnology. Using information contained in 3550 biotechnology patents of 4569 inventors we construct Canadian biotechnology innovation network and describe the collaborative behaviour of the inventors. We find that most of the collaborative activity which involves Canadian inventors takes place inside biotechnology clusters. We examine the structural properties of the local collaboration subnetwork of each cluster and relate them to the efficiency in knowledge diffusion and innovation creation in that cluster. We then investigate the network architecture of inter-cluster collaborations by examining the cooperation ties among inventors who are directly or indirectly interconnected in network components. We find that the cluster-based and component-based collaboration spaces overlap to a certain extent, but differ in their structure. Gatekeepers are Canadian inventors who by bridging over the two spaces enable the nurturing of clusters with fresh knowledge originating outside. We propose a number of indicators measuring an inventor’s importance as a procurer of external knowledge and find that usually only around 10%-20 % of all inventors are responsible for the inflow of the external knowledge to the cluster.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.010 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".