A comparison of R&D indicators for the Vancouver biotechnology cluster
Bibliographic record
Abstract
The basis of this paper is to go beyond abstract definitions of what a cluster is, and look at a variety of measurable indicators, to see which can demonstrate the presence of a cluster. The example presented is based on the biotechnology industry in Vancouver, Canada. Biotechnology differs from conventional industries, in that there are few tangible goods or services traded, but rather the basis of value creation is primarily the sale or licensing of intangible intellectual property or the (usually pre-revenue) firms themselves. The two main questions we aim to test are (i) is there a biotechnology cluster in Vancouver, and (ii) what are its inputs, outcomes, and impact on the region? We use data provided from local and federal agencies such as LifeSciences British Columbia and Statistics Canada to compare biotechnology R&D activity across regions, and within the local economy. Our findings indicate that there is significant activity around biotechnology R&D and commercialisation in Vancouver, but no guarantee of the longevity of the innovation system.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.011 | 0.019 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".