University Patenting: Estimating the Diminishing Breadth of Knowledge Diffusion and Consumption
Bibliographic record
Abstract
The rate of university patenting increased dramatically during the 1980s.To what extent did the knowledge flow patterns associated with public sector inventions change as university administrators and faculty seemingly became more commercially oriented?Using a Herfindahl-type measure of patent assignee concentration and employing a difference-in-differences estimation to compare university to firm patents across two time periods, we find that the university diffusion premium (the degree to which knowledge flows from patented university inventions are more widely distributed across assignees than those of firms) declined by over half during the 1980s.In addition, we find that the university diversity premium (the degree to which knowledge inflows used to develop patented university inventions are drawn from a less concentrated set of prior art holders than those used by firms) also declined by over half.Moreover, in both cases the estimated increase in knowledge flow concentration is largely driven by universities experienced in patenting, suggesting these phenomena are not likely to dissipate with experience.
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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 | 0.004 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".