US patent sales by universities and research institutes
Bibliographic record
Abstract
This Chapter explores the extent to which universities and other nonprofit research institutes currently participate in the secondary market for patents. We document 220 assignments, involving a total of 544 US patent assets, that appear to represent arms-length patent sales by universities (or other nonprofit research institutes) during the period 2012–2017. We present data on the entities and assets involved in these transactions, as well as the publicly available circumstances underlying each sale. Among other findings, we observe that foreign universities are the most active market participants. Overall, US universities and labs account for less than one quarter of sales, and elite US research universities are almost entirely absent from the market. We also find that few academic US patent sales bear the hallmarks of technology transfer. Just eleven percent of assets appear to have been purchased with commercialization in mind. Virtually all other purchases appear to have been either defensive acquisitions by operating technology companies or purchases by nonpracticing entities. Finally, we consider what conclusions policymakers and university administrators may draw from our data.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.007 | 0.010 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.018 | 0.006 |
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".