Bibliographic record
Abstract
Abstract This paper connects ideas from recent literature on the economics of intellectual property (IP) to address the question: Did the strengthening and broadening of IP rights from important patent policy changes in the US promote greater innovation? The analysis rests on the theory of cumulative innovation, which shows that if IP rights on a pioneer invention extend to follow‐on research and impediments to contracting exist, then strengthening patents can actually reduce overall innovation. Recent empirical studies are consistent with the theory: patents can significantly deter follow‐on research in “complex” technology areas where contracting is difficult (computers, electronics, telecommunications) but not in drugs, chemicals and human genes. I outline remedies from court decisions and antitrust policy for addressing inefficiencies from patent trolling, patent thickets and the anti‐commons of fragmented ownership. I then apply the analysis to the antibiotics market, drawing on recent research, to examine how patent and competition policies can be used to improve incentives for drug development in the battle against antibiotic resistance. The literature provides persuasive evidence that the policy changes overreached in broadening and strengthening IP rights and reveals important patent reforms for improving the effectiveness of patent systems in the US and Canada.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".