Intellectual property, antitrust, and the rule of law: between private power and state power
Bibliographic record
Abstract
Abstract This Article explores the rule of law aspects of the intersection between intellectual property and antitrust law. Contemporary discussions and debates on intellectual property (IP), antitrust, and the intersection between them are typically framed in economically oriented terms. This Article, however, shows that there is more law in law than just economics. It demonstrates how the rule of law has influenced the development of several IP doctrines, and the interface between IP and antitrust, in important, albeit not always acknowledged, ways. In particular, it argues that some limitations on IP rights, such as exhaustion and limitations on tying arrangements, are grounded in rule of law principles restricting the arbitrary exercise of legal power, rather than solely in considerations of economic efficiency. The historical development of IP law has reflected several tensions, both economic and political, that lie at the heart of the constitutional order of the modern state: the tension between the benefits of free competition and the recognition that some restraints on competition may be beneficial and justified; the concern that power, even when conferred in the public interest, can often be abused and arbitrarily
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 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 | 0.008 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.056 |
| Scholarly communication | 0.017 | 0.016 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.006 | 0.007 |
| 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".