Bibliographic record
Abstract
In perhaps no other area of competition policy is there greater dispute over the appropriate legal rule as there is over the practice of tying. The authors consider when tying is anti-competitive and when the practice should be prohibited, adopting economic efficiency as the policy criterion. Through a review of prominent economic theories and case studies of tying, the variant circumstances in which tying can be pro-competitive, ambiguous, or anti-competitive are explored. Additionally, the linkage with intellectual property rights is discussed to understand how tying affects the relationship between innovation incentives and static market efficiency that is at the core of optimal IP policy. The authors conclude that antitrust authorities cannot rely on general rules in concluding that tying in a given case violates antitrust laws, but must rely on case-by-case analysis. Given the relative rarity of anti-competitive tying, the authorities should require significant evidence of anti-competitive effects before making an order against tying.
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 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.043 |
| Scholarly communication | 0.013 | 0.017 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.013 | 0.001 |
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".