Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
A major issue for US antitrust enforcement in the last year or so has been how to achieve maximum detection and deterrence of cartels, even at the cost of weakening certain sanctions. Thus, new legislation protects first-to-confess price fixers from criminal penalties and from trebling of damages owed to customers. To the same end, US enforcement agencies have sought to cut back the ability of foreign victims of the non-US aspects of worldwide cartels to obtain damage relief in American courts. This approach has been justified primarily as facilitating the operation of leniency policies by decreasing the scope, or uncertainty, of the private damage action consequences of confession. Closing US courts to foreign victims has also been justified in terms of the expressed wishes of the US allies (e.g. Germany, Japan, Canada) to fashion their own private remedy policies for their residents. In merger enforcement, trends are steady, but many litigated merger cases were decided against the Government, which could not always support its theories of probable consumer injury with hard facts. Cases involving misuse of intellectual property continue to be aggressively fought, particularly where dubious means are used to enshrine a patented invention as part of an industry standard. US efforts toward international cooperation and harmonisation have had a steady pattern of achievement, but some difficult issues of policy and practice seem intractable, particularly centralisation of merger control and harmonisation of approaches to private remedies.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 0.004 |
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 it