On the Defects of Administrative Monopoly in China’s “Anti-Monopoly Law” and Its Improvement
Bibliographic record
Abstract
Regulating administrative monopoly is the major task of China’s “anti-monopoly law” and the greatest challenge in its enforcement. Anti-monopoly law has done a special chapter on administrative monopoly for the first time, which is a significant breakthrough of our country's legislation on the regulation of administrative monopoly. But, after all, “anti-monopoly law” is a new and due to the limitations of legislation, there are many system deficiencies, on the regulation of administrative monopoly in China’s Anti-monopoly law, which make it can not fully come into play. So, it is necessary to perfect the measures that can make up for the system deficiencies.Key words: anti-monopoly law; administrative monopoly; system defects; measures to improve; economic democracy Resume: La reglementation de monopole administratif est tâche principale de la anti-monopole en Chine et le plus grand defi dans son application. Pour premiere fois, loi anti-monopole a fait un chapitre special sur le monopole administratif, ce qui est une percee importante dans legislation sur reglementation de monopole administratif de notre pays. Mais, apres tout, la anti-monopole est une nouvelle loi, et en raison des limites de legislation, et il existe de nombreuses lacunes dans le systeme de reglementation de monopole administratif dans loi anti-monopole, ce qui l’empeche d’entrer pleinement entrer en jeu. Du coup, il est necessaire de perfectionner les mesures qui peuvent compenser les defauts du systeme.Mots-cles: anti-monopole; monopole administrative; defauts du systeme; mesures visant a ameliorer; democratie economique
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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 | 0.007 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.008 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".