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On the Defects of Administrative Monopoly in China’s “Anti-Monopoly Law” and Its Improvement

2010· article· en· W1741849631 on OpenAlexvenueno aff
Jin Sun

Bibliographic record

VenueCanadian social science · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicEuropean and International Law Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMonopolyPolitical scienceLegislationHumanitiesLawEconomicsPhilosophyMarket economy

Abstract

fetched live from OpenAlex

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

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.936
Threshold uncertainty score0.925

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.025
GPT teacher head0.307
Teacher spread0.282 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations5
Published2010
Admission routes1
Has abstractyes

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