The Empirical Studies of China's Enterprise Bankruptcy Law: Problems and Improvements
Bibliographic record
Abstract
Abstract Over the past 9 years since the implementation of China's Enterprise Bankruptcy Law in 2007, it has contributed to some measures of regulating market practice and rearrangement of market resources and has become an integral part in an improved legal system of China's market economy. However, a closer look at the effect of implementing the Enterprise Bankruptcy Law shows that the number of bankruptcy cases after its implementation, instead of increasing, has taken on a trend of decreasing. Even under the influence of the 2008 financial crisis, no significant increase in the number of Chinese bankrupt enterprises means that China's Bankruptcy Law failed to play its due role, leaving a large gap as desired. As such, this article aims to examine the problems arising from the implementation of the Bankruptcy Law and, taking this as guidance, probe into the reasons hidden behind and propose possible improvement measures. It is expected that the Bankruptcy Law would increasingly play a key role in the development of China's market economy, particularly under the current situation where Chinese government proposes to clean up zombie businesses. Copyright © 2018 INSOL International and John Wiley & Sons, Ltd.
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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 | 0.015 | 0.031 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.010 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".