Issues in the Protection of Minority Shareholders’ Rights and Interests under China’s Company Law
Bibliographic record
Abstract
On December 29, 1993, the Standing Committee of the National People’s Congress (NPCSC) of China adopted the Company Law of the People’s Republic of China (PRC), which was the first of its kind since the establishment of the PRC. Because of the historical background of the era when economic reform was begun, the contents and description of the Company Law were rather simplistic, and some of its articles simply didn’t make sense. Following the development of the market economy in China, the Company Law obviously could no longer meet the practical requirements of the economy. Although amendments were made by the NPCSC on December 25, 1999, and August 28, 2004, respectively, appeals for a complete revisal of the Company Law grew stronger and stronger. After a draft of the revised version was reviewed a number of times, the 10th NPCSC adopted the revised Company Law at its 18th General Session on October 27, 2005. (The revised Company Law is hereinafter referred to as the “New Company Law,” and the original version before this revisal is hereinafter referred to as the “Former Company Law.”) These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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 | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.011 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| 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".