The Application Issues and Improvement Approaches of Differential Voting Rights System —From the perspective of comparing domestic and foreign practices
Bibliographic record
Abstract
With the rapid development of science and technology industry, the traditional principle of "one share, one right" has limitations, and differentiated voting rights have emerged because of its advantages such as meeting the heterogeneous needs of shareholders, resisting hostile takeo-vers and guaranteeing corporate financing. The practice of differentiated voting rights in coun-tries such as the United States, Japan, Singapore and Canada and China is different in terms of regulatory models, information disclosure and sunset clauses. However, the differentiated vot-ing rights system may lead to the increase of agency cost, the lack of supervision mechanism and the intensification of moral hazard in practice. In order to improve the system, the information disclosure mechanism should be improved, the fiduciary duty of controlling shareholders should be strengthened, and a "time-type sunset clause" should be introduced to balance the in-terests of all parties and promote the optimization of China's business environment.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".