Chinese Corporate Balkanization: The Reality of Political Economy and Competition for Corporate Charters as a Replacement
Bibliographic record
Abstract
In the area of business law, legislatures always lack incentives to enact optimal laws and are reluctant to innovate even if innovation is badly needed in the real business world. This reluctance exists because lawmakers share few of the benefits of producing optimal laws. Competition among states for corporate charters is the genius of American corporate law. This competition has proved to be an effective way to improve the responsiveness of corporate law. In contrast, the EU and Canada have run into bottlenecks when trying to introduce charters competition. Due to a lack of specific legal expertise in corporate law, Chinese local governments often find themselves with enormous discretion in regulating the local market. Driven by political ambitions, bureaucrats are eager to use any means available to raise local GDP. These methods include some that contradict the policy of the central government and have negative effects on the local community. These practices invite a “race to the bottom” situation and create symbiosis between management and bureaucrats, increasing the likelihood of corruption. These problems of racing to the bottom can be solved by actions of the central government. Meanwhile, thru introducing charters competition, local lawmakers still can compete and the competition under legal frame will be “race to the top” competition. Given the specific political and economic realities of China, the problems preventing the EU and Canada from adopting charters competition will not haunt China Through proper legal arrangement, local provinces may have a chance to promulgate their own corporate laws, even if the corporate law-making power remains in the hands of the national legislature.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.008 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".