Theory, evidence, and policy on dual-class shares: A country-specific response to a global debate
Bibliographic record
Abstract
\n \n Dual-class shares have become one of the most controversial issues in today´s\n capital markets and corporate governance debates around the world. Namely, it\n is not clear whether companies should be allowed to go public with dual-class\n shares and, if so, which restrictions (if any) should be imposed. Three\n primary regulatory models have been adopted to deal with dual-class shares:\n (i) prohibitions, existing in countries like the United Kingdom, Germany,\n Spain, Colombia, or Argentina; (ii) the permissive model adopted in several\n jurisdictions, including Canada, Sweden, the Netherlands, and particularly\n the United States; and (iii) the restrictive approach recently implemented in\n Hong Kong and Singapore. This paper argues that, despite the global nature of\n this debate, regulators should be careful when analysing foreign studies and\n approaches, since the optimal regulatory model to deal with dual-class shares\n will depend on a variety of local factors. Namely, it will be argued that, in\n countries with sophisticated markets and regulators, strong legal protection\n to minority investors, and low private benefits of control, regulators should\n allow companies going public with dual-class shares with no restrictions or\n minor regulatory intervention (e.g., event-based sunset clauses). By\n contrast, in countries without sophisticated markets and regulators, high\n private benefits of control, and weak legal protection to minority investors,\n dual-class shares should be prohibited or subject to higher restrictions\n (e.g., time-based sunset clauses and stringent corporate governance rules).\n Intermediate solutions should be adopted for countries with mixed features.\n Therefore, the key question to be addressed from a policy perspective is not\n whether companies should be allowed to go public with dual-class shares, as\n many authors and regulators seem to be discussing, but whether dual-class\n class shares should be allowed and, if so, under which conditions, taking\n into account the particular features of a country.
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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 | 0.020 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.002 | 0.017 |
| Scholarly communication | 0.008 | 0.011 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".