Shareholders’ Power in Manage the Company’s Business in Private Limited Company – the Case of Czechia in an International Context
Bibliographic record
Abstract
The legal regulation of the Czech limited liability company is distinctive in an international context. While many foreign jurisdictions, to varying degrees, allow shareholders to influence the business management of the company through the general meeting and, for this purpose, to instruct the director (or even decide on a particular matter themselves), Czech company law, as a general rule, explicitly prohibits such a procedure, except where expressly permitted by law. According to established case law, no contrary conclusion may be drawn, even in view of the differing nature of a limited liability company as opposed to a joint-stock company. However, Czech case law and legal doctrine regrettably fail to explore the underlying rationale and objectives of this prohibition in depth. A comparison with the legal framework governing limited liability companies in Germany, Austria, Slovakia, the United Kingdom, Canada, and Australia suggests that shareholders’ intervention in the business management of a limited liability company can be functional, provided that the protection of minority shareholders and creditors remains unaffected and appropriate regard is paid to the director’s liability towards the company. Even these issues, however, can be adequately addressed within the existing framework of Czech legal scholarship.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.009 | 0.014 |
| Scholarly communication | 0.015 | 0.004 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.005 | 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".