Reconstruction of the Business Judgment Rule Doctrine in Indonesia: Legal Comparison with England, Canada, the United States, and Australia
Bibliographic record
Abstract
This research specifically analyzes the comparison of the substance of the business judgment rule doctrine in Indonesia with that in other countries by comparing several countries, namely: England, Canada, the United States and Australia. The aim of this research is to reconstruct the future regulation of the business judgment rule doctrine in Indonesia. This research is normative legal research that prioritizes conceptual, statutory, case, and comparative approaches. The research results show that the principles related to the business judgment rule doctrine in Indonesia include the principle of good faith, the principle of prudence, the principle of expediency, and the principle of legal certainty. The characteristics of the business judgment rule doctrine in Indonesia, as contained in statutory regulations and court decisions, actually emphasize the mechanisms that must be taken by directors before making a decision, namely the obligation to prioritize the willens aspect, namely knowing a decision to be taken, and the wettens aspect, namely wanting and understanding the potential consequences. by a decision to be taken. Reconstructing the business judgment rule doctrine in Indonesia by referring to practices in England, Canada, the United States, and Australia, the BJR regulations in Indonesia actually require reconstruction or updating in the future by formulating specific regulations regarding the BJR doctrine in Indonesia and providing space for judicial institutions to develop the application of the BJR doctrine according to developing cases.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".