Environmental Management Accounting, Islamic Social Reporting, and Corporate Governance Mechanism on Sharia-Approved Companies in Indonesia
Bibliographic record
Abstract
Issues of Islamic Social Reporting among Sharia-approved companies in Indonesia are still rare. Sharia-approved companies must comply with the sharia principles that have been approved by the Sharia Fatwa Council and the Financial Services Authority. The aim of this study is to obtain empirical evidence conformity of corporate environmental management accounting practices with the concept of Islamic Social Reporting. This study will also find evidence the effect of company's monitoring function to implementing Islamic Social Reporting.The practice of corporate environmental management accounting is an interesting and important study because environmental issues are a complex issue. For Sharia-approved companies, the commitment to comply with sharia principles in environmental activities provides assurance to its specific investor that the business activities run according to sharia principles. The commitment to prevent sharia-based business activities is stronger when the company's monitoring function also strengthens the company's objectives in protecting the environment.This study was conducted on Sharia-approved companies listed on the Indonesia Stock Exchange following the PROPER assessment from the Ministry of Environment. 38 companies were observed over a period of 3 years.The results of the study show that corporate governance has not provided a maximum monitoring function in the company. Companies are more obedient to the rules of law related to the environment. That is, for environmental protection companies are still in the concept of obeying the rules yet on awareness to integrate into the company's strategy.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".