PENGARUH KINERJA KEUANGAN, UKURAN PERUSAHAAN, STRUKTUR MODAL DAN CORPORATE GOVERNANCE TERHADAP PUBLIKASI SUSTAINABILITY REPORT(Studi Empiris Perusahaan-Perusahaan yang Listed (Go-Public) di Bursa Efek Indonesia (BEI) Periode 2007-2010)
Bibliographic record
Abstract
Publication of sustainability report (SR) in Indonesia is still voluntary, but the interests and priorities of the company to publish SR increases. The aim of this research is to examine the effects of profitability, liquidity, leverage, activity ratio, total assets, number of employees, capital structure, the number of audit committee meetings, the number of board meetings, and governance committee to the publication of sustainability report (SR). The population of this research is listed companies in the Indonesia Stock Exchange (IDX) in the year 2007-2010. The selection of this sample uses purposive sampling method. Based on purposive sampling method, the samples of firms that publish sustainability report (SR) are 24 companies while the number of companies that do not publish sustainability report (SR) are 19 companies. The analysis tool to test the hypothesis is the logistic regression analysis by using SPSS 17.0. Results of this research indicate that total assets, number of employees, board meetings, and committee governance have a positive effect on publication of SR. The leverage indicates a negative effect on publication of SR. While return on assets, current ratio, inventory turnover, capital structure, audit committee meetings showed no effect on SR publications.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".