Corporate governance on financial distress: Evidence from Indonesia
Why this work is in the frame
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Bibliographic record
Abstract
The main objective of this paper is to explore the most significant determinants of financial distress of manufacturing companies in Indonesia and to provide explanations on this issue by using multiple regression models. With Modigliani and Miller’s and Trade-off theories were reviewed to formulate a testable proposition on the determinants of financial distress of manufacturing companies in Indonesia. Multiple regression models were used as a statistical tool to investigate the most significant profitability determinants of manufacturing companies in Indonesia. The Lisrel software was used to analyze 300 manufacturing companies listed on the Indonesia Stock Exchange. It was found that institutional ownership, firm size, profitability, and board independence as variables had a positive relationship in an effort to avoid financial distress. Meanwhile, the board size variable had an insignificant positive relationship. The findings are consistent with the pecking order and financial agency theory which helps in understanding the application of financial distress studies for manufacturing companies in Indonesia.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it