AGENCY COST TO DIVIDEND PAYOUT RATIOAGENCY COST TERHADAP DIVIDEND PAYOUT RATIO
Bibliographic record
Abstract
This study was conducted to examine the effect of agency cost in dividend policy (dividend payout . In this case, the agency cost is represented by insider ownership, institutional ownership, collateralizable &bt to tatal assets, and.frim size. Basically, the purpose of this study is to know how big the infiuence cost of dividen policy (dividend payout ratio). The samples in this study used purposive sampling ofNon-Financial Companies which arelisted on thelndonesianStock Exchangewithin 2005- The analytical tool that used in this study were multiple regressions. From the analysis shows that in institutional ownership variables andfirm size variables are influence positively and signifrcantly on trn- This research also.found that collateralizable assets has negative and significant influence on DPR. The * variables in the research which are insider ownership and debt to total assets did not affect significantly t DPR. The result of regression estimation show the ability of model prediction is 45%while the remaining 5f '. influenced by other.factors outside the model that has not been included in the study
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.032 | 0.008 |
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".