Timeliness of corporate annual financial reporting in Indonesian banking industry
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The financial performance of the banking sector globally can be seen on the capital markets of each country. One of the important sources of information in the investment business on the capital market is the financial reports that are provided by every company going public. The objectives of this study are (1) to determine the simultaneous and partial effect of liquidity factors, Debt Equity Ratio, company size on timeliness of financial reporting in the banking sector in Indonesia. (2) to determine what factors are dominant in the timeliness of financial reporting in the banking sector in Indonesia. This research uses secondary data with panel data analysis method. The results show the liquidity variable, Debt Equity Ratio and firm size positively influence on timeliness of financial reporting in the banking sector in Indonesia. Firm Size is the dominant factor that has a significant positive effect on the Timelines Financial Report of the banking sector in Indonesia. The findings of this research are that increasing liquidity, Debt Equity Ratio and Firm Size can increase the Timelines Financial Report of the banking sector in Indonesia. Firm Size as the dominant factor is the attraction and driving force for the Timelines Financial Report banking sector in Indonesia. The research can be used as a reference for future researchers on identifying efforts of the influence of Liquidity, Debt to Equity Ratio, Firm Size and Timelines Report.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it