The Effect Of Return On Asset (Roa) And Dividend Policy On The Value Of Manufacturing Companies
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 purpose of this research is to know how much influence of Return on Assets (ROA) and Dividend Policy to Firm Value partially on Manufacturing Companies. The method of data collection is through the population data of manufacturing companies for the period 2017 to 2021. The data is taken through the official website of the Indonesia Stock Exchange (www.idx.co.id). The total population was found to be 167 listed companies. The samples of companies used in this study are twenty seven companies that have passed the criteria that have been determined in purposive sampling. In this study, the data used is secondary data. To obtain secondary data, it is taken from financial reports, annual reports and sustainability reports of each manufacturing company listed on the Indonesia Stock Exchange. Data processing using IBM SPSS 25 application.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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