The Effect of Net Income and Other Comprehensive Income on Future’s Comprehensive Income With Attribution of Comprehensive Income as Moderating Variable
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
This study aims to examine the effect of net income and other comprehensive income on the total of future’s comprehensive income with attribution of earning as a moderating variable. It also tests whether comprehensive income is more persistent than Net Income and whether re-measurement of the defined program is the highest predictive power for future CIs. The dependent variable was Comprehensive Incomet+1, and the independent variables were Net Income and Other Comprehensive Income. Data sources were financial statements 2014-2018 of 367 companies listed in Indonesia Stock Exchange. The empirical evidence were 1).Net income and other comprehensive income can predict future comprehensive income, 2). The CI attribution can improve the ability of NI and OCI in predicting future CI. 3). Net income is more persistent than other comprehensive income, 4). The defined program is the highest predictive power for future CIs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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