THE TIMELINESS OF ONLINE FINANCIAL REPORTING OF SELECTED INDIAN, U.K. AND U.S. BANKS
Bibliographic record
Abstract
The timeliness of Online Financial Reporting is an emerging topic in the accounting literature for decades. Now a days internet has become an vital means of communication of financial reporting information by banks since the mid to late nineties and timeliness factor refers to the need for accounting / reporting information to be presented to the users in time to fulfill their decision making needs. Now that many banks post their Quarterly Results on their websites according to their countries norms i.e. India, U.K. & U.K. norms. The banks listed on BSE (Bombay Stock Exchange) had found that sample banks disclosed their quarterly results on their websites within one month after the ending of each quarter. The banks listed on LSE (London Stock Exchange) had found that sample banks disclosed their quarterly results on their websites within 3 months after the ending of each quarter. According to SEC (Securities Exchange Commission) the banks listed on NYSE (New York Stock Exchange) had found that sample banks disclosed their quarterly results on their websites within 35 days after the ending of each quarter.
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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 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.009 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".