The effect of XBRL adoption on information symmetry in companies’ financial reports through knowledge management: Perceptions of employees of the Jordan securities commission
Bibliographic record
Abstract
The aim of this study is to investigate the impact of XBRL adoption on information symmetry in the presence of knowledge management as a mediating variable. Data were collected using a questionnaire distributed to all employees working at the Jordan Securities Commission (JSC). Applying the partial least squares method via SmartPLS-3, the results pointed out that the XBRL had significant positive direct effects on knowledge management and information symmetry, knowledge management had a significant positive direct effect on information symmetry. Hence, a partially mediating significant effect of knowledge management was detected between the XBRL and information symmetry. Accordingly, the study recommended governmental legislative bodies to continue supporting XBRL adoption to improve the quality of financial information. The study also recommends understanding the perceptions of preparers and users of financial statements about challenges that hinder the adoption of XBRL in various commercial sectors in order to improve the consistency of informational content in annual reports.
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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 | 0.008 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".