Firm’s size, mandatory adoption of IFRS and corporate risk disclosure amonglisted non-financial firms in Saudi Arabia
Bibliographic record
Abstract
This study examines the relationship between the mandatory adoption of International Financial Reporting Standards (IFRS) and the disclosures of corporate risk among non-financial firms in Saudi Arabia. Based on the observation of 320 firm-year from 2015 until 2017, this study reveals a positive relationship between the mandatory adoption of IFRS and the corporate risk disclosures. The relationship holds when we decompose corporate risk disclosures into financial and non-financial risk disclosures. The results are consistent for both the pooled Ordinary Least Squares (OLS) and random effects estimations. Additionally, the result is steady with all primary categories except risk management. We also provide evidence that large firms are more likely to adopt IFRS and reveal more risk information than small firms. This study’s findings are relevant for market regulators in their attempt to improve corporate risk disclosures among listed firms in Saudi Arabia.
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How this classification was reachedexpand
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".