The Role of Foreign Directors in Corporate Risk Disclosure: Empirical Evidence From Jordan
Bibliographic record
Abstract
The current study examined the role of foreign directors in enhancing the level of risk disclosure in the annual reports of Jordanian listed companies. The content analysis method was used to measure the level of risk disclosure by computing the number of risk-related sentences in annual reports. To achieve the study’s objective, random effect model have been applied on a sample of 376 firm-year observations of Jordanian non-financial companies for the period of 2014-2017. The findings are in line with the argument of agency theory and resource dependence theory, which posits that existence of foreign members on the board contributes in increasing the level of risk disclosure. The study aimed to fill the gap in the literature of risk disclosure regarding the relationship between foreign directors and risk disclosure. It is expected that the findings will be useful to researchers, authorities and investors alike in understanding the important role of foreign directors in improving practices of risk disclosure in Jordan.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 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 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".