Firm Characteristics, Governance Attributes and Corporate Voluntary Disclosure: A Study of Jordanian Listed Companies
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 paper focuses on the voluntary disclosure in corporate annual reports in Jordan, and its objectives are: (1) To measure the voluntary disclosure level in the annual reports of Jordanian companies listed in Amman Stock Exchange (ASE). (2) To examine the relationship between a number of explanatory variables and the level of voluntary disclosure. Unweighted disclosure index consisting of 63 voluntary items was developed to assess the level of voluntary disclosure in the annual reports of 124 listed companies on ASE for the period of 2010 to 2012. Univariate and Multivariate analysis were applied to explore the relationship between each explanatory variables and the level of voluntary disclosure and a number of sensitivity tests were taken to further analysis. The findings of the study reveal that the level of voluntary disclosure in Jordanian corporate annual reports is low (its average is 35.7% for three years), although there is a significant increase in the level of voluntary disclosure from year to year. Univariate analysis reveals that firm size, leverage, firm age, profitability, liquidity, board size and audit committee size have a significant positive relationship with the level of voluntary disclosure while independent directors and ownership structure have a significant negative relationship with the level of voluntary disclosure. Meanwhile, multivariate analysis reveals same results to Univariate analysis except leverage has no impact on the level of voluntary disclosure.
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 | 0.001 | 0.001 |
| 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 | 0.000 | 0.001 |
| 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 it