Corporate governance and the quality of accounting earnings: a Canadian perspective
Bibliographic record
Abstract
Purpose The paper seeks to examine the association between corporate governance mechanisms and the quality of accounting earnings. Design/methodology/approach Quality of earnings is measured in two ways: the accounting‐based measure of earnings management and the market‐based measure of earnings informativeness. Using firm‐level corporate governance data for a sample of Canadian firms in the years 2001‐2004, regression analysis explores the relation between corporate governance (including board composition, management shareholding, shareholders' rights and the extent of disclosure of governance practices), and the quality of earnings. Findings Empirical tests demonstrate that overall governance quality is negatively related to the level of abnormal accruals and positively influences the return‐earnings association. In addition, the magnitude of abnormal accruals is negatively associated with the level of independence of board composition, the extent of alignment of management compensation with interests of shareholders and the strength of shareholder rights. The results from the returns and earnings analysis are consistent with these findings. Research limitations/implications The tests in this study are association tests. Future research may use qualitative research approaches to examine the link between quality of financial reporting and governance effectiveness. Originality/value This study provides evidence that supports Canadian regulators' initiatives that stronger corporate governance mechanisms provide greater monitoring of the financial accounting process and may be important factors in improving the integrity of financial reporting.
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.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".