Bibliographic record
Abstract
Purpose Unlike firms listed in the USA, many large firms in Canada belong to business groups organized as pyramids. A pyramidal structure refers to a business group that consists of a set of enterprises or other entities and displays a top-down chain of control. The purpose of this paper is to investigate the relationship between pyramid ownership and earnings management. Design/methodology/approach The paper is an empirical study using a sample of 165 Canadian listed firms from 2010 to 2015. The impact of pyramid ownership on both accrual-based and real earnings management is examined. Findings The findings show that pyramid-affiliated firms engage in less accrual-based and real earnings management than non-pyramid-affiliated firms. The results further show that the divergence between control rights and cash flow rights of the controlling shareholders in the pyramid-affiliated firms is positively related to real earnings management. Moreover, the results highlight that intra-group transactions (other than internal financing) among pyramid-affiliated firms lead to higher level of both accrual-based and real earnings management, but internal financing is negatively associated with real earnings management. Overall, this study provides the evidence which indicates that pyramid ownership structure and earnings management are related to each other. Originality/value The paper contributes to the earnings management literature by studying the impact of pyramid ownership structure on earnings management, especially real earnings management.
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 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 | 0.001 | 0.003 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".