Does ownership structure affect the evaluation of going concerns in Jordan? A dynamic panel data study
Bibliographic record
Abstract
The purpose of this investigation was to establish the connection between ownership arrangement and valuation of the ability of a business to carry on. The investigation's goal is to clarify how various ownership forms affect how to assess a company's ability to remain in business. The listed firms at ASE throughout the year 2016–2022, according to this study of 65 covers the years 2016–2022, a dynamic panel system GMM estimation, had demonstrated a substantial degree of ownership structure in line with higher going concern awareness and implementation in Jordan. This study indicated that family ownership, foreign ownership, and block holder ownership were particularly important in affecting Jordan's going concern. This study explores the complex relationship between ownership forms and a company's ability to continue operating. In light of our findings, it is crucial for both practitioners and policymakers to adopt a thoughtful and nuanced approach when assessing the continued viability of businesses. This involves considering the unique ownership structures and governance mechanisms of each company.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".