Bibliographic record
Abstract
Auditor changes are alarmingly high in Yemen and have been rising of late and the driving factors in this regard could be particular to Yemen. This study examines the motivations for public firms in Yemen to change auditors. In this paper, a questionnaire instrument is used to elicit perceptions of behavioral, economic or other factors that influence auditor-client realignments in Yemen. The study concludes primarily that economic factors provide the principal motivators of auditor changes in Yemen. Behavioral forces albeit influential factors of auditor change, come only secondary in importance. Dissatisfaction with audit quality, use of inexperienced audit engagement staff feature and poor working relationships with audit partner/staff feature as foremost concerns. Underlying this, there is evidence of significant associations between the reasons for change and type of change. Also, there is a significant relationship between the auditor change and size of companies. In particular, larger and medium companies, and companies changing from a non-Big Four to Big Four firm, were more likely to change due to dissatisfaction with audit quality, and the need for a wider range of services.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".