Auditor Independence and Mandatory Auditor Rotation in Jordan
Bibliographic record
Abstract
Purpose: The purpose of this study is to test the relationship between auditor rotation and the level of auditor independency, and to investigate, the impact of auditor rotation, audit fees, audit tenure and the relationship with client on the auditor independency in Jordanian audit firms. Furthermore, to identify the reasons behind rotating the auditor and the advantages/disadvantages of auditor rotation. Design/methodology/approach: The study has been carried out through a questionnaire survey that aimed to collect data about the auditor independency in Jordan, and through a developed model to test the mandatory auditor rotation in the Jordanian audit firms. Findings: After defining the four independent main variables of the auditor independency (auditor-client relationship, audit tenure, audit fees, and mandatory auditor rotation). The findings of the study revealed that there is a significant positive relationship between the auditor independency and auditor-client relationship and mandatory rotation. A negative one with the audit fees and there is no relationship with audit tenure. Research limitations/implications: This paper has some limitations such as, some audit firms refused to allow researchers to distribute the questionnaire which is not familiar in Jordan. Originality Value: This paper contributes to the understandings of the nature and characteristics of the auditor independency by empirically exploring the nature and characteristics of mandatory auditor rotation in Jordan.
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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 | 0.003 | 0.010 |
| 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 | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".