The Attributes of Dysfunctional Audit Behavior (DAB): Second Order Confirmatory Factor Analysis
Bibliographic record
Abstract
This paper is intended to confirm the attributes of dysfunctional audit behavior (DAB). The attributes of dysfunctional audit behavior consist of under-reporting of time (URT), premature sign-off (PMSO), and time-budget pressure (TBP). We propose task complexity as a new attribute of dysfunctional audit behavior. The data was gathered from 367 senior auditors who work at Big-fourand Non-big four of 140 Public Accounting Firms that registered in Indonesian Public Accounting Association (IAPI). The data was processed using Second Order Confirmatory Factor Analysis (SEM-PLS) – SmartPLS3. The result of the study confirmed that the attributes of under-reporting of time (URT), positively, manifest the dysfunctional audit behavior. The attributes of premature-sign-off (PMSO), positively, manifest the dysfunctional audit behavior. The attributes of time-budget pressure (TBP), positively, manifest the dysfunctional audit behavior. The proposed factor, task complexity (TC) positively, manifests the dysfunctional audit behavior. The premature-sign-off is the most dominant factor reflecting/manifesting the dysfunctional audit behavior. The under-reporting of time (URT), premature sign-off (PMSO), time-budget pressure (TBP), and task complexity (TC) can be used as the predictor of dysfunctional auditor behavior (DAB). The higher the incidence of their attributes, the higher the potential incidence of dysfunctional audit behavior is.
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 | 0.014 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".