PENGARUH POTENSI KEBANGKRUTAN PERUSAHAAN PUBLIK TERHADAP PERGANTIAN AUDITOR
Bibliographic record
Abstract
The main objective of this paper is to examine the effect of failing firms (firms which arepotential to be bankrupt) on auditor switching. Hypothesis was derived from Schwartz and Menon (1985) which implies that failing firms have a greater tendency to switch auditors than healthier firms do. The Z score (Altman model) was used as a proxy to measure the potential of bankruptcy. This method was applied since it has been developed in several countries such as US, Germany, Brazil, Australia, England, Ireland, Canada, the Netherlands, and France. Annual report and Indonesian Capital Market Directory were used to collect the data for a sample of 7 firms that changed their auditors and 7 firms that did not. Those four-teen (14) firms have been selected as sample among firms in consumer goods industries to answer the question about the impact of firns with potential to go bankrupt on auditor switching. Chi-Square result shows that firms with potential to go bankrupt could not influence auditor switching.Keywords: auditor switching, bankruptcy, Altman Z-Score, failing firm
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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 | 0.003 |
| 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 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.021 | 0.004 |
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".