The Initial Going-concern of Delisting Firms: An Application of Proportional Hazard Model
Bibliographic record
Abstract
Normal 0 0 2 false false false EN-US ZH-TW X-NONE MicrosoftInternetExplorer4 This paper examines the survival period and the factors of business failure of firms who have been issued with an initial going concern opinion (IGCO) by auditors. Empirical results show that financial variables are not significant predictors for future delisting crisis, but the corporate governance variables are especially for firms under deteriorating financial condition. Important factors causing the higher rate of delisting risk include shorter listing years, lower rate of retained earnings to total assets, lower rate of market value of equity to total debts, and higher rate of pledged shares of directors’ and supervisors’ within 7.5 quarters after the IGCO issued, the number of delisting firms reaches its peak, consistent with the existence of self-fulfilling prophecy. The hazard delisting function first rises to a peak at the 38 th quarter and then declines rapidly, showing that after the disclosure of IGCO, first nine years is the delisting crisis period for Taiwan public firms.
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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 | 0.016 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 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".