Bibliographic record
Abstract
This article presents a bibliometric study on different types of risk and bankruptcy, aiming to contribute to academic knowledge in this area. We used the bibliometrix tools in R and VOSviewer, following the main laws of bibliometrics (Bradford’s law, Lotka’s law, and Zipf’s law). We analyzed 7163 relevant academic publications retrieved from the WOS database between 1995 and 2023. The characterization of the literature identified trends, importance, and scientific relevance of works, journals, and authors. This allows for promoting collaborations among researchers and provides insights for strategic decision making, advancing knowledge in the field. The most relevant journal was the “Journal of Banking and Finance”, with Edward Altman as the prominent author. The United States and China were the most active countries in research. The current research highlights terms such as “board size”, “CRS”, “responsibility”, and “governance”, which are commonly found in recent works. The themes of greatest centrality include risk, model, and debt. The bibliometric review revealed gaps in knowledge and research, indicating a growing trend of studies in this area. This article provides valuable information for researchers and managers, supporting decision making in risk management and bankruptcy.
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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 | 0.012 | 0.066 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.173 | 0.222 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.012 | 0.010 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".