As A Supply Chain Financing Source, Trade Credit and Bank Credit Relationship during Financial Crises from Clustering Point of View
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
<p>This paper examines trade credit and bank credit behavior of firms during financial crisis using World Bank Survey dataset that contains detailed data on trade credit utilization of firms. Unlike literature, cluster analysis is used in order to investigate credit behavior of firms during financial crisis. For better clustering results, feature selection method is used to select variables thought to be important on model. When examined the trade and bank credit behavior of clusters that have been formed by using these variables with clustering analysis, it has been found that impact of the crisis on firms in the supply chain is important. It is found that due to demand fall for goods generated by crisis, firms are motivated to give trade credits to their customers in order not to lose them. However, firms need financial support either from the previous link in the supply chain through trade credit or from the financial institutions through bank credit.</p>
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it