EVALUATION OF THE INCREASE IN PERSONAL CONSUMER LOANS AND CREDIT CARD USAGE AFTER THE COVID-19 PANDEMIC: THE CASE OF TURKEY
Bibliographic record
Abstract
Pandemics on a global scale always bring along important economic crises. The basis of this is the loss of workforce and the adverse effect the supply chain undertakes. Consumer loans and credit cards are the first products that individuals tend to use in order to overcome the difficulties they face while meeting their financial needs, even after the loss of workforce. This study has been carried out to determine the level of tendency of individuals to loan products in the solution of severe financial problems created by the Covid-19 Pandemic. In order to achieve this, the data published by the Banking Regulation and Supervision Agency on a monthly basis, from the first quarter of 2017 until the end of the first quarter of 2022, have been used. At the end of the study, when the data obtained have been evaluated it is seen that there was a great trend towards related credit products from the first days of the Covid-19 Pandemic. It is expected that the data obtained in the study will contribute to the understanding of the importance of the banking system and a better understanding of the economic effects of the pandemic.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".