Factors Affecting Campus Loans in Western China
Bibliographic record
Abstract
Campus loans have become a part of the lives of Chinese college students. While such loans are convenient for students, they can also create considerable difficulties. In the context of unbalanced economic development between Western and Eastern China, this study aimed to understand the factors affecting the campus loan behaviors of college students in Western China. A sample of 568 undergraduate and graduate students from four universities in Western China was taken as the research object. Binary logistic regression and orderly logistic regression were used to study campus loan consumption factors. Students without state-subsidized loans were found to have stronger campus loan consumption intention and higher loan amounts, and recreational consumption was the main loan purpose. The factors affecting campus loan consumption included students’ family structure, parents’ education level, peer students’ consumption status, grade level, relationship status, and ability to assess loan risk. Based on the findings, suggestions are made for managing campus loan behavior from the perspectives of the individual, family, school, and government. This study can provide guidance for standardizing campus loans and adjusting college students’ consumption attitudes and behaviors.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".