Research on the Development of China’s Peer-to-Peer Online Lending Industry Based on System Dynamics Simulation
Bibliographic record
Abstract
This paper divides the economic operating system of peer-to-peer online lending industry into industry subsystem, investment and financing subsystem and macroeconomic subsystem. By establishing a system dynamics model and conducting simulation analysis, this paper explores the influence and trend characteristics of the monetary policy, regulatory policies and investment and financing expectations to China’s P2P industry development. Tight monetary policy promotes the development of the P2P industry in the short term, but it reduces the scale of the industry in the long run. A strong regulatory policy leads to an outbreak of industry risks in the short term and stabilizes the industry in the long run. Changes in investment and financing expectations make the scale experience the process of falling, slight rising to rapid decline. Based on the simulation results, the policy enlightenment and suggestions can be obtained to promote the steady development of P2P online loan industry.
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How this classification was reachedexpand
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".