A Study on Some Legislation Emphases on Private Lending: Based on Financial Function Theory
Bibliographic record
Abstract
Based on the financial function theory, finance possesses six different functions, including resources allocation, floating of loan, information providing, means of payment, incentive mechanism as well as risk control. Compared with the status quo of China's private lending, the resource allocation function is still not significant confined to the geographical and habits factors. The information providing function is working without necessary accuracy, and may easily lead to moral hazard. The incentive mechanism function tends to alienate from originally normal incentive to a tool encouraging greed because of the unlimited rise of human lust Virtually nothing could be witnessed in terms of the function of means of payment and the role of risk control. To better achieve the functions of finance, legislation needs to play a more active role in the points hereinafter: defining the accession conditions for the market players to give some institutes the subject status, managing interest rate and suppressing usury firmly, defining legal responsibility to every kind of illegal private lending clearly, as well as encouraging the sector to self-discipline.
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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 | 0.002 | 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".