The Regulatory Mechanism of Charity Organization: Enlightenment on the Experience of Developed Countries
Bibliographic record
Abstract
It is not only the inherent requirements of enhancing the credibility of charitable organizations but also the inevitable choice of promoting their healthy development to make charities' regulation mechanism sound. In this regard, the United States,Britain,Canada and other developed countries have gained a relatively mature experience. Scientific regulation mechanism is a multilayer regulation system in which different parts are effectively combined together and complementary to each other. It includes government's regulation,charity association's regulation,third-party rating agency's regulation,and the mass media's regulation. In order to learn from the experience of developed countries and improve China's regulation mechanism of charity,we should accurately locate government regulation's responsibilities, strengthen charity legislation,strengthen self-construction of charitable organizations,and cultivate social supervision power.
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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 | 0.018 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.011 | 0.018 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.003 | 0.011 |
| 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".