对中国公民社会组织良好治理的研究 (NGOs in China: Issues of Good Governance and Accountability) [In Chinese]
Bibliographic record
Abstract
The English version of this paper can be found at http://ssrn.com/abstract=1367706本文研究中国公民社会组织（CSOs）在良好治理方面的作为，比 如在诚信和透明方面的表现。通过对主要的国际及国内公民社会组织的访问,本文将关注中国的公民社会组织是如何理解和实施良好的治理的.此外,本文还将关注中国的乡官人群和公众是如何看待在中国工作的国际和国内公民社会组织.最后,将通过以上方面的研究为中国公民社会组织在未来实现良好治理提出建议.Drawing on interviews conducted among leading local and international NGOs operating in China, this article examines how NGOs understand and implement good governance and accountability principles and practices. It also examines how Chinese constituents and the general public perceive local and international NGOs. The discussion provides a basis on which to assess ways of improving governance and accountability practices for NGOs operating in China.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".