Shenpi (Licensing) Reform from the Perspective of One Municipal Jurisdiction: Ideologies, Institutions, and Law
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The Administrative Licensing Law (xingzheng xuke fa) will constitute a major addition to Chinese administrative law, and the rhetoric surrounding its drafting promises path-breaking reform of the Chinese regulatory state. This report critically assesses that promise by chronicling the actual course of shenpi (licensing) reform carried out in Shenzhen in 2001. Shenpi reform derives its novelty from questioning the rationale of regulatory policies and not just the procedures by which they are carried out. In Shenzhen, however, the reform revolved around an effort to achieve quantitative reduction in the number of shenpi procedures, which could reflect either changes in the substance of policies or mere success in cutting red tape. Close examination reveals that Shenzhen's reform was a combination of house cleaning against errant rule-making and an attempt to further increase bureaucratic efficiency, whereas little was accomplished in policy reorientation. A key difficulty in overhauling regulatory policies in China is the extremely insular policymaking process, where policy development falls entirely into the hands of specialised agencies. Not only is legislative and judicial oversight over agency rule-making absent, Shenzhen's experience also suggests that accountability has been difficult to establish even within the executive branch. This is due both to the weakness of internal monitoring institutions and the limited concept of accountability the government employs. The report concludes that incremental reform is possible to allow greater input into the policymaking process and to impose greater accountability on that process, even if robust legislative and judicial supervision is not politically or institutionally feasible in the near future.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| 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 it