“Kill the chicken to scare the monkey”: Heavy penalties, excessive <scp>COVID</scp>‐19 control mechanisms, and legal consciousness in China
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
Abstract This study analyses the legal consciousness of Chinese citizens during the COVID‐19 pandemic when the authoritarian state invoked heavy penalties to deter noncompliance with its excessive COVID‐19 restrictions. China used the approach of “killing the chicken to scare the monkey,” publicly punishing those who violated restrictions in order to deter noncompliance. This article explains why ordinary citizens supported this selective application of the law, as well as how the possibility of being the “chicken” contributed to their compliance (or noncompliance) with excessive COVID‐19 restrictions. It suggests that the uncertainty and unpredictability of law in the authoritarian state bred fear, which then led to compliance, regardless of the lack of procedural fairness. People's dissatisfaction with the rules, however, led them to tolerate and even support the noncompliance of people they trusted.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Science and technology studies | 0.002 | 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 it