Bibliographic record
Abstract
Why would one person facilitate a community member’s evasion of the law, even when there is nothing tangible in it for themselves? In this article, I draw on stories in Chinese villages under the one-child policy to suggest that the lack of moral legitimacy in a particular law motivates people to help others overcome legal or policy restrictions, especially when there are existing connections and trust among them. It reveals the influential impact of law’s moral legitimacy on people’s responses to legal evasion and the relational nature of legal consciousness. An individual’s existing connections with and trust in those who evade the law often reinforce the sense of obligation to take matters into one’s own hands to help right the wrong that has been done to them. Nevertheless, the consequences of participating in such collusion may reshape expectations and obligations within the community, pushing law-evading citizens to minimize risks for those who are willing to facilitate their evasion of the law. The fluid nature of interpersonal relationships in Chinese society also means that when things go wrong, supportive members may in turn use their insider information against the law-evading citizen to seek revenge or teach them a lesson.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".