What Drives People to Protest in an Authoritarian Country? Resources and Rewards vs Risks of Protests in Urban and Rural 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
What drives people to protest in an authoritarian country? Drawing from a rich set of individual-level data from the China General Social Survey 2010, we address the question of protest participation by focusing on the factors of resources, and rewards vs risks, that might be unique to protestors in an authoritarian state. We find strong evidence for education, typically conceived as a key enabling resource in protests, to be negatively associated with likelihood of participation. There are, however, significant differences between political behavior in urban and rural samples. We find some, though rather weak, evidence to suggest that as urban residents become wealthier over time, they will increasingly turn to protests as a form of political participation, demanding greater accountability of government and corporate actions.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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