Students and protests: A quantitative cross-national analysis
Bibliographic record
Abstract
Previous studies have found a positive relationship between the youth and the educated with protest number, but the form that these protests take needs further research. We argue that students are a unique group, acting neither as an educated nor a young population, and three possible mechanisms push students toward non-violent rather than violent forms of protest. By promoting values of tolerance, higher levels of human capital, and social mobility, education serves as a factor that pacifies destructive tendencies in protest movements. At the same time, universities are a platform for cooperation, and the large amounts of free time and energy make the costs of participating in protests for students minimal compared with other groups. Using a negative binomial regression and a rare events logistic regression, we find that the proportion of students is a strong and consistently significant predictor of the number of nonviolent demonstrations. However, the share of students in the total population does not turn out to be significantly associated with violent protests/armed uprisings.
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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 | 0.002 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".