News coverage of social protests in global society
Bibliographic record
Abstract
This article links media and social movement studies with world society theory to explain cross-national variations in media attention to domestic social protests. We compile a novel large-scale dataset with over 1.2 million protest-related news articles from 12,644 web news sites across 140 countries/areas in 2015–2020. Our cross-national analysis shows that both media- and country-level characteristics explain news coverage of domestic social protests. Our findings show that web news outlets with high web traffic and a propensity to report conflictual events tend to cover more protests. In addition, web news sites in nations with vibrant civil society organizations report more protest events. We also find that there is a positive relationship between online censorship and news coverage in general. But this is driven by news media in democratic countries, and news sites in authoritarian regimes experiencing strong censorship cover fewer protest events. Finally, news media in authoritarian nations with more organizational ties to the international community cover more domestic protests.
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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 | 0.001 | 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 | 0.000 | 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 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".