Global movements, national grievances. Mobilizing for “real democracy” and social justice
Bibliographic record
Abstract
In the ashes of political and socio-economic collapse, social movements sometimes rise like a phoenix. Little more than a year has passed since the Tunisian uprisings, the spark that ignited a series of “mobilizations of the indignant” that spread like wildfire around the world. Many observers have reported on these unprecedented global protests. They have portrayed citizens who declare feeling marginalized if not scapegoated, and who reject the increasing inequalities between rich and poor, the declining mobility of most, and the “disclassment” of many. They have shown, as well, massive protests against governments and politicians that are perceived as indifferent at best, duplicitous at worst, and in any event as blatantly closed to popular concerns. Many journalists have indeed asked what took so long for people to protest given this fatal combination. For the social scientist, however, the questions of who, why and how mobilizes are not so simple. There are specific problematics of mediation between structure, culture and individual or collective agency that need to be addressed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.010 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.014 | 0.004 |
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 source (direct Gemma or distilled Codex), 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".