From the global South to the human rights stage: A study of global frame resonance using a comparative case of Women, Life, Freedom and Bloody November in Iran
Bibliographic record
Abstract
In the intersection of local and transnational oppression, global power hierarchies, and the dominance of global North in global civil society, social movements in the global South under authoritarian regimes usually cannot gain international attention and become a global human rights concern. Considering the global momentum toward authoritarianism and illiberalism and the salient role of large-scale media attention on the course of movements, it is important to understand how some social movements in such conditions can attract global awareness. By extending the social movements literature to the global scale using world society theory, this study argues that biases in global civil society affect the chance of a domestic movement in attracting global awareness and becoming a worldwide human rights concern. Domestic movements aligned with world society scripts get picked up by international organizations, governments of other countries, international media, and to a lesser degree citizens of other countries. The process pushes a domestic struggle to the human rights stage by creating a globally resonant frame with high salience and credibility. The argument is tested by focusing on the prioritization of women’s rights over economic rights in global civil society with analysis of the international discourse regarding Women, Life, Freedom movement and Bloody November movement in Iran on both news media and social media using natural language processing methods. The findings show that global civil society turned the Women, Life, Freedom movement into a human rights concern in need of urgent global support by emphasizing on its women’s rights dimensions and minimizing its revolutionary and economic aspects. Conversely, the Bloody November movement, mainly framed as an uprising with economic roots and anti-systemic character, was not able to receive widescale international attention or support.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.022 | 0.027 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".