Bibliographic record
Abstract
The tragic death of Zhina (Mahsa) Amini in September 2022 sparked the largest national movement in Iran since 2009. Iranian Women became the symbolic center and main actors of this movement, with the Kurdish slogan “Woman, Life, Freedom” emerging as its defining motto.. This paper presents a theoretical and exploratory reflection on the “Woman, Life, Freedom” (WLF) movement, focusing on how social media, as a medium, shaped its mainstream representations and trajectory. After a brief genealogical analysis of discourses that place women’s veiling at the core of Iranian national politics, the paper examines how the hyperreal nature of modern reality influences social movements. It argues that social media amplifies the visibility of “hyperreal political subjects,” making them dominant actors in the movement. This transformation of political subjectivity imposed the structural limitation of social media not only on representation but also on the “presence” of political actions. Finally, the paper explores how social media facilitates revolutionary and polarized political strategies, enabling the dismantling of dominant hegemonies while simultaneously discouraging radical and progressive political imagination in building counter-hegemonic discourses.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.022 |
| Scholarly communication | 0.013 | 0.013 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".