Iran Reframed: Anxieties of Power in the Islamic Republic, by Narges Bajoghli
Bibliographic record
Abstract
W hat does it mean to be pro-regime in the Islamic Republic of Iran?Narges Bajoghli's Iran Reframed, the 2020 recipient of the Margaret Mead Award, offers a rare, in-depth look at Iran's pro-regime media producers at a time when they face a crisis of credibility: Iran's youth, who comprise the majority of the population in the country, do not remember (and therefore do not understand) the Islamic Republic's revolutionary stories.Drawing on a decade of fieldwork in Iran among various groups of regime supporters and eighteen months of ethnographic research with their media producers specifically, Bajoghli highlights these men's struggles to "transmit the commitment to their revolutionary project" to younger generations and illustrates what is at stake for them in keeping the revolution alive (5).Bajoghli's ethnographically-rich analysis challenges entrenched stereotypes about Iran's regime supporters, demonstrating that they are far from homogenous, cohesive, unchanging, and all-powerful.
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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 | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".