NECROGEOGRAPHIES: War, Mourning, and the Aesthetics of Allegory in Gohar Dashti’s Photographs
Bibliographic record
Abstract
Iranian artist Gohar Dashti has stories to tell: of the Iran–Iraq War and its afterlife for her generation, in Today’s Life and War (2008), of bodies and of how bodies collect to create narrative spaces and relay tales of relationships in a constrained world, in Iran, Untitled (2013). These photographic series elucidate how in postrevolutionary Iran, the ubiquitous dissemination of images of martyrs and religious figures has played into the public/private divide, prioritizing certain social practices and affects as a result. The series also highlight the ambiguous nature through which these images operate, i.e., how a self-surveilling opto-architectural order has been imposed by the state upon the everyday practices of Iranians—a “necropticon” that functions through the overmarked nature of martyrdom. The same affects conjured up in “the sociality of mourning,” however, facilitate the formation of alternative modes of collectivity, as mourning and war offer valuable lessons in holding space together, generating rehearsal spaces—the allegorical mosque and battlefield—to practice collective political protest on the street. This model is long familiar to Iranians, as is abiding with the dead, and it is through their coupling that revolutionary counter-moods are born and bred.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.010 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".