Bibliographic record
Abstract
Abstract With the radical political change in 1979, Iran's revolutionary state assumed the responsibility of re‐rewriting the past history to forge a new sense of belonging, a particularly collective religious (Shia) identity. It launched a complex process of forgetting and remembering to first eliminate the national (Persian), non‐religious memories and heritage, associated and celebrated by the previous regime and then establish a sense of continuity with the country's Shia past; a feeling markedly engendered with a distinguishing symbolic reservoir of Shia traditions and memories, presented in history books, literature, the media, and everyday culture.This paper seeks to examine the role of street names in this process of reconstructing a new religious (Shia) collective memory and identity with particular reference to Tehran, Iran, during the 1979‐2019 period. It seeks to analyze changes in the city's street names and analyze the widespread renaming of streets and public spaces in the city as one means of both ‘de‐commemorating’ the pre‐revolutionary regime and marking the Shia legacy and memories as the signifiers of a widespread political maneuver to articulate a new version of the past and narrative of identity since the 1979 revolution.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.009 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".