The Politics of Calendars: State Appropriations of the Contested Iranian Past
Bibliographic record
Abstract
This paper seeks to investigate how commemorative practices, rituals, and holidays are invented, deployed, and recast for political and ideological purposes, to reinforce and sustain a particular narrative of national identity. It argues that the choice of particular moments of a country’s past to be commemorated in calendars as national holidays and the way in which the collective past is preserved and remembered both reflect and articulate a country’s vision of its present essence, of who its people are. Recognizing the link between the collective memory and national identity, the Iranian states before and after the 1979 revolution made a special effort to articulate their narrative of the past by commemorating a particular set of holidays and rituals. Viewing the calendar as a political artifact, this paper compares changes in the Iranian national calendars in the Pahlavi era (1925–1979) and the Islamic Republic (1979–2018). It examines the inclusion of new religious holidays and the removal of national days associated with the monarchy as well as the assignment of new meanings and celebratory practices to the old ones as the signifiers of a political maneuver to articulate a new shared public memory and narrative of identity since the 1979 revolution. It then examines two nationwide celebrations before and after the 1979 revolution, representing two state-sponsored, competing narratives of Iranian identity: firstly, the 2500-year celebration of the Persian Empire in 1953, and, secondly, the Ashura commemoration, a religious gathering dedicated to the remembrance of Shia Imams. These commemorations provided the state a unique political opportunity to present its own appraisal of the past and, in turn, national identity.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 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".