Suffering for/against the nation: <i>Gharbzadegi</i> and the tensions of anticolonialism in Iran
Bibliographic record
Abstract
What accounts for the nation’s persistence as a central object of identification in anticolonial movements during the 1960s? How can we understand the appeal of nationalism when it simultaneously could signify one path to and a pitfall of decolonisation, as Frantz Fanon warned? This article addresses some of these questions concerning anticolonialism, its political possibilities, decolonial fantasies and desires in Iran. I discuss how Jalal Al-e Ahmad articulated a diagnosis of cultural imperialism, gharbzadegi , that expressed tensions between the translocality to which his framework aspired and the rigid confines of the nation-state model. This imbroglio, I claim, reverberated through the pathologisation of the national group, with the wounds of colonial violence unsettling and reforming different national attachments in Iran. To support this argument, I read the specific conditions, dynamics and sociohistorical processes in which Al-e Ahmad was immersed alongside the transnational structures to which they were related. Juxtaposing this pathological discourse with his travelogues, we can grasp a specific articulation of the translocal-national dyad that informed Al-e Ahmad’s life and found expression in his limited theorisation of gharbzadegi . Analysing this particular context, I argue that this entanglement exposes the limits and pitfalls of anticolonialism in Iran. Souffrir pour/contre la nation : gharbzadegi et les tensions de l’anticolonialisme en Iran
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.028 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.001 | 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".