Comics Polysystem in Iran: A Case Study of the Persian Translations of Les Aventures de Tintin
Bibliographic record
Abstract
Despite the popularity of comics, the subject of their translation has remained notably underexplored. Comics swept into the market of Iran in the 1970s; however, they were a new and unfamiliar genre in the country. One of the earliest comic series to appear in Iran was Les Aventures de Tintin, translated by Khosro Sami’i and published by Universal Publications before the Islamic Revolution of Iran in 1979. Following the Revolution, Universal discontinued the series in Iran and other publishers briefly took it up; after a few years, publication of the books was discontinued. It was not until 2000 that the series was re-introduced by Tarikh-o Farhang and Andishe-ye No Publications. Moreover, as a result of the ubiquitous availability of comic books on the Internet, scanlations made by Tintinophiles have burgeoned recently. This study examines the translations into Persian of Les Aventures de Tintin from these three groups (the early editions of the 1970s and 1980s, the revived publications of 2000, and the Internet scanlations) and attempts to shed light on the position of comics in the translated polysystem of Iran. For this purpose, Even-Zohar’s Polysystem theory (“Polysystem Studies” 9-26) and Tamaki’s approach (119-146) are employed. The synthetic model of translation description proposed by Lambert and Van Gorp (42-53) is used to examine the translations in three layers: 1) preliminary data, 2) macro-level, and 3) micro-level. Onomatopoeic representations are analysed at the micro-level to investigate the extent to which their translations have broken target culture norms and conventions. The results of the study reveal a gap for comics, an empty niche to be filled, in the translated polysystem of Iran and, accordingly, a canonized position for this genre and its translations. This position, however, has migrated to a less central place in more recent translations.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".