Beyond the Book: The Periodical as an ‘Excavation Site’ for Translation Studies
Bibliographic record
Abstract
The present study starts with a theoretical and methodological discussion in an effort to approach the periodical as a composite genre formed through a range of interacting discourses and networks including translations and translators. It traces the position and role of translation and translators within the broader makeup of the periodical and its metanarrative. In light of the framework outlined in the first part, the second part elaborates on a popular, long-lasting Turkish film magazine, Yıldız [Star] (1938-1954) as a translational product and institution. The analysis of a film magazine as a case study adds further layers to the study and allows for multidisciplinary cross-fertilization and dialogue across translation, periodical, and film studies. Siting Yıldız vis-à-vis the socio-cultural and political context of the era and a large network of relations, this part reveals the substantial contribution of the translational habitus of the magazine to the construction and maintenance of its “common habitus” (Bourdieu 273; Philpotts). It also becomes evident that translation does not only contribute to the formation of the heteroglossic structure of Yıldız but also plays a significant part in shaping its metanarrative, which is highly relevant to the Turkish experience of American modernity presented by classical Hollywood films and stardom. Keywords: translation history, periodical studies, film magazine, translational habitus, common habitus
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.008 | 0.015 |
| Scholarly communication | 0.010 | 0.009 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".