Subversion in Visual and Verbal Paratexts. A Case Study of the Translation of a Contemporary Chinese Artist’s Biography
Bibliographic record
Abstract
Translation has long been integral to the circulation of art between the East and West (Whyte and Heide, 2011, p. 47). Classical Chinese art was first introduced to the West when a history of classical Chinese painting was translated into English (ibid., pp. 46-47). As indicated by the plethora of books and articles published on the subject, there is now widespread interest in contemporary Chinese art, which has achieved international acclaim since the 1990s. This paper draws on existing scholarship in translation studies and political science to analyze four types of paratext (title, cover design, epigraphs, and translator’s preface) in a biography of contemporary Chinese artist Zhang Xiaogang. Based on a comparative visual and verbal paratextual analysis, the paper examines the re-construction of the original title and cover design for the English translation of Zhang’s biography. In this “paratranslation” (Pellatt, 2013a), the translator subverts what Valerie Pellatt calls an “Occidentalist approach” in two ways: first, by privileging the source culture—China’s soft power—over the Western target readership and, second, by explicitly but subtly using rhetorical and narrative devices to convey his own social-political stance. The translated paratexts thus perform multiple functions. They promote the state’s soft power by constructing an image of an underground artist whose work, by resisting autocracy, was once suppressed by the state but is now acclaimed both nationally and internationally. Simultaneously, the translation provides a space for the translator’s voice. This study reveals the importance of translation to scholarship on contemporary Chinese art, which here goes beyond translation itself by giving the translator a voice to advocate for social awareness.
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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 | 0.004 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.009 | 0.016 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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".