Of Frames and Wonders: Translation and Transnationalism in the work of Janette Turner Hospital
Bibliographic record
Abstract
Author Janette Turner Hospital has been claimed as Australian, Canadian and American. She grew up in Brisbane, travelled extensively as an academic through England, France and India, and now lives in South Carolina. She actively renounces any national ties, and is what some critics would call a “transnational writer”. Her work reflects this ideology, dealing with notions of place and identity in a globalised community. The field of translation studies has seen a recent burgeoning interest in notions of spatial disruption in a transnational society. Theorists have questioned where the act of translation sits in relation to the geographical, temporal and ideological place of the translator, locating it in a liminal space “in between” or on a transcended level “beyond”. While Sherry Simon has noted the lack of studies on translation within transnational spaces, the same could be said of studies of Hospital. Just as questions of language can be seen as central to a globalised society, so they can be seen as central to her narratives. Taking as a springboard previous work on Hospital which has highlighted links between her writing and the discourse of transnationalism, this article explores how translation functions thematically in her short story “Frames and Wonders”. Ultimately it seeks to present Hospital’s narrative as a ‘tentative model’ (West-Pavlov, 2001) of the relation between translation and transnationalism.
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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 | 0.011 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.024 | 0.058 |
| Scholarly communication | 0.015 | 0.009 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.004 | 0.008 |
| 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".