Writing the Self: The Autobiographical Subject as Language Construct. The Case of Lost in Translation. A Life in a New Language by Eva Hoffman
Bibliographic record
Abstract
This paper focuses on Lost in Translation: A Life in a New Language, a translingual memoir published in 1989 by Eva Hoffman (Ewa Wydra, at birth), a Polish writer who, aged thirteen, emigrated to Vancouver and then to the States, learnt English from scratch and finally became editor of the New York Review of Books as well as the most important contemporary Polish female writer in English. The translingual memoir is a fairly recent sub-genre in autobiographical writings which deals with immigrants’ recounting their progress from alienation towards integration into the host culture. This progress revolves around a process of language acquisition, or, as Hoffman’s memoir title signals, of translation by which the migrant gradually loses her mother tongue to acquire the language of her host country. Being a writer, and thus well aware of the fact that discourse is constitutive of, and determined by identity, Hoffman starts from the general assumption that “nothing fully exists until it is articulated” and moves on to explore the ways in which the close interrelation between “languaging” and the Self is re-defined and adapted to a post-modern bilingual context, in which individuals are more and more often divided between two cultures, languages and nations. Through a detailed functional linguistics analysis of the roles of the two “I”s in the memoir (the cognitive active “I” of the author, who knowingly presides over her writing, and the narrativized “I” as the passive object of the language she does not know but in which “[she has] been written”), this paper shows that acts of designation and translation construct a split subject and, at the same time, function as a bridge that connects the subject’s linguistic and social status. Thus, the analysis of Lost in Translation makes a significant contribution to the exploration of migrants’ identities through “translation” – intended, in one of its etymologies, as a tool to represent the identity of a split subject who has been “carried across” different countries, cultures and languages.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.009 | 0.050 |
| Scholarly communication | 0.011 | 0.015 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.002 | 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".