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Record W2964269669 · doi:10.1093/fs/knz194

<i>Mémoires d’outre-langue: l’écriture translingue de soi</i> . Par <scp>Alain Ausoni</scp> <i>Mémoires d’outre-langue: l’écriture translingue de soi</i> . Par AusoniAlain. Genève: Slatkine, 2018. 198 pp., ill.

2019· article· fr· W2964269669 on OpenAlexaffabout
Rainier Grutman

Bibliographic record

VenueFrench Studies · 2019
Typearticle
Languagefr
FieldArts and Humanities
TopicHistorical Linguistics and Language Studies
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsNothingOrder (exchange)ArtBiographyLiteratureHistoryHumanitiesArt historyPhilosophy

Abstract

fetched live from OpenAlex

In this beautifully written and timely study, originally defended as a doctoral dissertation at the University of Oxford in 2015, Alain Ausoni looks at six writers whose careers developed mainly or even exclusively in French, a language none of them mastered as children in their respective countries of origin but acquired as (young) adults. As such, this book is a neat French-language companion to Mary Besemeres’s Translating One’s Self: Language and Selfhood in Cross-Cultural Autobiography (Oxford: Peter Lang, 2002), which focused on writers who similarly adopted English as the medium of their artistic expression: Eva Hoffman, Czesław Miłosz, and Vladimir Nabokov. Writers who transit (or are transported) into an acquired language have been termed ‘translingual’, a label Ausoni borrows from Steven Kellman after some very welcome fine-tuning. The authors studied are, in order of their appearance: Andreï Makine (whose native language is Russian), Héctor Bianciotti (Argentinian Spanish), Vassilis Alexakis (Greek), Nancy Huston (Canadian English), Ágota Kristóf (Hungarian), and Katalin Molnár (Hungarian). All these men and women (three of each, as it happens) wanted and managed to become creative writers in French, and, for the most part, in France: even Kristóf, who fled her native Hungary for Switzerland, published her work in Paris. As Ausoni is well aware, there is nothing innocent about this ‘pacte exclusif avec la nation’ (to use a phrase from the much-debated 2007 Manifeste pour une littérature-monde). His chapter on Makine, for instance, convincingly shows the latter fashioning himself after other successful Russians such as Henri Troyat (the pen name of Moscow-born Lev Aslanovitch Tarassov) and in particular Romain Gary (born Roman Kacew in Vilnius, then Russian-ruled Lithuania). The fascination with French grandeur that runs through Makine’s Testament français indeed reminds one of similar obsessions displayed by the narrator’s mother in Gary’s Promesse de l’aube. The fact that both of these novels are also highly and openly autobiographical is no coincidence: like Besemeres, Ausoni detects a ‘demande d’autobiographie’ (p. 40), a clear connection between life writing and the translingual condition, almost as if writers who move into a new language were pressed (or felt the need) to explain themselves. By privileging such aspects as the choice of genre or the intertextual connections with other translingual writers, Ausoni succeeds in describing a francophonie that is not collective but individual, not the product of linguistic politics and policies (as is the case with much postcolonial or minority writing) but the work of writers whose bilingualism and consequent language choices cannot primarily be ascribed to (and explained by) sociolinguistic factors. Like Leo Spitzer, who similarly (albeit from the quite different vantage point of stylistics) preferred aesthetics as a way of accessing writers’ individualities, Ausoni might say, contradicting the old scholastic adage: individuum non est ineffabile.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.598
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0030.003
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0010.001
Science and technology studies0.0040.003
Scholarly communication0.0010.000
Open science0.0020.000
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0010.001

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.

Opus teacher head0.015
GPT teacher head0.246
Teacher spread0.231 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations1
Published2019
Admission routes2
Has abstractyes

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