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Record W2083385648 · doi:10.1177/1477570006067780

Writing as a form of 'survival' in Franco-America Translingualism, memory and identity in Robert B. Perreault and Normand Beaupré

2006· article· en· W2083385648 on OpenAlexaboutno aff
Peggy Pacini

Bibliographic record

VenueComparative American Studies An International Journal · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsPrideIdentity (music)StorytellingIdeologyNarrativeSociologyFace (sociological concept)ImmigrationMedia studiesCode (set theory)LinguisticsLiteratureLawAestheticsPolitical scienceArtSocial scienceComputer science

Abstract

fetched live from OpenAlex

An issue lying at the core of analyses of ethnic writing is the way that the question of identity often generates a dialogue between writing and being. American literature in languages other than English engages with this dialogue, though the nature of this engagement is rarely given appropriate recognition in American Studies. As a step towards redressing this neglect, this article focuses on two contemporary Franco-American writers, both third-generation immigrants, Normand Beaupré and Robert B. Perreault, who choose to write in the language of their ancestors, French. In doing so, they not only cope with a pride rooted in la survivance, the ideology that used to define their community, but also attempt to link their narrative to a Québec storytelling tradition. In choosing to express themselves in their native French, they try to demarginalize it and to bring their native voice back to the center. Their works also aim at tackling the issue of code-switching, of working with a mixed and impure language – an issue which has forced many Franco-American novelists to write in English rather than in French.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.819
Threshold uncertainty score0.361

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0130.013
Scholarly communication0.0080.003
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.036
GPT teacher head0.387
Teacher spread0.351 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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

Citations2
Published2006
Admission routes1
Has abstractyes

Explore more

Same venueComparative American Studies An International JournalSame topicCanadian Identity and HistoryFrench-language works237,207