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Record W3201537365 · doi:10.32873/unl.dc.ffsc.010

Suivre le lilas et l’engoulement d’Amérique – vers une identité transmigrante dans La route du lilas par Éric Dupont

2020· article· fr· W3201537365 on OpenAlexaffabout
Simona Emilia Pruteanu

Bibliographic record

Venuenot available
Typearticle
Languagefr
FieldArts and Humanities
TopicLinguistics and Discourse Analysis
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsHumanitiesArtPhilosophy

Abstract

fetched live from OpenAlex

Le plus récent roman d’Éric Dupont, La route du lilas (2018), a déjà été acclamé comme un « road-trip féministe » ou « une véritable fresque féministe et horticole » (Sylvie Mousseau 2019). Alors que ce serait difficile de résumer les intrigues complexes étalées sur 600 pages, cette communication se propose d’étudier le concept d’identité transmigrante chez l’un des trois personnages principaux féminins : Maria Pia, une Brésilienne en fuite, essaie de rejoindre la Gaspésie aidée par Shelly et Laura, qui, chaque année, suivent la floraison du lilas en Amérique du Nord. Nous empruntons l’idée d’identités transmigrantes aux travaux de Gilles Dupuis qui, en analysant les contacts entre le corpus québécois ainsi dit « de souche » et les écritures migrantes, y voit la preuve d’une identité qui transmigre à travers le style. (« Identités transmigrantes » 2013). Le voyage de Maria Pia, dans le temps et dans l’espace, commence au Brésil, passe par la France, touche brièvement les États-Unis pour aboutir au Québec. Ce voyage qui lie le nord et le sud du continent américain, en faisant un détour par l’Europe, grâce aux « flash-backs », s’inscrit pour nous dans un projet esthétique transaméricain que nous avons défini ailleurs comme « le nouveau métarécit québécois » (Pruteanu 2016). Nous analyserons de quelle manière le roman de Dupont s’inscrit dans le genre de ce nouveau métarécit dans lequel « chaque individu traverse des frontières qui le traversent à leur tour » (Patrick Imbert 2011). Éric Dupont’s latest novel, La route du lilas (2018), has already been acclaimed as a « feminist road-trip» and a « true feminist and horticultural fresco » (Sylvie Mousseau 2019). While it would be difficult to summarize the complex various plots spread over 600 pages, this communication aims to study the concept of transmigrant identity embodied by one of three main female characters: Maria Pia, a Brazilian on the run, tries to reach the Gaspé Peninsula in Québec, with the help of two Americans, Shelly and Laura, who, every year, follow the journey of the blossoming lilac in North America. The concept of transmigrant identity belongs to Gilles Dupuis who, after examining literary connections between the Quebec literary canon, the so called « de souche », and the migrant one, argues the existence of an identity which permeates the writing style. (« Identités transmigrantes», 2013). Maria Pia’s journey through time and space, begins in Brazil, continues

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: yes
Not applicablelow
gptno category
Domain: not available · Genre: Other
About the Canadian research system: no · About a Canadian topic: yes
Theoretical or conceptualhigh
models splitAgreement compares identical category sets and study designs across arms.

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)0.001
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: none
Teacher disagreement score0.467
Threshold uncertainty score0.928

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0110.010
Scholarly communication0.0060.004
Open science0.0010.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0120.001

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 head0.018
GPT teacher head0.235
Teacher spread0.217 · 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

Labeled directly by 2 models reading the full record.

The models applied no category: nothing in the taxonomy fit this work.

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designNot applicable · Theoretical or conceptual
Domainnot available
GenreEmpirical · Other

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

Citations0
Published2020
Admission routes2
Has abstractyes

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