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Record W2994809019 · doi:10.3828/qs.2019.21

Les multiples appartenances à la Franco-Amérique: <i>Bondrée</i> d’Andrée A. Michaud

2019· article· fr· W2994809019 on OpenAlexaffabout
Maria Cristina Greco

Bibliographic record

VenueQuebec Studies · 2019
Typearticle
Languagefr
FieldSocial Sciences
TopicMigration, Health, Geopolitics, Historical Geography
Canadian institutionsUniversité de Moncton
Fundersnot available
KeywordsMultiplePhysicsMathematicsArithmetic

Abstract

fetched live from OpenAlex

Après que de nombreux travaux ont considéré la question de l’américanité de la littérature québécoise, des analyses récentes ont mis en avant le retour de l’identité canadienne-française. On entre ainsi dans la dynamique de la franco-américanité. De nombreux auteurs, en effet, ont choisi d’exprimer cette identité canadienne-française par le biais de leur écriture, entre autres la lauréate du Prix littéraire du Gouverneur général, Andrée A. Michaud. De nos jours, la redécouverte de cette Amérique francophone est de plus en plus manifeste: il s’agit d’une identité refoulée qui revient et qui apporte un renouveau du discours sur l’américanité. C’est dans ce contexte d’équilibre dynamique que se situe notre réflexion, soit une lecture américaine et franco-américaine, ou plutôt frontalière, du roman policier Bondrée (2014). Notre réflexion vise à montrer que Bondrée appartient de plein droit à cette tendance du roman de la Franco-Amérique contemporaine. En analysant les différentes manifestations de la frontière, l’utilisation de l’onomastique, la quête du père et, enfin, des traces d’américanité et d’européanité, nous verrons que Bondrée constitue en fait une fiction emblématique de la Franco-Amérique.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.470
Threshold uncertainty score0.934

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.005
Scholarly communication0.0040.003
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0100.001

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 head0.035
GPT teacher head0.325
Teacher spread0.291 · 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 designNot applicable
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

Citations0
Published2019
Admission routes2
Has abstractyes

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