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Record W1531187203 · doi:10.4000/lisa.2675

A Short Story from Canada in the German EFL-Classroom — “Borders” or a Sense of Belonging in a Multicultural Society

2005· article· en· W1531187203 on OpenAlexaffabout
Albert Rau

Bibliographic record

VenueRevue LISA / LISA e-journal · 2005
Typearticle
Languageen
FieldArts and Humanities
TopicTranslation Studies and Practices
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsHumanitiesArtGermanGerman cultureEthnologySociologyPhilosophyLinguistics

Abstract

fetched live from OpenAlex

Depuis quelques années, l’apprentissage interculturel joue un rôle central dans l’enseignement de l’anglais langue étrangère. Au lieu de divulguer uniquement des informations factuelles relatives à un pays étranger, l’apprentissage interculturel vise à comprendre une culture, un monde qui diffère du sien. Une façon d’appréhender une culture étrangère peut se faire en lisant sa littérature car les textes littéraires n’offrent pas seulement un sentiment d’empathie envers les personnages ou une impression de vivre leur quotidien par procuration, ils suscitent des questions et des réponses de la part des étudiants. La littérature canadienne se prête bien à l’apprentissage interculturel car les grandes interrogations portant sur le contexte socio-culturel canadien servent de modèles aux étudiants. La nouvelle Borders de Thomas King en est un exemple. Elle relate le vécu d’une famille nouvellement établie, piégée dans un terrain vague situé aux confins du Canada et des Etats-Unis, une famille désireuse de préserver son identité « pied noire » (Blackfoot).

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)0.001
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 score0.093
Threshold uncertainty score0.678

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0520.016
Scholarly communication0.0130.004
Open science0.0020.005
Research integrity0.0040.008
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 head0.037
GPT teacher head0.280
Teacher spread0.243 · 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
Published2005
Admission routes2
Has abstractyes

Explore more

Same venueRevue LISA / LISA e-journalSame topicTranslation Studies and PracticesFrench-language works237,207