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Record W2046369853 · doi:10.7202/019485ar

La construction identitaire par l’enseignement de la littérature acadienne dans les écoles secondaires du Nouveau-Brunswick

2008· article· fr· W2046369853 on OpenAlexaffvenueabout
Carole Boucher

Bibliographic record

VenueFrancophonies d Amérique · 2008
Typearticle
Languagefr
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsUniversité de Moncton
Fundersnot available
KeywordsHumanitiesPolitical scienceArt

Abstract

fetched live from OpenAlex

Dans tous les milieux minoritaires, la question identitaire fait surface, car inévitablement, une culture est dominante, l’autre est dominée. Cette dernière doit constamment se battre pour survivre et faire face à l’insé­curité culturelle. L’école étant un des premiers contextes sociaux structurés dans lequels s’insère l’enfant au cours du processus de cons­truction identitaire, nous aimerions démontrer que l’enseigne­ment en général, mais plus précisément la littérature et son enseignement, constitue un outil très important pour valoriser une culture. Nous ten­te­rons donc de déterminer dans quelle mesure le ministère de l’Éduca­tion du Nouveau-Brunswick perçoit les textes littéraires acadiens comme véhi­cules favorisant ce processus. En conséquence, nous exami­­­ne­rons les critères théoriques, littéraires et pédagogiques qui guident le Ministère dans son choix de textes, de même que sa percep­tion de l’appren­tissage de la culture en général, de la culture acadienne et de l’ouverture aux autres cultures.

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)0.003
metaresearch head score (Gemma)0.006
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 score0.116
Threshold uncertainty score0.538

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.004
Science and technology studies0.0120.014
Scholarly communication0.0070.004
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0090.000

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 head0.005
GPT teacher head0.199
Teacher spread0.193 · 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

Citations0
Published2008
Admission routes3
Has abstractyes

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