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Record W2277997784 · doi:10.1007/978-94-6209-932-6_5

Restructuring the Teacher Education Program at the Campus Saint-Jean of the University of Alberta

2014· book-chapter· en· W2277997784 on OpenAlexaffabout
Laurent Cammarata, Martine Cavanagh, Yvette d’Entremont

Bibliographic record

VenueSensePublishers eBooks · 2014
Typebook-chapter
Languageen
FieldArts and Humanities
TopicSecond Language Learning and Teaching
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsRestructuringSAINTFrenchFace (sociological concept)Work (physics)PedagogyPolitical scienceSociologyHumanitiesEngineeringHistorySocial scienceArtLaw

Abstract

fetched live from OpenAlex

The world is changing and teacher-training programs must be constantly renewed to meet the needs of future teachers who will have to face an educational situation that is increasingly complex. The Education Program at the Campus Saint-Jean (CSJ), a four-year baccalaureate program designed primarily to prepare students to teach in French-immersion and French first-language (or “Francophone”) schools, has recently undergone a major restructuring involving necessary changes to better meet the needs of future teachers who will work in complex linguistic-minority contexts that pose several unique challenges.

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)0.000
metaresearch head score (Gemma)0.000
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.982
Threshold uncertainty score0.686

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.001
Scholarly communication0.0020.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0280.004

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 head0.010
GPT teacher head0.190
Teacher spread0.179 · 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
GenreOther

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
Published2014
Admission routes2
Has abstractyes

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