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Record W268312642 · doi:10.5206/cie-eci.v38i1.9124

Literacy, Diversity and Education: Meeting the Contemporary Challenge

2009· article· en· W268312642 on OpenAlexafffundvenueabout
Marie Josée Berger, George Die, René Forgette-Giroux

Bibliographic record

VenueComparative and International Education · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicParental Involvement in Education
Canadian institutionsUniversity of TorontoUniversity of Ottawa
FundersMinistère de l’Éducation, Gouvernement de l’OntarioBộ Giáo dục và Ðào tạo
KeywordsSociologyPedagogyLiteracyPopulationCurriculumDiversity (politics)HumanitiesAnthropologyArtDemography

Abstract

fetched live from OpenAlex

The changing nature of our classrooms in terms of students’ racial population demands an understanding and validation into the different ways in which various ethnocultural and Aboriginal students respond to schools, classroom environments, curricula, and teaching strategies to ensure academic success. This paper is part of a larger study that examines literacy and diversity in relation to the educational challenges in Ontario schools. The focus of this paper is on a qualitative case study involving twenty educators. The study’s findings reveal educators’ articulations with regards to the connections between equity, diversity and multiple literacies. La nature changeante de nos salles de classe en termes de la population raciale des étudiants exige une compréhension et une validation des différentes manières auxquelles les divers étudiants ethnoculturels et indigènes répondent aux écoles, aux environnements de salle de classe, aux programmes d’études, et aux stratégies d’enseignement pour assurer le succès scolaire. Ce travail fait partie d’une étude plus large qui examine la littératie et la diversité dans les écoles ontariennes par rapport aux défis éducationnels. Le travail met l’accent sur une étude de cas qualitative impliquant vingt éducateurs. L’étude révèle les articulations des éducateurs en ce qui concerne les liens entre l’équité, la diversité et les littératies multiples.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.373
Threshold uncertainty score0.958

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.208
GPT teacher head0.443
Teacher spread0.235 · 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 teacher head, 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

Citations4
Published2009
Admission routes4
Has abstractyes

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