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Record W2115367751 · doi:10.2304/elea.2007.4.3.355

At the Edge of Reason: Teaching Language and Literacy in a Digital Age

2007· article· en· W2115367751 on OpenAlexaffabout
James Nahachewsky

Bibliographic record

VenueE-Learning and Digital Media · 2007
Typearticle
Languageen
FieldArts and Humanities
TopicLiteracy, Media, and Education
Canadian institutionsUniversity of Winnipeg
Fundersnot available
KeywordsSituatedLiteracyPedagogyReading (process)SociologyCritical literacyThe artsLanguage artsPostmodernismMathematics educationPsychologyVisual artsLinguisticsComputer scienceArtLiterature

Abstract

fetched live from OpenAlex

Canadian schools are witnessing widening gaps between traditional definitions of literacy, which include reading and writing, and contemporary literacy practices like interactive multimedia use and online communications. Language and literacy teachers are called upon daily to bridge these contradictions through the pedagogical and textual choices they make in their classrooms. This article reports work in a study funded by Canada's Social Sciences and Humanities Research Council (SSHRC). This study comprised a qualitative inquiry into three teachers' experiences and textual stances of authority within the rapidly evolving environment of language arts classrooms. Situated understandings of the teachers' personal and professionally situated literacies complicated their daily pedagogical and textual choices. Theorized divisions between modernist literacy approaches and evolving postmodern practices emerged as a more complex set of discourses within the contact zone of contemporary language arts classrooms than originally anticipated, including a ‘horizontality’ to the classes' critical literacy practices. These findings have implications for the education of pre-service teachers, the development of literacy pedagogy, and the continuing debate as to what it means to be literate in today's information society.

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)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.871
Threshold uncertainty score0.394

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0230.025
Scholarly communication0.0090.005
Open science0.0010.005
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.010
GPT teacher head0.248
Teacher spread0.238 · 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 designTheoretical or conceptual
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

Citations3
Published2007
Admission routes2
Has abstractyes

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