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Digital Epistemologies and Classroom Multiliteracies

2008· book-chapter· en· W2499125907 on OpenAlexaffabout
Heather Lotherington

Bibliographic record

VenueIGI Global eBooks · 2008
Typebook-chapter
Languageen
FieldArts and Humanities
TopicLiteracy, Media, and Education
Canadian institutionsYork University
Fundersnot available
KeywordsSituatedPedagogyLiteracyNarrativeSociologyCurriculumSituated learningAction researchDigital literacyReciprocalAction (physics)Computer scienceLinguistics

Abstract

fetched live from OpenAlex

Contemporary conceptualizations of literacy as socially and culturally situated practice must be framed in our digitally-mediated, glocalized societies where networked communication technologies have created innovative texts opening up new literacies and demanding new pedagogies. This chapter discusses a Toronto-based program of collaborative school-university action research that aims to develop a pedagogy of multiliteracies in an urban elementary school. The project engaging our research collective is about guiding children to rewrite traditional children’s stories as individualized digital narratives that enfold their cultural understandings and community languages. Situated within current epistemological questions about what it means to become a literate person in the 21st century, our project responds to reciprocal educational challenges: How can we facilitate the acquisition of relevant literacies for contemporary children experiencing divergent home, school, community and societal practices? How can we redesign curricula and assessment to be socially responsive and responsible?

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)0.005
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: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.017
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0060.047
Scholarly communication0.0170.013
Open science0.0010.013
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0060.001

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 head0.031
GPT teacher head0.235
Teacher spread0.204 · 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

Citations5
Published2008
Admission routes2
Has abstractyes

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