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Record W3032044781 · doi:10.1080/01596306.2020.1769939

‘Enabled to play, enabled to explore’: children’s civic engagement, literacies, and teacher professional learning

2020· article· en· W3032044781 on OpenAlexafffund
Lori McKee, Rachel Heydon

Bibliographic record

VenueDiscourse Studies in the Cultural Politics of Education · 2020
Typearticle
Languageen
FieldArts and Humanities
TopicLiteracy, Media, and Education
Canadian institutionsWestern UniversitySt. Francis Xavier University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsLiteracyPedagogyMeaning (existential)ExpansiveSociologyProfessional learning communityProfessional developmentCritical literacyTeaching methodCivic engagementPsychologyPolitical sciencePolitics

Abstract

fetched live from OpenAlex

Drawing from a multiple-case study of professional learning in literacy, this article presents vignettes from a Grade 1 classroom where the professional learning focused on multimodal literacy pedagogies that combined digital and print-based resources to expand children’s meaning-making. Linking children’s opportunities for expansive literacy options and civic engagement, we focus on a lesson cycle in one teacher’s engagement in the learning. We highlight how the teacher’s pedagogy of exploration positioned children as capable meaning makers and how the children’s innovative literacy practices informed the teachers’ understandings of literacy pedagogies. These findings forward grounded examples of classroom spaces for children’s meaning-making and civic engagement that are co-produced by multimodal and flexible pedagogies where children act as curricular-informants.

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.015
Scholarly communication0.0090.005
Open science0.0010.009
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0040.000

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 head0.127
GPT teacher head0.391
Teacher spread0.264 · 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

Citations4
Published2020
Admission routes2
Has abstractyes

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