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Record W3087661107 · doi:10.63997/jct.v35i2.841

Visualizing mapping as pedagogy for literacy futures

2020· article· en· W3087661107 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Curriculum Theorizing · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous and Place-Based Education
Canadian institutionsMount Saint Vincent University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsFutures contractLiteracyPedagogySociologyBusiness

Abstract

fetched live from OpenAlex

In this article, the authors explore mapping as a pedagogical approach. Drawn from two literacy classrooms, the authors report on five empirical examples of mapping, elucidating the ways in which mapping activities were sites of dynamic meaning-making through processes of deterritorialization and reterritorialization (Deleuze & Guattari, 1987). In both cases of mapping pedagogy, participants used mapping to interrogate texts, reflect on experiences, express identity, and locate emotions as language learners and readers. Employing visual analysis to ‘think with theory,’ the authors provide a coordinate plane to map the pedagogical dimensions of mapping across the five empirical examples. The authors illustrate the ways students gravitated across a continuum of literal to metaphorical visual depictions of their learning and life experiences. This inquiry offers new ways of theorizing thematic mapping of learning and experience for classroom practice.

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.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.707
Threshold uncertainty score0.699

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
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 head0.027
GPT teacher head0.393
Teacher spread0.366 · 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