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Record W3123231591 · doi:10.4018/ijbide.2020070101

Plurilingualism and STEAM

2020· article· en· W3123231591 on OpenAlex
Daniel Roy Pearce, Mayo Oyama, Danièle Moore, Kana Irisawa

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.

Bibliographic record

VenueInternational Journal of Bias Identity and Diversities in Education · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicPeace and Human Rights Education
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsMultidisciplinary approachContext (archaeology)Openness to experienceReflexivityPedagogyNature versus nurtureDiversity (politics)SociologyPolitical scienceEngineering ethicsPsychologySocial scienceGeographyEngineering

Abstract

fetched live from OpenAlex

This contribution attempts to clarify the relationship between the practice of plurilingual education and STEAM (interdisciplinary pedagogy that incorporates science, technology, engineering, art, and mathematics) through the lens of peace learning at an elementary school in Japan. Japan has a rich history of peace education, although it has received limited focus in the international literature, whereas plurilingual education remains relatively unknown in the country. Within this context, the article examines a teacher-initiated plurilingual and intercultural project focused on a multidisciplinary approach to peace learning. Analyses of multimodal data, including video recordings, photographs, researchers' field notes, learners' journals, and semi-structured reflective interviews, will demonstrate how even within a highly homogenous context, practitioners can promote transferable skills and nurture a deeper awareness of language and openness to diversity, foster reflexivity, and encourage multidisciplinary engagement through plurilingual education, dialogue, and storying.

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)0.000
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.185
Threshold uncertainty score0.182

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 studies0.0000.000
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 head0.069
GPT teacher head0.372
Teacher spread0.302 · 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