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Record W3126506988 · doi:10.7202/1075724ar

EDUCATIONAL CHANGE AND RETHINKING DISCIPLINARITY: A CONCEPT ANALYSIS

2021· article· en· W3126506988 on OpenAlexaffvenueabout
Aron Rosenberg, Lisa Starr

Bibliographic record

VenueMcGill Journal of Education / Revue des sciences de l éducation de McGill · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicCollaborative Teaching and Inclusion
Canadian institutionsMcGill University
Fundersnot available
KeywordsRelevance (law)Meaning (existential)Context (archaeology)SociologyEpistemologyDisciplineConceptual changeFocus (optics)Educational researchEngineering ethicsSocial sciencePedagogyPolitical scienceEngineeringGeography

Abstract

fetched live from OpenAlex

This article analyzes the potential for reshaping disciplinary divides by engaging with theories and movements that relate to educational change. Generating educational structures that diverge from conventional discipline-based models are a common way of attempting contemporary educational reforms. Interdisciplinary approaches are analyzed in this paper relative to theories of change in the context of secondary level education, with a focus on Québec, Canada. The purpose of this article is to understand and give meaning to the concept of interdisciplinarity within educational change and reform. This exploration proposes a conceptual map for understanding educational change efforts that aim towards rethinking disciplinarity. A model case, NEXTschool, is included to illustrate the applied relevance of the theories and ideas explored in this paper.

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)0.011
metaresearch head score (Gemma)0.009
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: Empirical
Teacher disagreement score0.035
Threshold uncertainty score0.151

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0070.005
Science and technology studies0.0090.044
Scholarly communication0.0110.011
Open science0.0020.007
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0020.000

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 head0.404
GPT teacher head0.476
Teacher spread0.072 · 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

Citations2
Published2021
Admission routes3
Has abstractyes

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Same venueMcGill Journal of Education / Revue des sciences de l éducation de McGillSame topicCollaborative Teaching and InclusionFrench-language works237,207