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Record W3132284782 · doi:10.1080/14767724.2021.1882957

Using the SDGs for global citizenship education: definitions, challenges, and opportunities

2021· article· en· W3132284782 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.

Bibliographic record

VenueGlobalisation Societies and Education · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Education and Multiculturalism
Canadian institutionsMcGill University
Fundersnot available
KeywordsGlobal citizenship educationSustainable developmentCurriculumMainstreamingEducation for sustainable developmentCitizenshipGlobal citizenshipPerspective (graphical)Political scienceEngineering ethicsGlobal educationGlobal challengesSociologyPedagogyCitizenship educationSpecial educationComputer scienceEngineering

Abstract

fetched live from OpenAlex

The 17 United Nations Sustainable Development Goals (SDGs) employ a global indicator framework to detail each Goal and monitor its implementation. This article focuses on three targets from the indicator framework, which call for mainstreaming education for global citizenship, sustainable development, and climate change into national curricula. By investigating the practicalities of meeting these targets from an educator's perspective, this article proceeds with: arguing for a need to shift the central purpose of education; examining what is meant by education ‘for’ the three key areas included in the global indicator framework; exploring curricular opportunities offered by the SDGs; and presenting inquiry-based learning as a pedagogical approach for critically interrogating the SDGs with learners. If the SDGs are used to drive a pragmatic definition of global citizenship, then trends in education such as inquiry- and problem-based learning come to life with a clear and urgent purpose.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.747
Threshold uncertainty score0.948

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 studies0.0010.000
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 head0.313
GPT teacher head0.397
Teacher spread0.085 · 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