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Record W4225006895 · doi:10.1177/17461979221080606

Global citizenship education as a project for decoloniality

2022· article· en· W4225006895 on OpenAlexaff
Thashika Pillay, Carrie Karsgaard

Bibliographic record

VenueEducation Citizenship and Social Justice · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Education and Multiculturalism
Canadian institutionsUniversity of AlbertaQueen's University
Fundersnot available
KeywordsDecolonialityCitizenshipWhite (mutation)SociologyResistance (ecology)Economic JusticeGlobal citizenshipPoliticsRelation (database)White paperEpistemologyGender studiesSocial scienceEnvironmental ethicsColonialismPolitical scienceLaw

Abstract

fetched live from OpenAlex

Youth from every continent used online tools to exchange ideas, debate alternatives, and create a document that represents their voice on the relationship education should have with global citizenship: the International Youth White Paper on Global Citizenship. This paper applies de Sousa Santos’ sociology of absences and emergences to trace the ways in which the White Paper extends—and limits—decolonial thought in relation to global citizenship education. Through document analysis of the White Paper, we note particularly the students’ emphasis on a decolonial and processual notion of relationality that challenges current neoliberal notions of the global community and instead is oriented toward justice. Further, the students connect political resistance to epistemological resistance, asserting that diverse ways of being, knowing, and seeing are necessary to ensuring those who are marginalized are included in the decision making processes that affect their lives.

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)0.017
metaresearch head score (Gemma)0.008
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 score0.017
Threshold uncertainty score0.088

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0130.023
Scholarly communication0.0100.008
Open science0.0010.022
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0080.001

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 head0.047
GPT teacher head0.406
Teacher spread0.359 · 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

Citations11
Published2022
Admission routes1
Has abstractyes

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