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Record W4385188443 · doi:10.20355/jcie29538

Tracing the Lines of Power, Coloniality, and Neoliberalism in UNESCO’s Education for Sustainable Development Policy

2023· article· en· W4385188443 on OpenAlexaffvenue
Marwa Younes, Leticia Nadler Gomez

Bibliographic record

VenueJournal of Contemporary Issues in Education · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Education and Sustainability
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsEducation for sustainable developmentIndigenousNeoliberalism (international relations)Sustainable developmentSociologyDiversity (politics)Power (physics)Environmental ethicsPolitical scienceEngineering ethicsSocial scienceLawEngineering

Abstract

fetched live from OpenAlex

This paper critically analyses a reflection paper commissioned by the United Nations Educational, Scientific and Cultural Organization (UNESCO) that proposes a future where we, humans, learn to coexist with the non-human world and thereby contribute to its preservation. The paper, titled Learning To Become With the World: Education for Future Survival, represents a response to previous unsuccessful Education for sustainable development (ESD) initiatives. Drawing on Carol Bacchi’s (2009), “What’s the problem represented to be?” method, our analysis sheds light on assumptions and silences and considers potentially conflicting interests among different actors in formulating the policy proposed by the paper. Through this critical approach to analysis, several crucial implications have emerged. We argue that the report lacks practical applicability by ignoring human complexities and diversity and does not pay enough attention to the potential important role Indigenous ways of knowing, learning, and teaching could play for education for sustainable development.

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 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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.063
Threshold uncertainty score0.303

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
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 head0.014
GPT teacher head0.329
Teacher spread0.315 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations3
Published2023
Admission routes2
Has abstractyes

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