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Record W4404083629 · doi:10.1177/17461979241289280

Pedagogical principles for encouraging (socially just) youth climate action: A schema for citizenship education curriculum analysis

2024· article· en· W4404083629 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueEducation Citizenship and Social Justice · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Education and Multiculturalism
Canadian institutionsQueen's University
Fundersnot available
KeywordsCurriculumCitizenship educationCitizenshipPedagogySociologySchema (genetic algorithms)Action (physics)Action researchEnvironmental educationCurriculum developmentMathematics educationPsychologyPolitical sciencePolitics

Abstract

fetched live from OpenAlex

This article synthesizes pedagogical principles for supporting youth climate action from across local (Ontario) and global literature. It also seeks out stories of Indigenous youth engaging in climate action in distinct ways—highlighting examples from Sioux (of Standing Rock) and Inuit youth. The authors propose the Pedagogical Principles for Supporting Climate Action curriculum analysis schema before using it to examine the Ontario citizenship framework. The findings reveal how the curriculum segment in its current form is incongruent with the pedagogical principles of supporting youth climate action. The authors articulate both immediate and urgent curriculum revisions that are necessary for supporting youth in socially just climate action—with a call for immediate revisions that include a shift toward centering Indigenous knowledges, integrating climate justice and upholding relationality to the land and all that it sustains.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.709
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.000
Scholarly communication0.0010.000
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 head0.179
GPT teacher head0.453
Teacher spread0.274 · 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