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Record W4411068339 · doi:10.53967/cje-rce.7153

Nurturing Identity, Shaping Communities, and Forging New Pathways: Racially Minoritized Youth Climate Justice Activists’ Perspectives

2025· article· en· W4411068339 on OpenAlexaffvenueabout
Rupinder Kaur Grewal, Paul D. Berger

Bibliographic record

VenueCanadian Journal of Education / Revue canadienne de l éducation · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicYouth Development and Social Support
Canadian institutionsLakehead University
Fundersnot available
KeywordsIdentity (music)Gender studiesSociologyEconomic JusticeClimate justicePolitical scienceCriminologySocial justiceClimate changeLawEcologyAesthetics

Abstract

fetched live from OpenAlex

This study explores the experiences of racially minoritized youth activists involved in the climate justice movement. From July to October of 2023, I conducted semi-structured narrative interviews with 15 Black, Indigenous, and youth of colour in Ontario, aged 18 to 29, who had been affiliated with a climate justice organization for at least six months. Through timeline mapping and semi-structured interviews, participants highlighted pivotal life events that shaped their justice-oriented values. Three overarching themes emerged: nurturing identity, shaping communities and schools, and forging new pathways for racially minoritized youth leaders. The findings underscore the empowerment youth experience through local action and community engagement. With a grounding in relational solidarity and ethical relationality, this study emphasizes the imperative for Canadian education systems to integrate robust climate justice pedagogies as well as interdisciplinary, action-oriented climate justice learning that fosters student efficacy and leadership. The study also aims to highlight the ways educators, policy makers, and stakeholders can engage with climate justice, informed by racially minoritized activists.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.655
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
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 head0.094
GPT teacher head0.330
Teacher spread0.236 · 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.

Study designQualitative
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
Published2025
Admission routes3
Has abstractyes

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