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Record W4413494648 · doi:10.3390/socsci14090510

“Even the Small Work That I Do, It Has Impact, It Has Meaning”: Collective Meaning-Making in Youth Climate Groups

2025· article· en· W4413494648 on OpenAlexafffundabout
Julia L. Ginsburg, Natasha Blanchet‐Cohen

Bibliographic record

VenueSocial Sciences · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicYouth Development and Social Support
Canadian institutionsConcordia University
FundersConcordia University
KeywordsMeaning (existential)Work (physics)PsychologyMeaning-makingSociologySocial psychologyEngineeringPsychotherapist

Abstract

fetched live from OpenAlex

This article focuses on participation in youth-led climate-oriented groups and the role of this form of civic engagement for young people. Thirty interviews were conducted with 13- to 18-year-olds belonging to four groups: Extinction Rebellion Youth, Sustainabiliteens, Sunrise Movement, or school-affiliated clubs. The participants had been part of their group for an average of 1.5 years, coming from either the United States (n = 26) or Canada (n = 4). They were predominantly female (n = 22), with a few male (n = 5) and a small number identifying as non-binary (n = 3). Significant in the thematic analysis was the critical role of increased meaning-making, which involved relationship-building, processing emotions, and taking action. The peer-led group settings served to create community, work through the range of emotions the climate crisis evoked, and generate actions that felt purposeful at both the individual and collective levels. In these spaces, young people seek meaning together, and they propose and demand action from governmental bodies and corporations on climate change. Through everyday activism, young people express an ecocitizenship that is constructive, hopeful, and generative. In a world characterized by the climate crisis, joining and contributing to youth-led climate groups is becoming part of young people’s identity development, a way of enacting citizenship and expressing political agency.

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)0.006
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.642
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.005
Science and technology studies0.0120.003
Scholarly communication0.0020.000
Open science0.0010.000
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 head0.142
GPT teacher head0.361
Teacher spread0.220 · 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; both teacher heads agree on what is shown here.

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

Citations0
Published2025
Admission routes3
Has abstractyes

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