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Record W4409049808 · doi:10.3390/youth5020034

Relational Pathways to Sociopolitical Control: A Mixed-Methods Study

2025· article· en· W4409049808 on OpenAlexafffundabout
Kathryn Y. Morgan, Katherine Wiley, Brian D. Christens, A Clark, Colleen Loomis

Bibliographic record

VenueYouth · 2025
Typearticle
Languageen
FieldHealth Professions
TopicCommunity Health and Development
Canadian institutionsWilfrid Laurier University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsControl (management)BusinessPolitical scienceEnvironmental planningGeographyComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

Adolescence is a critical period for sociopolitical development, yet research has primarily focused on youth with explicit civic engagement, overlooking the role of community involvement in broader contexts. This mixed-methods study examines how adolescent community involvement—ranging from volunteering and advocacy to participation in sports, religious, and cultural activities—shapes sociopolitical control (SPC) in young adulthood. Using longitudinal quantitative survey data from 352 Canadian families, alongside qualitative interviews with 32 adult participants, we analyze how relationships with parents and peers mediate the link between community involvement and SPC. Regression analyses demonstrate that community involvement in high school predicts SPC at age 25, with parental support and positive peer relationships serving as significant mediators. Mediation analysis further reveals that relationships with mothers exert the strongest indirect effect on SPC, followed by relationships with fathers and peers. Qualitative findings highlight the mechanisms through which relational contexts foster or hinder SPC, illustrating that family values, peer norms, and early exposure to social issues shape long-term civic identity. These results underscore the importance of fostering relationally supportive environments that encourage diverse forms of adolescent community participation, contributing to both individual empowerment and broader democratic engagement.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.461
Threshold uncertainty score0.867

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.161
GPT teacher head0.514
Teacher spread0.353 · 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

Citations0
Published2025
Admission routes3
Has abstractyes

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