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Record W4414993269 · doi:10.1177/23328584251375052

Examining the Role of a Program for Youth Advocates in Critical Consciousness Development

2025· article· en· W4414993269 on OpenAlexaff
Laura Wray‐Lake, Christopher M. Wegemer, Elan C. Hope, Kristina Cổ-Đoàn, Qin L. Kramer, Emily Greytak

Bibliographic record

VenueAERA Open · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicYouth Development and Social Support
Canadian institutionsUniversity of Toronto
FundersAmeriCorps
KeywordsCritical consciousnessAgency (philosophy)Critical thinkingPoliticsAction (physics)Program evaluationPositive Youth DevelopmentPolitical action

Abstract

fetched live from OpenAlex

The ACLU’s National Advocacy Institute (NAI) is a one-week residential program designed to build youth’s capacities to advocate for civil rights and challenge injustices. This study assessed its role in fostering adolescents’ critical consciousness. We surveyed NAI participants and a comparison group of engaged youth before, one week after (N = 58(NAI)/166(comparison)), and six months after the program (N = 47(NAI)/165(comparison)). Using difference-in-differences analyses with covariates, NAI youth increased their likelihood of taking low- and high-risk political actions after one week and high-risk action frequency after six months, relative to the comparison group. NAI youth increased three forms of critical agency one week and, marginally, six months post-program. No associations were found for critical reflection. As a robustness check, propensity score models mostly replicated results. Findings show the promise of short, intensive programs for sparking growth in critical agency and action and highlight the need for more critical consciousness-raising spaces.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0020.002
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.083
GPT teacher head0.410
Teacher spread0.327 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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 routes1
Has abstractyes

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