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Record W3130768918 · doi:10.1002/jcop.22521

Bullying victimization, psychosocial functioning, and protective factors: Comparing African American heterosexual and sexual minority adolescents in Chicago's Southside

2021· article· en· W3130768918 on OpenAlexaff
Jun Sung Hong, Alberto Valido, Matthew Rivas‐Koehl, Ryan M. Wade, Dorothy L. Espelage, Dexter R. Voisin

Bibliographic record

VenueJournal of Community Psychology · 2021
Typearticle
Languageen
FieldPsychology
TopicBullying, Victimization, and Aggression
Canadian institutionsUniversity of Toronto
FundersCenter for Health Administration Studies
KeywordsPsychosocialPsychologySexual minorityClinical psychologyPsychological interventionProtective factorAfrican americanSubstance useLesbianPsychiatryMedicine

Abstract

fetched live from OpenAlex

African American heterosexual and sexual minority (SM) adolescents report widespread bullying victimization (BV), which is associated with poorer psychosocial functioning. However, studies examining potential protective factors that moderate this association are limited. Using data from a cross-sectional study conducted in Chicago, we examined the association between BV and psychosocial functioning among a sample of heterosexual (n = 475) and SM (n = 105) African American adolescents and examined whether four empirically-supported protective factors moderated these associations. Among SM adolescents, having close parents was protective against psychosomatic symptoms for those who reported high BV and having caring teachers was protective against substance use for those who reported both high and low BV. Among heterosexual adolescents, having close parents was protective against substance use for those who reported high BV but having high neighborhood support exacerbated the risk of developing psychosomatic symptoms for those who reported high BV. Implications for school and parental-based interventions are discussed.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.036
Threshold uncertainty score0.072

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.043
GPT teacher head0.336
Teacher spread0.293 · 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 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

Citations16
Published2021
Admission routes1
Has abstractyes

Explore more

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