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National trends in school victimization among Asian American adolescents

2014· article· en· W1965917313 on OpenAlex
North Cooc, Kevin A. Gee

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Adolescence · 2014
Typearticle
Languageen
FieldPsychology
TopicBullying, Victimization, and Aggression
Canadian institutionsTellabs (Canada)
Fundersnot available
KeywordsAsian americansPsychologySocioeconomic statusAcademic achievementEthnic groupDevelopmental psychologySuicide preventionPoison controlDemographyPopulationSociologyMedicineEnvironmental health

Abstract

fetched live from OpenAlex

The "model minority" perception of Asian American students often ignores the academic and social challenges that many face in schools. One area that has received less attention is the school victimization experiences of Asian American adolescents. While some qualitative researchers have explored factors contributing to school victimization in recent years, missing in the literature is the scope of these incidents among Asian Americans. This paper contributes to this literature by (1) examining national trends in the victimization of Asian American adolescents in schools over the last decade and (2) investigating how victimization varies according to their gender, socioeconomic status, and achievement levels. The results show that although Asian American adolescents are consistently less likely to be bullied relative to other students, they are more likely to report experiences of racial discrimination. Victimization incidents for Asian Americans also differ by gender and academic achievement levels.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.073
Threshold uncertainty score0.557

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.011
GPT teacher head0.293
Teacher spread0.282 · 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