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Record W1497973224 · doi:10.1177/0886260515585528

The View From the Bottom

2015· article· en· W1497973224 on OpenAlexaffabout
Anthony Napoletano, Frank J. Elgar, Grace Saul, Melanie A. Dirks, Wendy Craig

Bibliographic record

VenueJournal of Interpersonal Violence · 2015
Typearticle
Languageen
FieldPsychology
TopicBullying, Victimization, and Aggression
Canadian institutionsQueen's UniversityMcGill University
Fundersnot available
KeywordsMultinomial logistic regressionPsychologyHuman factors and ergonomicsInjury preventionSuicide preventionPoison controlOccupational safety and healthLogistic regressionDevelopmental psychologySocial psychologyDemographyMedicineEnvironmental healthSociologyMathematics

Abstract

fetched live from OpenAlex

We investigated the relation between relative deprivation (RD)-disparity in affluence between adolescents and their more affluent schoolmates-and involvement in bullying among 23,383 students (aged 9-19) in 413 schools that participated in the 2010 Canadian Health Behavior in School-Aged Children survey. Students reported family affluence and frequency of bullying victimization and perpetration during the previous 2 months. Using the Yitzhaki index of RD and multinomial logistic regression analysis, we found that RD positively related to three types of bullying victimization (physical, relational, and cyberbullying) and to two types of perpetration (relational and cyberbullying) after differences in absolute affluence were held constant. These findings suggest that RD uniquely contributes to risk of bullying involvement.

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)0.002
metaresearch head score (Gemma)0.004
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.127
Threshold uncertainty score0.253

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0030.008
Scholarly communication0.0080.006
Open science0.0010.005
Research integrity0.0020.006
Insufficient payload (model declined to judge)0.0120.004

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 head0.031
GPT teacher head0.313
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

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

Citations51
Published2015
Admission routes2
Has abstractyes

Explore more

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