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Record W3106666274 · doi:10.1002/ab.21938

A dyadic perspective on aggressive behavior between friends

2020· article· en· W3106666274 on OpenAlex

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

VenueAggressive Behavior · 2020
Typearticle
Languageen
FieldPsychology
TopicBullying, Victimization, and Aggression
Canadian institutionsYork UniversityBrock University
Fundersnot available
KeywordsPerspective (graphical)Human factors and ergonomicsPoison controlPsychologyInjury preventionSuicide preventionOccupational safety and healthMedical emergencyMedicineComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

Youth are sometimes victimized by their friends, but we know little about the nature of these relationships. Taking a dyadic approach, we studied relationships characterized by both friendship and aggression. Participants (952 middle schoolers; 50% female; 44% Latinx) nominated friends and aggressive perpetrators and victims. Using two analytic samples of friend dyads (N = 6971) and aggressive dyads (N = 4662), results indicated that aggression by a friend was somewhat common. Compared with friend dyads without aggression, aggressive friend dyads were stronger (i.e., reciprocal) and longer lasting, though victimized youth were less satisfied with the friendship. Aggressive dyads who were friends more often had reciprocal aggression than aggressive dyads who were not friends. Results provide insight into the dynamics of aggression in close peer relationships.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.199
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.002

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 head0.348
Teacher spread0.305 · 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