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Record W2921704075 · doi:10.1371/journal.pone.0211124

Preadolescent children’s perception of power imbalance in bullying: A thematic analysis

2019· article· en· W2921704075 on OpenAlexaff
Helen Nelson, Sharyn Burns, Garth Kendall, Kimberly A. Schonert‐Reichl

Bibliographic record

VenuePLoS ONE · 2019
Typearticle
Languageen
FieldPsychology
TopicBullying, Victimization, and Aggression
Canadian institutionsLearning PartnershipUniversity of British Columbia
FundersAustralian Government
KeywordsThematic analysisEmpathyPsychologyFocus groupPerceptionPower (physics)Peer groupInjury preventionPoison controlSocial psychologyDevelopmental psychologyHuman factors and ergonomicsSuicide preventionClinical psychologyQualitative researchMedicineEnvironmental healthSociology

Abstract

fetched live from OpenAlex

Bullying in schools is associated with an extensive public health burden. Bullying is intentional and goal oriented aggressive behavior in which the perpetrator exploits an imbalance of power to repeatedly dominate the victim. To differentiate bullying from aggressive behavior, assessment must include a valid measure of power imbalance as perceived by the victim. And yet, to date, there remains no agreement as to how to most accurately measure power imbalance among preadolescent children. This qualitative study explored children's (age 9 to 11) understanding of power imbalance through thematic analysis of focus group discussions. Subthemes that emerged as influencing power imbalance include: age of victim, peer valued characteristics, and group membership and position. Subthemes of empathy and peer valued characteristics emerged as protecting against the negative impact of power imbalance.

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 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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.025
GPT teacher head0.258
Teacher spread0.233 · 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 teacher head, not a consensus.

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

Citations30
Published2019
Admission routes1
Has abstractyes

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