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Record W2102818929 · doi:10.1177/0829573509357550

Do School Bullying and Student—Teacher Relationships Matter for Academic Achievement? A Multilevel Analysis

2010· article· en· W2102818929 on OpenAlexaffabout
Chiaki Konishi, Shelley Hymel, Bruno D. Zumbo, Zhen Li

Bibliographic record

VenueCanadian Journal of School Psychology · 2010
Typearticle
Languageen
FieldPsychology
TopicBullying, Victimization, and Aggression
Canadian institutionsUniversity of British Columbia
FundersAmerican Educational Research Association
KeywordsSocial connectednessPsychologyMultilevel modelAcademic achievementSchool climateAffect (linguistics)Developmental psychologyStudent achievementMathematics educationSocial psychology

Abstract

fetched live from OpenAlex

In extending our understanding of how the social climate of schools can affect academic outcomes, this study examined the relationship between school bullying, student— teacher (S-T) connectedness, and academic performance. Using data collected in Canada as part of a larger international study conducted by the Organisation for Economic Co-operation and Development, participants included 27,217 students aged 15 years and 1,087 school principals. Results of multilevel analyses revealed that math achievement was negatively related to school bullying and positively related to S-T connectedness. For boys, there was a significant interaction between bullying and S-T connectedness, suggesting a buffering effect of S-T connectedness on the relationship between school bullying and math achievement. Similar results were evident for reading achievement.

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)0.006
metaresearch head score (Gemma)0.014
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 score0.194
Threshold uncertainty score0.385

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.014
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.004
Bibliometrics0.0030.003
Science and technology studies0.0030.001
Scholarly communication0.0030.002
Open science0.0020.003
Research integrity0.0010.003
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 head0.059
GPT teacher head0.374
Teacher spread0.315 · 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

Citations237
Published2010
Admission routes2
Has abstractyes

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