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Record W4322745248 · doi:10.26737/ij-mds.v6i1.4156

Analysis of the Factors Causing Bullying Behaviour of Class XI Students at MAN Singkawang

2023· article· en· W4322745248 on OpenAlexaff
Kamaruddin Kamaruddin, Slamat Fitriyadi, Miranti Aulia Angel, Floria Kabora

Bibliographic record

VenueInternational Journal of Multi Discipline Science (IJ-MDS) · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicEducational Methods and Impacts
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsNonprobability samplingPsychologyTriangulationSocial psychologyClass (philosophy)Mass mediaDevelopmental psychologyAdvertisingSociologyDemographyMathematicsComputer science

Abstract

fetched live from OpenAlex

<p><em>This study aims to describe the factors that cause</em> <em>bullying behaviour of class XI students at MAN Singkawang. The research used is qualitative. The research subjects used were 13 people. The method used was the interview with sampling, the data source was purposive. Collection technique with triangulation. The results of this study indicated that factors causing bullying behaviour: (a) family factors were caused by a less harmonious family, incomplete (parents die or get divorced), communication between parents and children was not smooth, and unfair parenting; (b) the peer factor due to the excessive intensity of communication between peers allowed for the desire to bully at the instigation of their friends, so that they were considered to have full authority over their group; (c) the mass media factor, often excessive online gameplay and even more so the misuse of social media.</em></p>

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)0.000
metaresearch head score (Gemma)0.001
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 score0.024
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.121
GPT teacher head0.508
Teacher spread0.387 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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