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Record W4392754263 · doi:10.26555/humanitas.v21i1.394

Exposure to violent video and aggressive behavior among Public Secondary Students, Kwara State, Nigeria

2024· article· en· W4392754263 on OpenAlexaff
Samuel Kolawole Ajiboye, Oluwatoni Esorun, Bolaji Gbenuade Oladejo

Bibliographic record

VenueHumanitas Indonesian Psychological Journal · 2024
Typearticle
Languageen
FieldPsychology
TopicBullying, Victimization, and Aggression
Canadian institutionsCanadian Rural Health Research Society
Fundersnot available
KeywordsState (computer science)PsychologyCriminologySocial psychologySocioeconomicsSociologyComputer science

Abstract

fetched live from OpenAlex

Aggressive behavior is a range of acts that result in physical and psychological harm to the perpetrator, and other students, thus hindering learning activities. This study investigated the relationship between exposure to violent videos and aggressive behavior among public secondary students in Kwara State, Nigeria. The survey method with a correlational design was adopted. A total sample of 381 participants was involved using the stratified random sampling technique. A research-designed questionnaire titled Exposure to Violent Videos and Aggressive Behaviour Questionnaire (EVABQ) was used to collect the data. Pearson’s product-moment correlation and t-test statistics were used to analyze the hypotheses. Results revealed a positive relationship between exposure to violent videos and aggressive behavior. The results showed statistically significant differences in exposure to violent videos and aggressive behavior among public secondary students based on gender and age. Male respondents were more exposed to violent videos and had more aggressive behavior than females. In contrast, students below 15 years old were more exposed to violent videos and exhibited aggressive behavior than 15 years and above. Therefore, school counselors should sensitize public secondary students to the influence of exposure to violent videos on aggressive behavior, especially among males and students below 15 years old.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Insufficient 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 score0.256
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0080.000

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 head0.029
GPT teacher head0.341
Teacher spread0.312 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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