Cyberbullying and Cybervictimization in Tanzanian Secondary Schools: Prevalence and Predictors
Bibliographic record
Abstract
Abstract This study explored cyberbullying and cybervictimization, and the role of sociodemographic and access to technology variables for Tanzanian adolescents. A self-report questionnaire was completed by secondary school students aged 14 to 18 (Form 1 to Form IV). Results provide evidence that online violence is increasingly becoming a problem of concern for Tanzanian adolescents. In particular, whereas 42% of the students reported to have cyberbullied others using electronic communication devices, 58% admitted having experienced cybervictimization. Also, results showed that students who spend more time online, share cellphones with others, and who access digital devices in a private location are more likely to experience cybervictimization. We also found out that students who use digital devices in a private location, and who spend more time online (for older and male adolescents) were more likely to cyberbully others online. The findings provide a further evidence that cyberbullying is a problem of concern for all children and adolescents across cultures. The paper concludes by providing implications and suggestions for intervention programs, and for future studies
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".