The construct of bullying in school settings theoretical basis-7.8-GD003
Bibliographic record
Abstract
School bullying represents a pervasive and detrimental issue within educational settings worldwide, exerting significant negative impacts on the psychological well-being, social development, and academic performance of students. This comprehensive study endeavors to establish a robust theoretical foundation for understanding and addressing school bullying by meticulously dissecting its conceptual underpinnings, typologies, theoretical frameworks, and causal mechanisms. Employing a multidisciplinary approach, the research integrates ecological systems theory, social learning theory, and social cognitive theory to elucidate the intricate interplay of individual, interpersonal, and environmental factors that contribute to bullying behaviors. The findings underscore the efficacy of holistic prevention strategies and multifaceted intervention approaches in mitigating the prevalence and severity of bullying incidents, thereby fostering a conducive learning environment that promotes the holistic development of students. This study not only contributes to the theoretical discourse on school bullying but also furnishes practitioners and policymakers with empirically grounded, actionable insights to inform policy formulation and intervention design. The implications of this research extend beyond the confines of academic settings, offering a nuanced perspective on the broader societal implications of bullying and the potential for collaborative, systemic solutions to enhance the safety and well-being of all students.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.011 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".