Acoso escolar, ciberbullying y su impacto socioafectivo y psicológico en los estudiantes de las instituciones educativas
Bibliographic record
Abstract
The issue related to bullying in educational institutions is in vogue this problem has its origin through harassment or bromas ranging from a happy slapping or slap, ask the victim to do such or such favor asking for things, Money, gestures and actions of intimidation, these and other manifestations of harassment such as cyberbullying through the network and other expressions of violence impede the optimal development of students, interfere in the sense of group pertinence, their relationship of healthy and harmonious coexistence , Being one of the most important factors of the school desertion.This research aims to determine the predominant factors that affect harassment and how they generate far-reaching consequences in the lives of those who experience it, considering that Cotopaxi is no exception, since a high percentage of students recognized and accepted some type of harassment School or cyberbullyingin their school life, as well as the fear of denouncing by multiple sociocultural factors.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".