School Personnel’s Self-Esteem, Sense of Self-Efficacy and Interventions on Weight-Related Bullying According to Their Weight Perception and Dieting Behaviors
Bibliographic record
Abstract
To increase academic performance in children, elementary school personnel are encouraged to focus on socio-emotional learning. Better classroom management and safer environments, exempt of bullying and particularly of weight-related bullying, appear like ways of fostering socio-emotional learning in children. However, some school personnel’s characteristics could impact their ability to act on these dimensions. This research is interested in how weightrelated intervention behaviors, self-esteem and sense of self-efficacy vary according to school personnel’s dieting behaviors and weight perception are related to their self-esteem, sense of self-efficacy, and intervention behaviors on weight-related bullying. A total of 164 Canadian participants filled in questionnaires focusing on bullying, self-esteem, and sense of self-efficacy. Results show that most school personnel felt competent to manage their group of students and to intervene on weight-related bullying. Those who were on a diet and who perceived their weight as higher seem significantly more involved in promoting motivation for school and learning engagement in their students as well as more likely to intervene with the bully when encountering weight-related bullying situations. For their part, participants of normal weight who were on a diet had a significantly lower self-esteem than those dieting and having a perception of overweight. These results are encouraging because they suggest that elementary school personnel feel competent with regards to the socioemotional learning of their students and is actively involved in providing them a safe learning environment.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".