School-based Factors Contributing to Students’ Indiscipline Behavior at Public Schools
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This research investigates the School-based factors contributing to students' indiscipline behavior at public schools. The researcher uses a qualitative research approach method. Therefore, the method involves synthesizing existing literature related to this topic. The article delves into the complexity of indiscipline, identifying school-based factors which include School Leadership, and Administration, Curriculum, and Teaching Methods, Poor Teachers Students Relationship, Overcrowded Classroom, School Climate and Culture, Curriculum and Teaching Methods Limited Parental Involvement as causes that disrupt a conducive learning environment. Indiscipline encompasses actions deviating from accepted standards, leading to disorder and misconduct in various settings, especially public schools. In educational settings, it involves students disregarding rules, disruptive behavior, and violating codes of conduct. Indiscipline poses challenges to education systems and student development. The study identifies school-based factors which include crowded classrooms, lack of effective school leadership, lack of motivation, and many more as the most problematic school-based factors that influence students' indiscipline behavior at public schools. The article emphasizes the ongoing need for efforts from educational stakeholders to improve the situation.
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.
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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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 it