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Record W2068477275 · doi:10.5539/ass.v7n12p3

Characterizing Misbehaviour among Jordanian High School Students

2011· article· en· W2068477275 on OpenAlexvenueno aff
Ameen Mohammed Mousa Mahasneh, Sharifah Md Nor, Abdul Rahman Aroff, Nur Surayyah Madhubala Abdullah, Bahaman Abu Samah, Ahmad Mohammed Mousa Mahasneh

Bibliographic record

VenueAsian Social Science · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicEducation Discipline and Inequality
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyAffect (linguistics)Social psychology

Abstract

fetched live from OpenAlex

The main purpose of this paper is to investigate the level of student misbehaviour and to explore the types of student misbehaviour among Jordanian high school students in the Governorate of Jarash. This paper presents the findings of a survey conducted to identify the level and type of misbehaviour. It emphasizes the important role school plays in reinforcing positive societal norms and values in teenagers with the ultimate aim to produce well-adjusted young adults. The findings support the idea that factors such as gender and grade level affect the type and level of misbehaviour exhibited by Jordanian high school students. The results of this study also revealed that the majority of the respondents showed a low level of misbehaviour. The most frequent types of misbehaviour found among Jordanian high schools students were disobedience, classroom disruption and vandalizing school property. Student misbehaviour differs significantly according to the students’ gender, grade level and the type of school they attend.

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.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.350
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.002
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.060
GPT teacher head0.382
Teacher spread0.322 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2011
Admission routes1
Has abstractyes

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