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Record W3029062333 · doi:10.5539/ies.v13n6p85

Relationship Between Behavioural Disorders and Social Cognition among Orphans in Saudi Arabia

2020· article· en· W3029062333 on OpenAlexvenueno aff
Huda Othman Alghamdi

Bibliographic record

VenueInternational Education Studies · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicPoverty, Education, and Child Welfare
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyNonprobability samplingCognitionInterpretative phenomenological analysisClinical psychologyQualitative researchDevelopmental psychologyPsychiatryMedicinePopulation

Abstract

fetched live from OpenAlex

This study aimed to investigate the relationship between behavioural disorders and social cognition among orphans in Saudi Arabia by adopting a phenomenological qualitative approach. To achieve this aim, 50 subjects were selected to participate in this study through a purposive sampling. The participants were subjected to a semi-structured interview session which lasted from 45 minutes to an hour. After data has been gathered, Interpretative Phenomenological Analysis was used to analyse data into themes which were categorized into three: Symptoms of Behavioural Disorders, Social Cognitions, and Factors. The results of the study showed that emotional and behavioural disorders that orphans face in Saudi Arabia were manifested by symptoms of disorders such as Posttraumatic Stress Disorder, Oppositional Defiant Disorder, and Social Phobia. Factors that tend to have a significant effect on behavioural problems among orphans consisted of traumatic events, events prior to admittance in the orphanage such as physical abuse, and the overall physical environment of the orphanage, which can be at risk of being conducive for bullying and fighting among orphans. Furthermore, there might be a relationship between behavioural disorders and social cognition among orphans in Saudi Arabia.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.090
GPT teacher head0.379
Teacher spread0.289 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations2
Published2020
Admission routes1
Has abstractyes

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