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Record W4391172703 · doi:10.35631/ijlgc.834011

NAFKAH IN A FAMILY: A STUDY ON AWARENESS OF ISSUES AMONG UNIVERSITY STUDENTS

2023· article· en· W4391172703 on OpenAlexaff
Atiratun Nabilah Jamil, Nurhidayah Muhamad Sharifuddin, Khafizatunnisa’ Jaapar, Fathiah Fathil

Bibliographic record

VenueInternational Journal of Law Government and Communication · 2023
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicIslamic Finance and Banking Studies
Canadian institutionsImpact
Fundersnot available
KeywordsMathematics educationPsychology

Abstract

fetched live from OpenAlex

This study aims to examine the level of awareness among students taking the course on Islamic Family Institution Management (HKR111) regarding obligations and issues related to financial support. The research method involves a questionnaire assessing the students' knowledge of financial obligations and their views on this responsibility. The study results indicate that awareness of financial obligations has not yet reached an optimum level, and most students only have a basic understanding of the concept of financial support. Educational background, religion, and residential area play a crucial role in shaping their perceptions on this matter. Students with higher formal education and upbringing in religious values tend to have a deeper understanding of financial obligations. Media influence also impacts their perceptions of financial obligations. Media content that tends to portray this responsibility negatively or superficially can influence students' attitudes toward the concept of financial support. Therefore, there is a need to enhance student awareness through formal education and religious teachings, as well as encourage the creation of media content that provides a balanced and realistic view of financial responsibilities. Overall, this study suggests that there is room for improving general public awareness of financial support. Continuous efforts are required to ensure that they understand the importance of this responsibility in shaping a responsible and ethical society.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.039
Threshold uncertainty score0.217

Codex and Gemma teacher scores by category

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

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 head0.025
GPT teacher head0.289
Teacher spread0.264 · 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.

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

Citations1
Published2023
Admission routes1
Has abstractyes

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