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Record W4405652102 · doi:10.6007/ijarafms/v14-i4/24222

Examining the Relationship between Empathy and Subjective Well-Being among University Students

2024· article· en· W4405652102 on OpenAlexaboutno aff
Nurul Athina Zakaria, Nor Azzatunnisak Mohd Khatib

Bibliographic record

VenueInternational Journal of Academic Research in Accounting Finance and Management Sciences · 2024
Typearticle
Languageen
FieldPsychology
TopicEmotional Intelligence and Performance
Canadian institutionsnot available
Fundersnot available
KeywordsEmpathyPsychologySocial psychologyDevelopmental psychology

Abstract

fetched live from OpenAlex

Empathy is an important aspect of understanding socialization and human nature.Past studies also showed that research findings on empathy are inconsistent in explaining the relationship between empathy and subjective well-being.Hence, this study examines the relationship between empathy and subjective well-being among university students.A total of 272 students were selected as participants, which was retrieved using convenient sampling.Toronto Empathy Questionnaires and the Malaysian version of the Personal Well-Being Index (PWI) were used to measure empathy and subjective well-being.A cross-sectional descriptive correlational design was used in the present study.Statistical Package of Social Sciences (SPSS) is software for data management that is used in analyzing data using descriptive and inferential statistical analysis.The results of the analysis found that there is a significant positive relationship between empathy and subjective well-being score (r = .18,p<.003).The results of the present study verify that empathy is related to the subjective wellbeing of a university student.Future studies have suggested focusing on the influence of empathy on subjective well-being from a larger perspective involves many domains.

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)0.007
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 score0.043
Threshold uncertainty score0.347

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.177
GPT teacher head0.470
Teacher spread0.293 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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Same venueInternational Journal of Academic Research in Accounting Finance and Management SciencesSame topicEmotional Intelligence and PerformanceFrench-language works237,207