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Record W4399548407 · doi:10.58578/yasin.v4i4.3170

Hubungan antara Big Five Personality dengan Quarter Life Crisis pada Mahasiswa Tingkat Akhir di Universitas Negeri Padang

2024· article· en· W4399548407 on OpenAlexaboutno aff
Nurul Fadila, Free Dirga Dwatra

Bibliographic record

VenueYASIN · 2024
Typearticle
Languageen
FieldPsychology
TopicStudent Stress and Coping
Canadian institutionsnot available
Fundersnot available
KeywordsConscientiousnessAgreeablenessExtraversion and introversionPsychologyQuarter (Canadian coin)PersonalityNeuroticismCluster samplingBig Five personality traitsSocial psychologyDemographyPopulationSociologyGeography

Abstract

fetched live from OpenAlex

This study aims to see the relationship between big five personality and quarter life crisis in final year students at Padang State University. This research uses quantitative methods with a correlational research design. The sample collection technique in this study used cluster sampling technique. The number of respondents in this study was 116 final year students at Padang State University. The instrument in this study uses the scale of quarter life crisis crisis adopted from researcher Salsabilla (2023). And Goldberg's (1992) International Personality Item Pool-Big Five Factor Marker 50 (IPIP-BFM-50) scale, adapted to Indonesian by Akhtar & Azwar (2018). The results of the analysis used Product-Moment correlation analysis and found a significant negative relationship between the big five personality dimensions, namely extraversion, agreeableness, conscientiousness, neuroticism, and with quarter life crisis in final year students at Padang State University.

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 score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.028
GPT teacher head0.305
Teacher spread0.277 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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