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Record W4410001777 · doi:10.56709/stj.v4i1.706

Kemampuan Self Compassion memprediksi Quarter Life Crisis pada Individu Dewasa Awal

2025· article· en· W4410001777 on OpenAlexaboutno aff
Ayu Prabasari Dharmajayanti, I Rai Hardika, Agnes Utari Hanum Ayuningtias

Bibliographic record

VenueSci-Tech Journal · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Character Development
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyCompassionQuarter (Canadian coin)PhilosophyHistoryTheology

Abstract

fetched live from OpenAlex

This study aims to look at the role of self-compassion in predicting the occurrence of a quarter-century crisis in Early Adults. This research refers to the ability of self-compassion in helping individuals develop a willingness to rise and grow over the discomfort experienced. The sample of this study was 348 people obtained by the quota sampling technique, whose characteristics were Early Adult Individuals domiciled in Bali and aged 20-39 years. This study has two instruments: the self-compassion scale and the quarter-life crisis scale. All scales have proven reliable and valid based on the CFA test. Based on the results of a simple regression test, it was found that Self-compassion can predict the occurrence of a quarter-life crisis with a significance value of 0.00 and a percentage of 63.5%. The results of this study also illustrate that self-compassion and quarter-life crises grow significantly as a result of the internal motivation of the individual rather than the impulse from outside the individual self.

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)0.000
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 score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
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 head0.016
GPT teacher head0.323
Teacher spread0.307 · 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
Published2025
Admission routes1
Has abstractyes

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