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Record W4408217677 · doi:10.53008/kalbisiana.v11i1.747

Persepsi Perempuan dalam Menginterpretasi Quarter Life Crisis

2025· article· en· W4408217677 on OpenAlexaboutno aff
Kevin Gutomo Putra, Agustrijanto

Bibliographic record

VenueKALBISIANA Jurnal Sains Bisnis dan Teknologi · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicGender and Women's Rights
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)Political scienceHistoryArchaeology

Abstract

fetched live from OpenAlex

Quarter life crises tend to attack women compared to men, because women have more demands and roles to do at one time. For example, getting married, raising children, working and having a career, having a good financial condition, and building a social life. One of the efforts usually made by women in overcoming the quarter life crisis is by conducting interpersonal communication with other individuals to simply pour out their hearts or even find solutions. This study focuses on women's perceptions of the quarter life crisis and how they can overcome the quarter life crisis by conducting interpersonal communication. The research method used is descriptive qualitative. The results showed that women's perceptions in overcoming the quarter life crisis phase were by doing all positive ways such as discussing and telling stories to friends or the surrounding environment, introspecting themselves, and reflecting on everything that had happened by thinking about solutions that would be done so that the problem was solved.

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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.031
Threshold uncertainty score0.102

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0020.002
Open science0.0000.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0310.004

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 head0.300
Teacher spread0.284 · 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 designQualitative
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

Explore more

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