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Record W7115892267 · doi:10.37278/jipsi.v7i2.1397

Analisis Tingkat Learned Helplessness pada Perempuan dalam Toxic Relationship di Periode Quarter Life Crisis

2025· article· W7115892267 on OpenAlexaboutno aff

Bibliographic record

VenueJIPSI Jurnal Ilmiah Psikologi · 2025
Typearticle
Language
FieldPsychology
TopicStudent Stress and Coping
Canadian institutionsnot available
Fundersnot available
KeywordsLearned helplessnessCronbach's alphaQuarter (Canadian coin)Population

Abstract

fetched live from OpenAlex

Periode Quarter Life Crisis (QLC) pada perempuan yang berusia 21-25 tahun, biasanya dihadapkan dengan banyak tantangan, terutama tuntutan menuju pernikahan. Sebelum menikah, biasanya mereka melalui dengan berpacaran, namun tidak semua berjalan lancar. Dalam perjalanannya, banyak yang mengalami toxic relationship dan sulit keluar dalam hubungan tersebut. Tujuan penelitian ini untuk mengetahui tingkat Learned Helplessness (LH) pada perempuan dalam toxic relationship di periode QLC. Metode yang digunakan adalah kuantitatif dengan metode deskriptif. Responden penelitian adalah 155 perempuan yang berpacaran di periode usia QLC. Teknik pengumpulan data menggunakan Learned Helplessness Scale (LHS) dikembangkan oleh Quinless dan Nelson (1988), dengan koefisien reliabilitas Cronbach Alpha sebesar 0,962. Penelitian ini menghasilkan 73 responden atau sebesar 47,1 % berada dalam kategori LH sangat tinggi, sebanyak 57 responden atau sebesar 36,77 % berada dalam kategori LH tinggi dan selebihnya masuk ke dalam kategori LH rendah serta LH sangat rendah.

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)0.004
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 score0.008
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0080.001

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 head0.058
GPT teacher head0.368
Teacher spread0.310 · 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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