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Hubungan Dukungan Sosial dan Regulasi Emosi dengan Quarter Life Crisis Mahasiswa

2023· article· id· W4400367975 on OpenAlexaboutno aff
El-tsaniyah Rihlatul Widaad, Arbin Janu Setiyowati, Diniy Hidayatur Rahman

Bibliographic record

VenueBuletin Konseling Inovatif · 2023
Typearticle
Languageid
FieldPsychology
TopicPsychological Well-being and Life Satisfaction
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyQuarter (Canadian coin)HumanitiesPolitical scienceArtGeographyArchaeology

Abstract

fetched live from OpenAlex

Kecemasan terhadap masa depan, finansial dan perkerjaan, kurangnya kepercayaan diri, keraguan dalam memutuskan pilihan, tertekan dengan tuntutan lingkungan, serta seringkali terlibat dalam permasalahan hubungan dengan orang terdekat menyebabkan quarter life crisis yang berpengaruh pada kesehatan mental individu. Faktor penyebabnya yaitu dari internal (regulasi emosi) dan eksternal (dukungan sosial. Tujuan penelitian untuk mengetahui hubungan antara dukungan sosial dan regulasi emosi dengan quarter life crisis. Penelitian menggunakan rancangan penelitian korelasional. Sampel penelitian sejumlah 175 mahasiswa, menggunakan metode simple random sampling dalam pengambilan sampel. Teknik analisis dengan analisis korelasi berganda. Instrumen penelitian menggunakan skala dukungan sosial, skala regulasi emosi, dan skala quarter life crisis ketiganya sudah teruji validitas dan reliabilitasnya. Hasil penelitian uji korelasi berganda menunjukkan nilai signifikansi sebesar 0.00 terhadap hubungan X1 (dukungan sosial) dan Y (quarter life crisis) maka ada hubungan antar keduanya, lalu pada hubungan X2 (regulasi emosi) dan Y (quarter life crisis) menunjukkan nilai signifikansi 0,395 maka tidak ada hubungan signifikan antar keduanya, sedangkan hubungan X1 dan X2 dengan Y menunjukkan signifikansi 0,00 maka terdapat hubungan secara simultan antar ketiganya.

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)0.004
metaresearch head score (Gemma)0.009
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0140.002

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 head0.035
GPT teacher head0.312
Teacher spread0.278 · 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".

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Citations0
Published2023
Admission routes1
Has abstractyes

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