Bibliographic record
Abstract
Quarter life crisis is a term used to describe a period of uncertainty generally experienced by adults in their 20s. This research aims to explore the phenomenon, identify factors, and describe students attitudes in dealing with quarter life crisis. The research informants consisted of seven students in the Special Region of Yogyakarta from the D3, D4, S1 and S2 levels. This research is descriptive qualitative research that uses purposive sampling as a subject determination. The data analysis techniques used is interactive model including Data Condensation, Data Presentation, and Consclusion Drawing. Data collection techniques use observation and interviews. Based on the research results, it was found that the quarter life crisis experienced by informants with informants with D3, D4, and S1 education levels was more complex crisis than informants with masters education levels. The crisis experienced by informant was caused by internal and external factors as well as many demands in the form of career paths, finances, education and interpersonal relationships. Quarter life crisis has an impact on mood and reduced self-confidence which then continues to compare. Each informant has there own way and strategy to survive in quarter life crisis.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".