SURVIVE OR THRIVE? STUDENTS’ FUTURE ORIENTATION DURING QUARTER LIFE CRISIS
Bibliographic record
Abstract
The average age of undergraduate students in Indonesia is 19-24 years. In terms of period development, students can experience a transition period from adolescence to early adulthood. The main responsibilities during early adulthood are both personal and professional development. Developmental period tasks and the knowledge that students have presents many alternative routes and choices for their future, but some also have an impact on psychological dynamics and raise anxiety. This can be included in the characteristics of the quarter life crisis. The purpose of this study was to describe the future orientation of students during the quarter life crisis.This research is a descriptive quantitative research. The sample was 344 students during the quarter life crisis, so the sampling technique used was convenience sampling. The analytical method used is descriptive analysis with data collection using a scale of entrepreneurial intentions with a reliability coefficient of 0.931 and 29 of 30 valid items.Based on the results of analysis of research data regarding future orientation of students during the quarter life crisis, it can be concluded that there is a future orientation for students during the quarter life crisis. The general orientation of students during the quarter life crisis was in the high category with an empirical mean value of 117.616.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".