Comparison of Quarter Life Crisis in Adolescents
Bibliographic record
Abstract
Quarter Life Crisis is a new term related to the stages of human socio-emotional development. Approaching the age of 25, individuals usually have to face new life situations such as work and marital status, as well as changes in mindset that are more mature from adolescence to adulthood. This situation also makes individuals at the peak of self-maturity, when entering the age of 25, question their own lives, doubt their own choices, feel confused about the things they are living, and begin to recall the past. The type of research used for this research is qualitative with interview techniques. The primary data source is in the form of interviews regarding their understanding of the quarter life crisis. Our secondary data sources are information from journals or other internet sources. Interview results show that individuals in early adulthood who experience a quarter life crisis feel anxious and afraid, which is caused by uncertainty about the future, social pressure, hormonal changes, and others. In the publication, we present two contents on the Instagram page (reels and feed).Our reels upload reached 714 views until October 16, 2023 at 4.10 PM. Meanwhile on Instagram feeds, our content reached 36 users within 15 hours through mass media the information conveyed can be accessed more widely and spread quickly. It is expected that this social campaign can change several aspects of the target audience, such as awareness, attitude, & action.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".