RATIONAL EMOTIVE THERAPY (RET) UNTUK MENGATASI QUARTER LIFE CRISIS REMAJA AKHIR DI MAN 2 YOGYAKARTA
Bibliographic record
Abstract
The quarter life crisis of late adolescence is an unstable state due to the many life choices facing the future that cause problems such as anxiety, worry and fear. One of the efforts that can be made to address this is Rational Emotive Therapy (RET) counseling. The aim of this study was to find out the steps of Rational Emotive Therapy (RET) to address the quarter life crisis in late adolescence. This type of research is qualitatively descriptive with observational, interview and documentation data retrieval methods. The subjects in this study were counselors who had managed a quarter life crisis using Rational Emotive Therapy (RET) and students who were or had received Rational Emotive Therapy (RET) counseling to overcome a quarter life crisis. The results of this study were in the form of Rational Emotive Therapy (RET) measures. The first step is to point out the irrational problem of counseling. It is in this step where the counselor shows the counselor that the problem he is facing is related to his irrational beliefs. The second step is for the counselor to sensitize the counseling and show that the counselor maintains emotional disorders and illogical thinking. The third step is to correct the counselor's thinking. The counselor corrects his thoughts and abandons his irrational ideas. The fourth step is to develop a rational philosophy of life that is to challenge counseling to develop a rational philosophy of life so as to avoid the possibility of falling victim to rational beliefs.
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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 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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.
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".