STRATEGI MEMPERSIAPKAN GENERASI EMAS 45 MELALUI ANALISIS PSIKOLOGIS DAN STUDI KOLABORATIF ANTARA SEKOLAH DAN KELUARGA TENTANG PERILAKU MALADJUSTMEN REMAJA
Bibliographic record
Abstract
Generasi emas 45 perlu didukung dalam pencapainnya melalui mempersiapkan remaja sebagai generasi penerus estafet pembangunan bangsa ke depan. Remaja perlu dipersiapakan untuk pencapaian perkembangan yang matang, terhindar dari perilaku salah suai (malaadjusment). Dari hasil penelitian yang telah dilakukan di Tahun 2016 tentang perilaku salah suai yang terjadi pada remaja dari beberapa pendekatan seperti analisis transaksional, rational emotif behavior therapy dan pendekatan realitas. Dari hasil penelitian tersebut menunjukkan bahwa remaja pada umumnya banyak memiliki tingkah laku salah suai. Jika kondisi ini tidak disikapi, maka akan mengganggu perkembangan remaja selanjutnya. Dengan demikian melalui tulisan ini akan dibahas secara mendalam tentang bagaimana kolaborasi antara sekolah dan keluarga mengatasi tingkah laku salah suai remaha (maladjusment).
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 | 0.009 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.019 | 0.004 |
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".