Pusat Rehabilitasi Anak Jalanan Di Surakarta Dengan Pendekatan Healing Environment
Bibliographic record
Abstract
Street children are not new to Indonesia and have long developed. One's surakarta. Since 2020, Indonesia's share of bobi's interest rate has been fairly stable, and by 2022 social services will be responsible for all 285 motorists, a major problem for credit for Indonesia. This posed a challenge to the city of surakarta because it was one of the cities modeled on the construction of kla and was designated as the town of worthy children (kla). The city government of surakarta has established a number of programs for handling street children, but it has not been able to get them out of street life. This is because the facility's limitations and capacity as its location for activity are not able to provide maximum activity, the presence of the facility is not currently working as it should. The strategy to empower street children is to create rehabilitation facilities for them. This design is an important means of upbuilding and rehabilitation of street children to avoid returning to the streets. To make such a contribution, there can be an architectural concept of healing environment that can help a child's psychological, physical, and emotional recovery process, and it is hoped that street children can return to society and gain the desire to end street life.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 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) | 0.023 | 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".