Konsensus Ahli dalam Menentukan Kriteria Taman Ramah Anak: Pendekatan Delphi
Bibliographic record
Abstract
Perencanaan yang inklusif dan berkelanjutan harus dapat menjamin tumbuh kembang anak secara menyeluruh. Pemenuhan kebutuhan anak terhadap ruang sebagai salah satu upaya mendukung konsep Child-Friendly Cities Initiative (CFCI) dan program Kabupaten Layak Anak. Penelitian ini bertujuan untuk merumuskan kriteria taman kota ramah anak berdasarkan validasi pendapat para ahli menggunakan metode Delphi. Penelitian ini menggunakan pendekatan deskriptif kualitatif. Proses Delphi berlangsung dalam satu putaran dan berhasil mencapai konsensus, ditunjukkan melalui kesepakatan semua responden. Hasil wawancara menunjukkan bahwa seluruh responden sepakat terharap kriteria taman ramah anak yang diujikan. Tidak terdapat perubahan terhadap variabel yang diujikan sebagai kriteria taman ramah anak, sehingga kriteria yang diperoleh dianggap relevan dan dapat digunakan sebagai dasar dalam menilai kesesuaian pemanfaatan taman kota terhadap prinsip taman ramah anak.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".