EVALUASI PROGRAM KARTU JAKARTA PINTAR (KJP) PLUS DI SEKOLAH DASAR KECAMATAN MAKASAR JAKARTA TIMUR
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Secara umum tesis ini bertujuan untuk mendapatkan informasi tentang program KJP Plus di Sekolah Dasar Kecamatan Makasar Jakarta Timur. Evaluasi ini menggunakan pendekatan model CIPP (Context, Input, Process, dan Product). Teknik pengumpulan data melalui studi dokumentasi, dan kuesioner. Teknik analisis data dalam metode evaluasi ini menggunakan pendekatan kuantitatif-deskriptif dengan tahapan yang terdiri dari: reduksi data, penyajian data, dan penarikan kesimpulan. Hasil evaluasi menyimpulkan bahwa: (1). Konteksdari pelaksanaan program KJP Plus di Sekolah Dasar Kecamatan Makasar Jakarta Timur sudah sesuai dengan ketentuan yang berlaku di dalam program KJP plus. (2) Input dari pelaksanaan program KJP Plus sudah sesuai dalam mendukung kesuksesan program KJP plus di Sekolah Dasar Kecamatan Makasar Jakarta Timur. (3) Pelaksanaan program KJP Plus di Sekolah Dasar Kecamatan Makasar Jakarta Timur sudah berjalan baik namun perlu ada perbaikan pada aspekpelaporan penggunaan dana KJP plus. (4) Ketercapaian pelaksanaan program KJP Plus di Sekolah Dasar Kecamatan Makasar Jakarta Timur di masa pandemi covid-19 belum optimal terutama dalam pemenuhan kebutuhan peserta didik khususnya dalam menunjang kebutuhanpendidikan.
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.
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 | 0.008 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.011 |
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 it