KESIAPAN PENERAPAN PEMBELAJARAN TATAP MUKA (PTM) DI MASA NEW NORMAL PANDEMI COVID-19 (Studi Kasus di SMPN 2 Siberut Utara, Kabupaten Kepulauan Mentawai)
Bibliographic record
Abstract
Pandemi Covid-19 membuat sekolah harus siap dengan kondisi penerapan new normal yangmengacu pada pola pendidikan yang ditetapkan oleh pemerintah karena proses PembelajaranTatap Muka (PTM) akan dilakukan seperti biasa di sekolah. Penelitian yang dilaksanakanadalah penelitian kualitatif dengan pendekatan studi kasus mengenai kesiapan sekolahterhadap PTM di masa new normal pandemi Covid-19 di SMPN 2 Siberut Utara. PersiapanSMPN 2 Siberut Utara sesuai protokoler kesehatan diantaranya adalah peserta didik dan guruwajib menggunakan masker baik masker kain maupun masker bedah di lingkungan sekolah,mencuci tangan dengan sabun pada tempat yang sudah disediakan, mengecek suhu tubuh,menjaga jarak antar peserta didik di dalam kelas dengan penataan tempat duduk sesuai jarakyang ditentukan maupun di luar kegiatan belajar mengajar dengan tetap menjaga jarak, adanyaproses penyemprotan disinfektan di dalam kelas dan lingkungan sekolah secara rutin, sertasekolah juga membuat sosialisasi pencegahan Covid-19 di SMPN 2 Siberut Utara melaluispanduk pencegahan Covid-19 yang ditempelkan di lingkungan sekolah. SMPN 2 Siberut Utaramemiliki kesiapan yang sudah sesuai dengan anjuran pemerintah dalam pelaksanaanPembelajaran tatap Muka (PTM).
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".