Intepretasi falsafah dan hati budi Melayu dalam peribahasa Melayu sekolah rendah
Bibliographic record
Abstract
Pemahaman terhadap peribahasa Melayu terutamanya kata-kata hikmat adalah semakin kurang dalam kalangan pelajar di Sekolah Rendah. Isu ini akan memberi kesan kepada penghayatan dan penguasaan kandungan kurikulum yang berkesan bagi mata pelajaran Bahasa Melayu ini. Justeru, kajian ini adalah bertujuan untuk: a) mengenal pasti kata-kata hikmat berunsur alam yang terdapat dalam buku teks Bahasa Melayu sekolah kebangsaan (SK) dan sekolah jenis kebangsaan (SJK), dan b) menginterpretasi kata-kata hikmat yang berunsur alam yang terdapat dalam buku teks Bahasa Melayu SK dan SJK. Kajian ini menggunakan pendekatan deskriptif dengan kaedah analisis kandungan yang melibatkan buku teks Bahasa Melayu SK dan SJK. Ringkasnya, terdapat dua kata-kata hikmat dengan unsur alam iaitu ‘masa itu emas’ dan ‘membaca jambatan ilmu’. Kedua-dua kata-kata hikmat ini mempunyai semantik yang berbeza namun kaya dengan pedoman hidup. Ringkasnya, dapatan kajian ini memberi penjelasan yang mendalam terhadap peribahasa Melayu yang dapat digunakan dalam memperkasa pemahaman dan penghayatan nilai peribahasa Melayu dengan lebih berkesan.
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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.008 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.027 | 0.007 |
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".