Survei Pemahaman Leksikon Ekologis Bahasa Jawa Pada Mahasiswa PGSD Universitas Sanata Dharma (Tinjauan Ekologi Linguistik)
Bibliographic record
Abstract
<p><em>This study examined the use of Lexicons related to ecological lexicons in Javanese that are commonly used by everyday students. This type of research according to Furchan (1982) was a qualitative descriptive research sub-category of survey research. Research subjects were 96 students from Java (Yogyakarta and Central Java). The instrument developed was a questionnaire. Validation of instruments using the expert judgment of Javanese linguists. The results showed students who were ecological lexicon in Javanese were 53.19%, students who did not understand the ecological lexicon of Javanese were 46.81%. More than half of the students still understand the meaning of the ecological lexicon of the Javanese language. The data was followed up with interviews. The results of the interview revealed that students' understanding of the meaning of the ecological lexicon was not entirely appropriate. Some ecological lexicons of Canada are no longer used in terms of the absence of the main factors. First, youth urbanization in Javanese society. Second, the number of speakers is getting smaller. Third, the changing natural factors, climate, and weather are commonly described by the ecological lexicon are not felt by the majority of Javanese people</em>.</p>
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.026 | 0.005 |
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".