Analisis Semiotika Pada Poster Manner Oleh Perusahaan Biro Transportasi Kota Nagoya Tahun 2018
Bibliographic record
Abstract
Penelitian ini mengenai tanda lingual dan non-lingual yang terdapat di dalam poster manner oleh perusahaan biro transportasi kota Nagoya yang terbit pada bulan Oktober tahun 2018. Ilustrator menghubungkan tata krama menggunakan transportasi umum dengan karakter tokoh-tokoh samurai pemersatu Jepang. Pada poster, terdapat tanda lingual berupa kalimat dalam bahasa Jepang serta tanda non-lingual berupa gambar-gambar dari karakter para pemersatu Jepang. Penelitian ini merupakan kajian semiotik. Metode yang digunakan dalam penelitian ini ialah metode kualitatif deskriptif. Data dianalisis dengan menggunakan metode padan dan menggunakan teknik pilah unsur penentu (PUP). Peneliti menggunakan teori Roland Barthes untuk menganalisis data. Hasil analisis data disajikan secara informal. Hasil penelitian ini menunjukkan bahwa pesan-pesan yang ingin disampaikan pada poster manner oleh perusahaan Biro Transportasi Kota Nagoya tahun 2018 adalah mengenai tata krama yang harus dipatuhi oleh masyarakat Nagoya dalam menggunakan transportasi umum, agar semua penumpang transportasi umum dapat menikmati perjalanan dengan tenang.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.036 | 0.009 |
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".