Teaching Specific Purpose Translation: Utilization of Bilingual Contract Document as Parallel Corpus
Bibliographic record
Abstract
This study introduced the specific purpose translation teaching to Indonesian undergraduate students at Universitas Al-Azhar Medan, Indonesia. The courses were attended by the Business and Economics students who are new to translation. As parallel corpus, bilingual contract documents in Indonesian and English were chosen to help the students to grasp the conventions and norms in both languages. Dealing with difficulties in teaching specific purpose translation, the procedures and sequence analysis were conducted. The procedures consist of preliminary test, introduction to translation strategy, discussion by compare two translation text, and final test. The sequence analysis were conducted on discussion. This analysis based on semantic, lexical and syntactical aspect. The analysis shows that contract terms were characterized by nominalization, passive voice, sentence length and complexity, impersonality, binominal and multinominal expressions, unusual word order, one syllable and phrase equivalence. The students also recognizes the archaicsm, repetition and redundancy, synonymy and redundancy and absorption of foreign words. Based on the commentaries of the students, the use of parallel corpus as a tool in translation exercise has improving their ability in translating and drafting bilingual contract documents. In the end of course, 24 students completing the course and 19 (80%) of them are ready to attend the advance course.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 teacher head, 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".