Theoretical Foundations of Translation Studies
Bibliographic record
Abstract
Epistemologies of translation are a complicated subject that is beyond the scope of this article. As such, only the critical points have been addressed in this paper. One key epistemological issue is the analysis of discourse in any science. In this article, four scenarios of translation studies have been discussed. An underlying concept in translation studies is the issue of fidelity in translation. In this paper, the trajectory of this concept is analyzed in brief. It is followed by a reflection on two fundamental concepts of source oriented (Sources) and target oriented translation approaches, as they occupy a particular position in the translation. The last section of the article investigates dichotomies in the field of translation studies, including the theory of the action, the untranslatability versus translatability, art versus science, and etc. In this paper, we try to study theoretical principles of translatology. So we consider four important speeches of Jean Rene Ladmiral: Prescriptive translatology, Descriptive translatology, Productive translatology, scientific translatology and then we consider faithfulness in translation. Ladmiral suggests two concepts for fidelity in translation: The source oriented (sources) and target oriented. These two concepts are the fundamental concepts in translatology. In the next step the translation science is investigated in various languages such as English, German and at last in French. Finally, we take a look at binary concepts: Theory vs. action, Translatability vs. untranslatability, Art vs. Science. This paper is in epistemology scope of translation and does not have pedagogical aspect, in other words, it is a function-oriented translation.
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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 | 0.016 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.005 | 0.042 |
| Scholarly communication | 0.012 | 0.013 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.015 | 0.003 |
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".