Bibliographic record
Abstract
This paper proposes a new methodology for describing, explaining, and tracking the linguistic and non-linguistic shifts that occurred in the ancient biblical translations. It first surveys the approach to Descriptive Translation Studies (DTS) taken by Gideon Toury, outlining pertinent theoretical points. Second, it summarizes the principles and methods of Optimality Theory (OT), arguing that this linguistic model may be harnessed in order to benefit the study of ancient translations. Third, this article applies the theory and methods developed here to a single sample verse, 2 Sam 11:1. Through this study, I demonstrate that the combined theoretical and methodological model provided by DTS and OT allows us to identify, describe, evaluate, and organize the norms constraining the translator of Tg. Jon. to Samuel—and, by extension, to the other ancient Versions. Finally, I argue that we may use OT's notational system to capture regularities and anomalies in ancient translations, outlining their respective “grammars.”
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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 | 0.007 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.019 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".