On the Inter-Subjectivity in Translation: Viewed from “Triangulation” Model
Bibliographic record
Abstract
Most studies of inter-subjectivity are about the translators’ subjectivity, which pay less attention to the subjectivity of writers and readers. Some papers center on binary dialogue among translation subjects, and place one subject in the center. Based on Davidson’s triangulation model, the paper provides a clearer ternary dialogue for inter-subjectivity. Davidson adopts “triangulation” to express the person-person-world interaction in the language communication. Translation, as the cross-cultural communication involving many subjects, is the result of the triangulation among the subjects. Triangulation in translation should be: a writer, a source text and a translator; a translator, a target text and a target reader. Based on triangulation, the paper creates distance and width among a writer, a source text and a translator; a translator, a target text and a target reader to discuss the inter-subjectivity. Adjusting the distance and width to approach the optimized triangle is to explore how to achieve the best translation. Based on these two three-dimensional multi-directional interactions with triangulation, the paper achieves the fusion of visual realms among the translation subjects.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".