Translation, Interpretation, and Common Meaning: Victoria Welby’s Significal Perspective1
Bibliographic record
Abstract
As she worked through the nineteenth century Victoria Welby elaborated a fascinating theory of translation based on her theory of sign and meaning, which she designated with the term significs. This means to say that, on the one hand, Welby’s theory of translation took account of the vastness and variety of the world of signs, therefore of the unbounded nature of translative-interpretive processes which cannot be limited to the mere transition from one language to another. The condition for interlingual translation in the human world is the larger context where translative processes converge with life processes and maybe push beyond in what would seem to be an unbounded cosmic dimension. On the other hand, that Welby should have related her translation theory to her theory of sign and meaning also implies that she founded her translation theory in a theory of value recognizing the inevitable importance of the latter when translating within a single language as much as across different languages in a plurilingual and intercultural world. Ultimately, in the properly human world, to translate means to interpret, that is, to translate transfiguring and transvaluating significance.
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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 | 0.008 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.016 | 0.095 |
| Scholarly communication | 0.014 | 0.017 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.007 | 0.010 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".