The Abyss of Meaning or the Cauldron of Signs: Meaning and Tertium Quid. Shakespeare as a Translator?
Bibliographic record
Abstract
Abstract Sum of atoms or molecules that are the signs that the author of a text organizes in speech, the text contains meaning, in latency. To activate it, reveal it must be interpreted, whether or not the purpose is to translate it. When it comes to translating, the difficulties presented by the translation of normative texts are due in large part to the notional burden, the degree of “juridical status” of the message conveyed by the text and the cultural singularity revealed by its mode of writing. While the substance of a text is of paramount importance in its interpretation, the manner in which it is written and presented – its form – is far from negligible. Each way of saying carries its own, and participates in, the meaning. The approach defined for the translation, sourcing (least-cultural) or targeting (most-cultural), guides the meaning. That is when the final interpretation of the two versions of the instrumental text by the courts fulfils the canonical function of law and language: to say the law by determining the meaning of all or part of a text. Until then, the signs generating the speech and its meaning nested in this place of uncertainty that is the tertium quid, where rest, like the ingredients that the Sisters of Destiny (Macbeth) stir in their cauldron, the signs of where meaning will come out, an uncertain and precarious truth deduced by the original interpreter of the instrumental text, the translator, transcribed into the target text. Would Shakespeare provide an answer to the existential questions posed by the translator, when the spectre (Hamlet) and the witches (Macbeth), enigmatic oracles, answer the protagonists’ ontological questions about the meaning and direction of their lives? The bard indeed launches this injunction: keep law and form and due proportion in Richard II (3.4.43)! Will the translator follow him in each of these three directions?
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.027 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".