Prolegomena to a translingual study of literary labels: Shake-speares Sonnets and the son(n)et in early modern England
Bibliographic record
Abstract
In this article I focus on sonnets from a translingual lexicological point of view, asking what influence the spelling of the word itself might have had on the perception and definition of the poems it served to designate. I treat the word “son(n)et” as a lexical palimpsest, a condensed version of the history of English borrowings from continental Romance languages, asking what it tells us about the transnational character of English literature in the early modern period. Bearing in mind orthographic fluidity at the time, in England as well as in France and Italy, I look at mentions of “sonnets” in Shakespeare’s works and as Shakespeare’s works, compared to other publications from the same period. As opposed to the variety of spellings from one work to another, and even sometimes within one single collection of poems, which is found in most early modern English texts, “sonnet” is always spelt with two n’s when it comes to Shakespeare. What can we infer from this coherence in spelling?
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.014 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".