Bibliographic record
Abstract
This article provides a sustained close reading and literary onomastic analysis of Derek Walcott’s “Sainte Lucie”, arguing that the poem presents names as poetic terms of art: sites of mimicry, misnomer, and transformation. The poem confronts the philosophical and linguistic instability at the heart of naming. By weaving together multilingual references, colonial and postcolonial toponyms, oral traditions, and etymological slippages, names are shown to act not as referential tools but as creative misrepresentations. Resisting referential realism, Walcott presents a name not as a mirror of the world but as a poetic artifact with an aesthetic value derived from its capacity to generate meaning beyond its referent. Ultimately, the article shows that Walcott’s poetics do not seek to repair the inherent aporia between name and referent but to embrace it as the very grounds of art. In contrast to dominant philosophical theories (from Frege to Russell to Searle), Walcott’s approach recasts the name as a transformative site of memory, loss, and aesthetic form and naming as a mode of poetic authorship that sustains cultural identity amidst historical dislocation. Within this view, naming becomes a mode of poiesis.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.036 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".