Dante’s True Constellation: Writing the Stars in Aratus, Ovid, and <i>Paradiso</i> 13
Bibliographic record
Abstract
This essay uses the constellation writing of Ovid and Aratus to gain comparative perspective upon Dante’s constellation writing in Paradiso 13. Though Dante did not know the Greek poetry of Aratus, the two authors share the goal of bringing the heavens into human view. For Aratus, the constellations are tools for enabling celestial observation. The constellations give form to the firmament. They enable observers to distinguish between stars and therefore to perceive and track celestial structure and motion. But the constellations do not leave a mark upon the sky. Rather, as Ovid’s poetry also helps show, they must continually be rediscovered and reformed through guided observation. The essay explores how these aspects of constellations help Dante to imagine unique forms of literary creativity in Paradiso 13. For Dante, the heavens need to be divided up by fictions in order to be described by poetry. But Dante’s constellation writing suggests how such fictions might not be etched onto the world once and for all. Instead, like constellations, they emerge in the moment of being perceived. In this sense, constellations help Dante to imagine creativity without impact; that is, human art that does not mark or change a preexisting environment. Dante’s constellations gain a sense of immediacy from their ephemerality and their reliance upon a perceiving viewer or reader. Constellation writing helps Dante to bridge the gap between human and divine art by turning human perception into a mirror of divine creation.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.012 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| 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".