Homer like Thucydides? Hobbes and the Translation of the Homeric Poems as an Educational Tool
Bibliographic record
Abstract
Thomas Hobbes had a deep and, to some extent, controversial relationship with both the classics and the classical world. At the beginning of his career as a political thinker, for example, he translated from Greek into English the History of the Peloponnesian War by Thucydides. Despite this initial involvement, the philosopher subsequently stopped translating, although, several decades later, in the final period of his life, he decided to return to this activity, translating the Iliad and the Odyssey, apparently for his own amusement, nothing more. However, recent literature has suggested that these works, as in the case of his translation of Thucydides’s work, hid another motive: he wanted to continue spreading his political thought in a period when he no longer able to do it in the usual way because of old age, illness, and, above all, censorship. By offering a comparison of the original Greek texts and Hobbes’s translations, this essay aims to show how he handled the political elements of the Iliad and the Odyssey that did not fit his political theory and ran the risk of undermining his attempt to teach moral and political virtue. It focuses in particular on the political question of overlapping sovereignties, with a view to explaining some systematic uses of translation choices that clearly deviate from the Greek.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.010 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".