Bibliographic record
Abstract
From Homer to the Hellenistic period and beyond, one of the defining features of ancient Greek cultural history and its ongoing interpretation and adaptation is athletic competition. For the ancient Greeks, athletics, along with warfare, was a primary arena for the contestation of status and for the attainment of superiority and excellence. In antiquity, writers recognized the central role of athletics in Greek culture and identity: Thucydides’ Perikles stresses competitive festivals as one of the elements that make Athens an example for Greece (2.38–41); Herodotus includes common festivals in his famous definition of “Greekness” (8.144); moreover, the Persians marvel that οἳ οὐ περὶ χρημάτων τὸν ἀγῶνα ποιεῦνται ἀλλὰ περὶ ἀρετῆς (“[The Greeks] contend not for money but for arete ,” Hdt. 8.26). Pindar, as frequently, puts it best: ὃς δ’ ἀμφ’ ἀέθλοις ἢ πολεμίζων ἄρηται κῦδος ἁβρόν / εὐαγορηθεὶς κέρδος ὕψιστον δέκεται, πολιατᾶν καὶ ξένων γλώσσας ἄωτον (“but he who wins luxurious glory in games or as a solider / by being praised gains the highest profit, the finest words from tongues of citizens and foreigners,” Isthm. 1.50–51).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.247 | 0.115 |
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".