Bibliographic record
Abstract
The listeners who follow them are like performers, hired and bought. They huddle together with a middleman; in the middle of a basilica sportulae are handed out as openly as in a triclinium. They run from one court to another for the same wage. Hence these people are called not without humour Sophocleses from sophos and kaleisthai; in Latin the name given them is laudiceni. Sherwin-White in his commentary on this passage deals only with the explanatory words in Greek in the manuscripts, which he would delete as a gloss.2 One could add that Pliny would have known that kalein and not kaleisthai was required as an explanation, since the parasites shout Sophos, i.e., kalein sophos-Hoorayshouters, while sophos kaleisthai s not meaningful at all; kaleisthai seems to be a mistake prompted by the word vocantur. But it is unclear, despite Sherwin-White, why we need the Latin variant. The whole explanation looks like a grammarian's gloss, since Hooray-shouters are obviously the claqueurs wanted in a law court, while Dinner-praisers interrupts the argument. There is a more interesting problem. Why does Pliny find it obvious that handing out sportulae as bribes in a basilica should be compared to handing them
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.499 | 0.149 |
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".