Bibliographic record
Abstract
In our relativistic age the practice of flattery is not seen as a dangerous societal malaise, let alone as a mortal sin in flatterers and an inducement to sin in their victims. This tolerant view did not prevail in the medieval world. Constant attacks on the social and personal harm wrought by flatterers are made by patristic and scholastic authorities from Augustine's day to that of a near-contemporary of Chaucer and Langland, John Bromyard, whose tone grows especially vehement in his lengthy capitula on Adulatio in the Summa Praedicantium. Nor did this universal condemnation die out with the advent of Renaissance humanism. In The Praise of Folly Erasmus satirises the practice of flattery, saying it reigned in chief at the courts of princes, a charge echoed by his friend Thomas More in Utopia. Even before their era, voices were raised against the malaise, notably by Cicero in De Amicitia. He quotes Terence as saying "Flattery produces friends; the truth breeds hatred" and then adds:
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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 | 0.016 | 0.041 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".