Bibliographic record
Abstract
Fear of just censure and the sense of shame it produced kept Roman citizens from doing wrong (Cic. Rep. 5.6). Invective functioned socially as a strategy of social sanction. One amongst a number of commonly identified topics of accusation in the Roman tradition of ridicule was unusual appearance, clothing or demeanour. Not surprisingly, John the Baptist emerges from the desert attired distinctly, demoniacs come out of the tombs so fierce that no one would pass by them (Mt 8:28), a man with an unclean spirit lives amongst the tombs and, even though adorned with fetters and chains, cannot be controlled (Mk 5:15–20). Herod pretentiously puts on the royal robes and is eaten by worms and dies (Ac 12:21). A woman uninvited enters a rich man’s dinner party with an alabaster flask of perfume and anoints the feet of Jesus (Lk 7:38). Clearly, in each case, unusual appearance, clothing, and demeanour suggest a lapse from the appropriate, socially acceptable style of deportment and clothing. Oddities in dress and demeanour were equated with oddities in behaviour and provided a powerful rhetorical means of excluding undesirables from society.
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 | 0.004 |
| 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 | 0.036 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 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".