Jean Chrysostome et les exempla tirés de l'histoire impériale récente
Bibliographic record
Abstract
En général, on constate que Jean Chrysostome, bien que prédicateur brillant et excellent exégète, insère peu d’ exempla provenant de l’histoire récente dans ses homélies. Cela est d’autant plus remarquable que lorsqu’il nous donne, dans la 15 e homélie sur l’épître aux Philippiens (PG 62,294.28-295.46), une liste des malheurs qui affligent les empereurs, de Constantin à Arcadius, les exempla qu’il choisit se distinguent quelquefois fortement de la version officielle de la propagande impériale. Cet article propose une traduction avec commentaire de cette section de la 15 e homélie et vise à démontrer, par une analyse du contexte socio-politique, que Jean cherchait à satisfaire sa propre παρρησία et le goût de son audience pour le sensationnel au point de sembler ne plus être conscient des possibles conséquences politiques, en particulier celle de son exclusion de la cour, provoquée entre autres par cette revue critique des empereurs.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.012 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.011 | 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".