Bibliographic record
Abstract
The lectures in this series open with general comments about rhetoric, rhetorical questions, moral problems, and issues relating to the connections between emotions and persuasion. Even though persuasion may be a foundation point of rhetoric, beginning with Henry Johnstone’s arguments, the opening lecture teases out why rhetoric should be understood more broadly and positions upcoming lectures in the realm of scholars’ rhetorical thoughts both ancient and present. Les cours dans cette série commencent par des commentaires généraux sur la rhétorique, sur les questions rhétoriques, sur les problèmes moraux, et sur les rapports entre émotions et persuasion. Même si la persuasion peut être à la base de la rhétorique, le premier cours, en commençant par les arguments de Henry Johnstone, indique pourquoi il vaudrait mieux comprendre la rhétorique dans un sens plus large et situe les cours à venir dans le contexte de réflexions sur la rhétorique provenant de penseurs anciens et modernes.
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.010 |
| Insufficient payload (model declined to judge) | 0.078 | 0.037 |
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".