Bibliographic record
Abstract
The connection between rhetoric and hegemony leads us back to Kenneth Burke’s work on political critique and the subtle ways discourse shapes political consciousness. This lecture also looks at how Ernesto Laclau connects rhetoric and the theory of articulation; Joseph Nye’s work on soft power; Timothy Borchers’ discourse on the work of rhetorician Dana Cloud; and Robert Ivie’s thoughts on balancing the opposing notions of identification and division. La connexion entre rhétorique et hégémonie nous ramène aux écrits de Kenneth Burke sur la critique politique et les façons subtiles dont le discours forme la conscience politique. Ce cours examine aussi : la manière dont Ernesto Laclau relie la rhétorique et et la théorie de l’articulation; le travail de Joseph Nye sur le soft power (« pouvoir de convaincre »); les réflexions de Timothy Borchers sur l’œuvre du rhétoricien Dana Cloud; et les pensées de Robert Ivie sur l’utilité d’équilibrer les notions opposées d’identification et de division.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.011 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.017 | 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".