Bibliographic record
Abstract
In this dissertation I argue for a critical re-investigation of several connected rhetorical traditions, and then for the re-articulation of theories of composition pedagogy in order to more fully recognize the importance of embodied differences.Metis is the rhetorical art of cunning, the use of embodied strategies-what Certeau calls everyday arts-to transform rhetorical situations.In a world of chance and change, metis is what allows us to craft available means for persuasion.Building on the work of Detienne and Vernant, and Certeau, I argue that metis is a way to recognize that all rhetoric is embodied.I show that embodiment is a feeling for difference, and always references norms of gender, race, sexuality, class, citizenship.Developing the concept of metis I show how embodiment forms and transforms in reference to norms of ability, the constraints and enablements of our bodied knowing.I exercise my own metis as I re-tell the mythical stories of Hephaestus and Metis, and reexamine the dialogues of Plato, Aristotle, Cicero and Quintillian.I weave through the images of embodiment trafficked in phenomenological philosophy, and I apply my own models to the teaching of writing as an embodied practice, forging new tools for learning.I strategically interrogate the ways that academic spaces circumscribe roles for bodies/minds, and critique the discipline of composition's investment in the erection of boundaries.I propose new ways to conceptualize rhetorical history, embodiment, composition's geographies, pedagogies, and engagements.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.009 | 0.043 |
| Scholarly communication | 0.009 | 0.014 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 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".