Bibliographic record
Abstract
The following is a personal manifesto of the state of 21st-century rhetoric. Rhetoric is so intrinsically bound into all aspects of life and all communication environments that it appears inevitable to communicate by using some form of rhetoric. Though, the ethical nature of rhetoric comes into question when we consider the ways rhetoric might be used for good and for evil. This article explores the ethical state of rhetoric today — what it should or shouldn't be, where rhetoric went right and where rhetoric may have gone wrong, and if the current rhetorical state is our reality, our dream, or our nightmare. First, by establishing rhetoric as a persuasive communication strategy that can be easily learned and both innocently and connivingly used, this article then explores if or how rhetoric can be used in "right" and/or "wrong" ways, and what this means for the present and future state of rhetoric. This article was written as an end of term paper in a classical and modern rhetoric course.
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 | 0.011 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.007 | 0.022 |
| Scholarly communication | 0.016 | 0.014 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.016 | 0.004 |
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".