On the Pragmatic Functions of English Rhetoric in Public Speech: A Case Study of Emma Watson’s HeForShe
Bibliographic record
Abstract
The current research is mainly conducted to explore the pragmatic functions of English rhetoric in public speech. To do this, methods of close reading and case studies are adopted. The research first reveals that the boom of public speech programs helps reexamine the art of utterance, during the delivery of which English rhetoric plays an indispensable role in shaping and expressing a speaker’s opinions, and then, with Emma Watson’s HeForShe as a case study, concludes the specific pragmatic functions of English rhetoric: parallelism helps strengthen opinions; irony shows dissatisfaction, disapproval or rejection; rhetorical questions invite no answers, but call for emphasis and sense of urgency; contrast describes difference(s) so as to show preference. Use of proper English rhetoric devices in public speaking as well as in daily life improves communicative effect and efficiency.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.009 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".