Reading Rhetorically: Discussing the Ethics of Narrative Form
Bibliographic record
Abstract
In this study, we explore discussions of literature in a high school English Language Arts (ELA) classroom, examining how students read rhetorically. Reading rhetorically considers the ethical effects of narrative content as it is mediated through character dialogue and action, narrator discourse, and the author's organization: a narrative as a story told to someone for some rhetorical purpose. Drawing from rhetorical narratology, we analyzed data collected in a 12th-Grade ELA classroom during student-driven Socratic seminars to ask: how did students address the ethics of various narrative situations as they talked about literature? We found that youth engaged in interpretive discussions that grappled with the complexities of ethical positioning in narrative. We argue that ELA classrooms are key spaces to help students examine how narratives act on readers, how readers act on narratives, and the ethical dimensions of such interpretive work.
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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 | 0.016 | 0.026 |
| 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 | 0.040 |
| Scholarly communication | 0.014 | 0.015 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".