The Interpretive and Ethical Payoffs of Intention-Curious Rhetorical Reading: Fictionality, Original Paratexts, and Ford’s Impressionism
Bibliographic record
Abstract
ABSTRACT In recent years, debates about whether readers should consider authorial intention have given way to demonstrations of the interpretive and ethical consequences of not doing so. This article takes up a case study featuring an author’s and a critic’s conflicting ideas about authorial intention in relation to the use of fictionality as a rhetorical strategy in narrative fiction. This article demonstrates the value, for successful author–reader communication through texts employing fictionality, of intention-curious rhetorical reading: openness to maximizing the interpretive relevance of statements of authorial intention appearing in paratexts and epitexts. In unpacking the clash between author Ford Madox Ford and critic Gerald Gould vis-à-vis errors of fact and misquotations in Parade’s End, this article takes an historical approach, highlighting the relationship between changing ideas about authorial intention and changing forms of literary criticism, and a theoretical approach, drawing on rhetorical narrative theory and fictionality theory.
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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 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.049 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.004 |
| 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".