Symbolic Cognition in Poetic Experience: Re-representing the Paraphrase Paradox
Bibliographic record
Abstract
Abstract This article considers an apparent tension between, on the one hand, a widespread belief among literature teachers that the appreciation of a poem involves an experience of form-content inseparability and, on the other hand, these same teachers’ use of paraphrase to encourage appreciation. Using Terrence Deacon’s model of art experience, I argue that the tensions of this ‘paraphrase paradox’ mirror tensions inherent in poetic experience. Section II draws upon work by Rafe McGregor, Peter Lamarque, and Peter Kivy to frame an approach to the form-content distinction, and to offer a brief overview of the paraphrase paradox. Sections III-IV summarize Deacon’s model of aesthetic experience, and argue that this model implies that poetic experience both triggers an impulse towards paraphrase, and frustrates this impulse. Section V looks at implications for the poetry teacher’s attempts to navigate the paraphrase paradox. Section VI tests these implications through an analysis of Philip Larkin’s poem ‘Faith Healing’.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.021 |
| Scholarly communication | 0.007 | 0.012 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".