Expressive reading: A phenomenological study of readers' experience of Coleridge's The rime of the ancient mariner.
Bibliographic record
Abstract
To articulate what constitutes expressive reading, we conducted a phenomenological study of readers’ responses to Samuel Taylor Coleridge’s poem, The Rime of the Ancient Mariner. After reading the poem twice during 1 week, each of 40 readers chose five passages that they found striking or evocative and then commented on each one. Numerically aided phenomenological methods [(Kuiken, D., & Miall, D. S. (2001). Numerically aided phenomenology: Procedures for investigating categories of experience. Forum Qualitative Sozialforschung/Forum: Qualitative Social Research, 2(1). Retrieved from http:// www.qualitative-research.net/index.php/fqs/article/view/976] were used to (a) compare these commentaries, identifying and paraphrasing recurrent meaning expressions (called constituents); (b) create matrices reflective of the profiles of constituents found in each commentary; (c) create clusters of commentaries according to the similarities in their profiles of constituents; and (d) examine each cluster to ascertain their distinctive attributes. Among the six distinct types of commentary identified, one in particular involved (a) metaphoric and quasi-metaphoric engagement with sensory imagery from the poem; (b) progressive transformation of an emergent affective theme; and (c) metaphoric blurring of boundaries between the reader’s and narrator’s perspectives. This mode of reading, which we call expressive enactment, contrasted with five other types of response: ironic allegoresis, aesthetic feeling, autobiographical assimilation, autobiographical diversion, and nonengagement.
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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 | 0.006 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.012 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.002 | 0.005 |
| 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".