Reading, Hearing, and Seeing Poetry Performed
Bibliographic record
Abstract
The study investigated the differences between reading a poem, listening to a poem, and watching a live poetic performance. Stimulus materials included three poems with positive and three with negative themes written by Michelle Hilscher. The 32 participants, including an equal number of males and females in psychology and literature, completed a General Poetry Questionnaire (GPQ) to indicate their experiences and impressions of poetry coming into the study. Following the presentation of each poem, participants answered 14 5-point scale questions in a Poetry Reception Questionnaire (PRQ) which captured cognitive and emotional nuances of poetry reception, and one open-ended question where the participants wrote freely about the poem's meaning. A factor analysis of the GPQ distinguished primarily between participants' responsiveness to the stylistic features and subject matter of poetry. A factor analysis of the PRQ identified global absorption, interpretive engagement, and narrative representation as the primary activities involved in responses to the six poems. A factor analysis of qualitatively derived meaning categories (MC) contrasted an elaboration of style and metaphor as opposed to subject matter and story line. Analyses of variance showed that respondents preferred to read poetry as compared to hearing, or seeing it performed live. By reading poetry themselves, participants were able to explore and interpret the literary devices in poetry in an independent and creative manner, whereas participants who experienced a live performance seemed constrained in their ability to be actively involved in their experience of poetry and therefore found the poetry less engaging.
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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 | 0.001 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".