The Development of an Emotional Response to Literature Measure: The Affective Response to Literature Survey
Bibliographic record
Abstract
Based on theories of emotional intelligence, adult education, psychology of reading, and emotions and literature, this study was designed to develop and validate the Affective Response to Literature Survey (ARLS), a psychological instrument used to measure an emotional response to literature. Initially, 27 items were generated by a review of research relevant to emotional intelligence and emotional effects of literature. A panel of 10 experts rated 27 proposed items. After applying the content validity ratio to the expert’s ratings, 18 items were retained. The instrument was then administered to 165 individuals to assess psychometric properties. The ARLS demonstrated high internal consistency (Cronbach’s alpha=.90) and test-retest reliability (r=.90, p < .001). Factor analysis extracted four factors: (a) Reflective Synthesis, (b) Acting with Volition, (c) Processing, and (d) Empathetic Responding. The four factors have important implications for conducting research sensitive to literature, emotional intelligence, and transformational learning.
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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 | 0.021 | 0.053 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".