"How do young adults respond to emotionally evocative fiction? An empirical study of young readers' reactions to Inger Edelfeldt´s short story 'Kaninernas himmel' (Rabbit Heaven)"
Bibliographic record
Abstract
Fiction-reading has, since 1990, entered a completely new phase with the establishment of the internet society. This has caused fears that the young generation will abandon traditional fiction and maybe even lose the special kind of competence that this kind of reading presupposes. The aim of this study is to identify and analyze young adults´(19-29) of their reader reactions to an emotionally evocative story. The respondents were asked to write down their reactions like emotions, thoughts, associations and reflections comprehensively. Grounded theory was chosen as theoretical and methodological starting-point. / Results show that categories as emotional, ethical and psychological, self-reflecting and creative were found in the respondents´reactions. Reading strategies found were close (subjective), distanced (objective), or both. Initial reactions are important in the establishment of reading strategy, which also is important in the evaluation of the story. Emotional or self-reflexive reactions showing closeness to the text, initiates creative reactions, which distance to the text does not. Bisected reading strategy leads to disappointment and frustration in default of emotional reactions. Analogies to literature occur equally in both reading strategies. Various kinds of using the text occur: The story can be used for therapy, but also in a future, professional context. The study shows that close and personal reading strategy results in more categories and dimensions than the distanced reading strategy does. Ambience like a relaxed and open meeting with the text, a physical and mental space surrounding the act of reading, seem to have had some influence.
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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 | 0.005 |
| 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 | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".