The qualitative value of reading fiction : seven life stories about the meaning of reading fiction for elderly people – a study with features of life history
Bibliographic record
Abstract
The purpose of this thesis is to form an idea about the qualitative value and meaning of reading fiction in a psychological perspective and over a lifetime. Seven women, 68-79 years old, were interviewed about their reading habits of fiction in their lifetime. The material is presented as life stories. I use an inter-nordic research project called the SKRIN project which looks upon reading habits from an individualistic and psychological perspective. I also refer to an American study which focus on reading development with roles readers take in different ages of life written by J A Appleyard. I use a Canadian paper which deals with reading fiction for emotional knowledge written by Catherine Sheldrick Ross. I touch upon two other fields of research; reading in the perspective of gender and reader-response criticism. The method I use is a combination of qualitative interviews, life history method and studies of literature. The study shows that literature of significant meaning is the fictional moods of realism, poetry, romance and detective stories. Particularly memorable books belong to the fictional moods realism and romance. Realism is important for identification, social understanding and social connection. Poetry is read for many reasons among them therapy in crisis. Reading romance appears to be of decisive importance psychologically for women. Detective stories are primarily read for relaxation and escape from reality. Many of the women in the study have been helped by books in different situations in life.
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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 | 0.007 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| 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".