Bibliographic record
Abstract
Purpose The purpose of this paper, aimed primarily at readers' advisors in public libraries, is to take a critical look at the concept of escapism in leisure reading, highlight the multiple aspects of escapism, present it in a more positive light, and show that escapism is associated not only with light entertaining reading but also with the reading of serious literature. Design/methodology/approach The paper takes the form of a critical review of literature and real‐life examples. Findings It is found that escapism in leisure reading is a very complex and composite concept. Although it is not always associated with pleasure and relaxation, it is always a transformative and thus instrumental and functional experience in the reader's life. Research limitations/implications The paper provides a valuable discussion of the literature on escapist reading. Practical implications The paper considers the importance of escapist reading and whether would this be of benefit to library professionals involved in the public library sphere. Originality/value Multiple and diversified examples of escapism through leisure reading are reviewed and critically analyzed; and the application of this knowledge in readers' advisory work is clearly delineated.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.017 | 0.076 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".