Exploring engagement with non-fiction collections: sociological perspectives
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Purpose The purpose of this paper is to build on limited understandings of how readers engage with non-fiction. Drawing from prior research and three recent case studies involving non-fiction reading, this paper considers heterogeneity in modes of reading and the central role of libraries in fostering non-fiction reading cultures. Design/methodology/approach Findings from three recent case studies of non-fiction reading about relationship advice; developmental disorders; and financial planning, based on qualitative interviews, participant observation and survey data, are used to assess and expand understandings of non-fiction reading and collections. Findings There is considerable heterogeneity in modes of non-fiction reading, and readers often appropriate non-fiction texts for purposes unintended by the authors. Both physical and online libraries function as sites where non-fiction reading can be used by a broad range of demographic groups to participate in individual or group-based resistance to structural and cultural sources of power and inequality. Practical implications This paper provides insight into the role and value of non-fiction collections. Social implications Findings speak to the value of robust funding for print and online non-fiction collections in communities and schools. Originality/value This paper offers new empirical and theoretical insight into how non-fiction collections are used by a range of demographic groups in community and school contexts. Sociological theories are introduced to highlight the role of non-fiction collections in facilitating social change at individual and group levels.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it