An interdisciplinary platform for information behavior research in the liberal arts hobby
Bibliographic record
Abstract
Purpose – The liberal arts hobby is a leisure pursuit that entails the systematic and fervent pursuit of knowledge for its own sake. The purpose of this paper is to introduce the liberal arts hobby as a setting for information behavior research. Design/methodology/approach – The method of interdisciplinary translation work is used to relate existing research from the specialties of leisure studies, adult education, and information behavior. Drawing from leisure studies, the liberal arts hobby is presented within the context of the serious leisure perspective, a theoretical framework of leisure. Also, relevant research. Findings – The basic informational features of the liberal arts hobby and adult learning project are discussed in terms of three issues of current interest within information behavior scholarship. The issues are: first, social metatheory and the ideal level of analysis; second, time and information behavior; and third, information behavior in pleasurable and profound contexts. Research limitations/implications – Research into everyday life, serious leisure and hobbies is extended and methodological tools are provided. Practical implications – Information professionals, such as public librarians or systems designers, will have a better understanding of the information experience of a popular hobby group and be better able to meet their information needs. Social implications – Awareness and understanding of the liberal arts hobby will be increased across the field of information science, thereby creating a better alignment between the field and society. Originality/value – The paper is the first to establish an interdisciplinary starting point for information behavior research in the liberal arts hobby.
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 | 0.029 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.004 | 0.012 |
| Scholarly communication | 0.016 | 0.011 |
| Open science | 0.002 | 0.015 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.030 | 0.007 |
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".