What everybody knows: embodied information in serious leisure
Bibliographic record
Abstract
Purpose The purpose of this paper is to reconsider the role of the body in information in serious leisure by reviewing existing work in information behaviour that theorises the role of the body, and by drawing selectively on literature from beyond information studies to extend our understanding. Design/methodology/approach After finding a lack of attention to the body in most influential works on information behaviour, the paper identifies a number of important authors who do offer theorisations. It then explores what can be learnt by examining studies of embodied information in the hobbies of running, music and the liberal arts, published outside the discipline. Findings Auto-ethnographic studies influenced by phenomenology show that embodied information is central to the hobby of running, both through the diverse sensory information the runner uses and through the dissemination of information by the body as a sign. Studies of music drawing on the theory of embodied cognition, similarly suggest that it is a key part of amateur music information behaviour. Even when considering the liberal arts hobby, the core activity, reading, has been shown to be in significant ways embodied. The examples reveal how it is not only in more obviously embodied leisure activities such as sports, in which the body must be considered. Research limitations/implications Embodied information refers to how the authors receive information from the senses and the way the body is a sign that can be read by others. To fully understand this, more empirical and theoretical work is needed to reconcile insights from practice theory, phenomenology, embodied cognition and sensory studies. Originality/value The paper demonstrates how and why the body has been neglected in information behaviour research, reviews current work and identifies perspectives from other disciplines that can begin to fill the gap.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.018 |
| Scholarly communication | 0.009 | 0.014 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".