Managing documents at home for serious leisure: a case study of the hobby of gourmet cooking
Bibliographic record
Abstract
Purpose This paper aims to describe the way participants in the hobby of gourmet cooking in the USA manage culinary information in their homes. Design/methodology/approach The study utilizes domain analysis and serious leisure as a conceptual framework and employs an ethnographic approach. In total 20 gourmet cooks in the USA were interviewed at home and then their culinary information collections were documented through a guided tour and photographic inventory. The resulting ethnographic record was analyzed using grounded theory and NVivo software. Findings The findings introduce the personal culinary library (PCL): a constellation of cooking‐related information resources and information structures in the home of the gourmet cook, and an associated set of upkeep activities that increase with the collection's size. PCLs are shown to vary in content, scale, distribution in space, and their role in the hobby. The personal libraries are characterized as small, medium or large and case studies of each extreme are presented. Larger PCLs are cast as a bibliographic pyramid distributed throughout the home in the form of a mother lode, zone, recipe collection, and binder. Practical implications Insights are provided into three areas: scientific ethnography as a methodology; a theory of documents in the hobby; and the changing role of information professionals given the increasing prevalence of home‐based information collections. Originality/value This project provides an original conceptual framework and research method for the study of information in personal spaces such as the home, and describes information phenomena in a popular, serious leisure, hobby setting.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.012 | 0.005 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".