Taste, consumption, and markets an interdisciplinary volume
Bibliographic record
Abstract
"Taste is a core concept for the social sciences and an orienting notion in everyday practice. It is of equal relevance to academics and laypeople alike. Theorizations of taste are frequently multi- disciplinary, bringing an opportunity to cross-fertilize ideas and concepts. At the same time, a reader, challenged by the diverse body and dispersed nature of theories on taste, needs guidance navigating the literature and framing areas of interest. Until now, those interested in an academic perspective on the concept have had to traverse a wide range of literature. This is the first book that assembles a range of writings on taste from across disciplines to provide the reader with a sense of the emerging and expanding boundaries of this field of study. Taste, Consumption and Markets offers a comprehensive and up-to-date review of taste, with an emphasis on how taste shapes boundaries, subcultures, and global culture, complemented by an introduction that provides a scaffold for the reader and a concluding section that reflects on the past, present, and future of research on taste. It shows the latest state of knowledge on the topic and will be of interest to students at an advanced level, academics, and reflective practitioners. It addresses the topics with regard to the sociology of taste and consumption and will be of interest to researchers, academics, and students in the fields of consumer studies, consumption ethics, sociological perspectives on consumption, and cultural studies"...
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.017 | 0.003 |
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".