More than just a Fine Drink: Processes of Cultural Translation, Taste Formation and Idealized Consumption in the Wine World
Bibliographic record
Abstract
My dissertation, presented as three interrelated studies prepared as standalone articles, uses the cultural practice of wine to examine how ideas, tastes and consumption practices travel and are adopted in new places. Through field observations, interviews and discourse analysis in the established Châteauneuf-du-Pape and the emerging Niagara, I begin by examining how the concept of terroir is expressed and used across a French and a Canadian regional cultural context in Chapter 3. Through a comparative analysis of terroir, a complex French cultural term used to identify and classify artisanal foods and drinks in relation to a specific place, this first study clarifies the factors that drive consistency and change in the translation of a cultural idea like terroir, advancing our understanding of what translates and what must be adapted when a cultural idea travels in a globalized context. In Chapters 4 and 5, I further deepen this questioning by examining how wine consumers and producers in the emerging, non-traditionally wine producing Ontario wine market consider the development of a taste for wine, a cultural good that is often viewed as complex and intimidating. In Chapter 4, I consider how consumers frame their interest in wine to understand how cultural practices and tastes “take”, and become more interesting to cultural consumers. I show that consumers frame their interest in learning about wine in terms of different cognitive, sensory and status pleasures. This chapter builds on emerging research that examines the pleasurable and embodied aspects of cultural practices by investigating how the sensory and cognitive interact to produce engagement with cultural objects and practices like wine appreciation. Chapter 5 examines how wine producers conceptualize the domestic market for their product in a context of emerging wine connoisseurship and nascent wine knowledge. I analyse how producers construct the “good wine consumer” through three key dimensions: 1) spending, 2) tasting, and 3) knowledge. This study contributes to better scholarly understanding of producers’ role in creating conventions of good taste, and of the contours of taste hierarchies in times of shifting cultural standards and cultural democratization trends, alongside continued patterns of distinction.
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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 | 0.008 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.031 |
| Scholarly communication | 0.015 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".