Eating for Taste and Eating for Change: Ethical Consumption as a High-Status Practice
Bibliographic record
Abstract
Abstract Under what conditions is ethical consumption a high-status practice? Using unique food consumption survey data on aesthetic and ethical preferences, we investigate how these orientations to food are related. Existing research on high-status food consumption points to the “foodie,” who defines good taste through aesthetic standards. And emergent evidence suggests the “ethical consumer,” whose consumption is driven by moral principles, may also be a high-status food identity. However, ethical consumption can be practiced in inexpensive and subcultural ways that do not conform to dominant status hierarchies (e.g., freeganism). In order to understand the complex cultural terrain of high-status consumption, we investigate how socioeconomic status (SES) is related to foodie and ethical consumer preferences and practices. Using a k-means cluster analysis of intercept survey data from food shoppers in Toronto, we identify four distinct clusters representing foodies, ethical consumers, ethical foodies, and those whose preferences involve neither aesthetic nor ethical ideals. Through multinomial logistic regression, we find that while high-status consumers can be foodies or ethical consumers, the highest status consumers prioritize ethical and foodie preferences. Respondents’ reported shopping locations corroborate the results of the regression analyses. The taste preferences of the highest status consumers are associated with culinary sophistication and moral considerations, suggesting that high cultural capital tastes incorporate aesthetic and ethical dimensions. These results contribute to literature examining how food consumption repertoires can produce and reinforce classed boundaries and to literature on tastes that has focused on aesthetics to the neglect of ethical ideals.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".