Introduction: Looking at Food Practices and Taste across the Class Divide
Bibliographic record
Abstract
This editorial introduces a Special Issue on food practices and social inequality by outlining a dichotomous tendency in policy-related, academic and populist accounts of the relationship between food and class. The Special Issue aims to move our understanding beyond this dichotomous divide, which privileges either middle-class discerning taste or working-class necessity in understandings of the determinants of food practices. The papers call attention to the diverse, complex forms of critical creativity and cultural capital employed by individuals, families and communities across the spectrum of social stratification, in their attempts to acquire and prepare food that is both healthy and desirable. The papers report on research carried out in the United States, Canada, Mexico and Denmark, and cover diverse contexts, from the intense insecurity of food deserts to the relative security of social democratic states. Through quantitative and qualitative cross-class comparisons, and ethnographic accounts of low-income experiences and practices, the papers examine the ways in which food practices and preferences are inflected by social class (alone, and in combination with gender, ethnicity and urban/rural location). Thus, the Special Issue offers a debunking of the figure of the uncritical, uncultured low-income consumer. Calling for the development of a more nuanced, dynamic account of the tastes and cultural competences of socially disadvantaged groups, the editorial concludes by underlining the simultaneous need for structural critiques of the gross inequalities in the degrees of freedom with which different individuals and groups engage in food practices.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.011 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.012 | 0.007 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.008 | 0.013 |
| Insufficient payload (model declined to judge) | 0.012 | 0.004 |
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".