Bibliographic record
Abstract
Food studies as a distinct field within sociology has seen extensive interest and growth. Previously, studies of food production and consumption typically fell under the purview of research on health, agrarian studies, development sociology, agricultural economy, or social anthropology. Rural and natural resource sociologists especially have long emphasized the management and impacts of food production systems in their work. In classical tomes food was typically mentioned as an example of social classification or of social problems rather than a distinct object of study. Since the 1980s sociologists’ attention to how food strengthens social ties; marks social and cultural differences; and is integrated into social organizational forms, ranging from households to empires, has grown. Early-21st-century interest in food by both researchers and the larger public follows heightened awareness of the global character of markets and politics, concerns with health and safety, and the ways cooking and dining out have become fodder for media spectacle. Today sociologists of food display considerable diversity in their theoretical approaches, research methods, and empirical foci. Sociologists draw upon both classic and contemporary sociological theorists to study food’s production, distribution, and consumption as well as how food and eating are integrated into social institutions, systems, and networks. Topically, sociologists contribute to research on inequality and stratification, culture, family, markets, politics and power, identity, status, social movements, migration, labor and work, health, the environment, and globalization. Sociological work on food in the late 20th and early 21st centuries is characterized by two overlapping threads: food systems (derived in part from scholarship on agricultural production and applied extension as well as environmental, developmental, and rural sociology) and food politics, identity, and culture (which reveals social anthropological and cultural-historical undertones). Both are nested in the emerging interdisciplinary research field of food studies, which has gained greater institutional footholds at universities in Europe and Australia than in the United States and Canada (but this may be changing). Sociologists working across the two threads examine issues of food and inequality, trade, labor, power, capital, culture, and technological innovation. This article maps out social science research and theorizing on what we eat, how we produce and procure food, who benefits, with whom we eat, what we think about food, and how food fits with contemporary social life.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.402 | 0.236 |
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".