Bibliographic record
Abstract
As a subject of study, “comfort food” is relevant to a number of scholarly disciplines, most obviously food studies, folkloristics, and anthropology, but also American culture studies, cultural studies, global and international studies, tourism, marketing, and public health. This volume explores the concept of “comfort food” primarily within a western context with examples from Atlantic Canada, Indonesia, England, and various ethnic, regional, and religious populations as well as rural and urban residents in the U.S. It includes studies of a wide range of dishes—bologna to chocolate, sweet and savory puddings, fried bread with an egg in the center, dairy products, fried rice, cafeteria fare, sugary fried dough, soul food, and others—exploring ways in which they comfort or in some instances cause discomfort and how they are connected to a sense of emotional well-being. Some essays analyze the phenomenon in daily life; others consider comfort food in the context of cookbooks, films, Internet blogs, literature, marketing, and tourism. Recognizing that what heartens one person might discomfort another, the collection is organized accordingly, from pleasant and comforting to unpleasant or discomforting food experiences. Those foods and food experiences are then related to concepts and issues such as identity, family, community, nationality, ethnicity, class, sense of place, tradition, stress, health, discomfort, guilt, betrayal, and loss, contributing to a deeper understanding of comfort food as a significant social category of human behavior.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.089 | 0.026 |
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".