“I’m like, whatever you want me to be. I’m the flavor of the day”: A mixed-methods study of the food dispositions and behaviors of mixed-race individuals
Bibliographic record
Abstract
There is a dearth of research on how food serves a tool for the formation and enaction of the social identities of mixed-race people, how these social identities shape the unique food dispositions and behaviors of mixed-race individuals, and how, by virtue of their liminal status, mixed-race consumers are apt to blend and adapt food behaviors from their dual heritages, and subsequently diffuse these adaptations into the broader population. This mixed methods study, entailing semi-structured interviews with mixed-race individuals, followed by an international survey involving 645 mixed-race consumers living in Canada, the USA, and the UK, aims to address these knowledge gaps. Induced from the qualitative data, we disclose four overarching themes regarding the food practices and perceptions, in relation to our mixed-race informants’ identity and their position astride two cultures: (1) ‘you are what you eat’ (food as instrumental for ethnic identity), (2) ‘mixing the best of both worlds’ (integration and transmutation), (3) situational authenticity and awareness of cultural appropriation, and (4) double marginalization, denigration, and self-valorization. The quantitative findings revealed that blending cultural customs, blending food practices, and using products to express mixed-race identity, were all a positive function of the racialized-minority parent’s ethnic maintenance, as well as both independent and interdependent self-construals—demonstrating that racial and cultural blending promulgates these behaviors. Theoretical and practical implications and directions for future research are elucidated.
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 | 0.020 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".