Food, culture, and identity in multicultural societies: Insights from Singapore
Bibliographic record
Abstract
The choice of food practices can be influenced by one's identity in many societies, but has mostly been evaluated in light of the maintenance of cultural identity in migrant populations. This study focused on understanding the influence of identity on food practices among individuals in multicultural societies. We conducted 18 focus group discussions (n = 130) among Indian, Chinese and Malay women in Singapore. Focus group transcripts were analysed using Thematic Analysis both inductively and deductively. Deductive analysis was framed within a Social Representations Approach, a social psychological theory that allows a deeper understanding of the contextual aspects of identity. Participants highlighted the central position of food in social events, cultural celebrations, and persistent traditional beliefs about health (such as 'hot-cold balance'). These beliefs extended to the perception of certain traditional foods possessing medicinal properties. Importantly, the consumption of these traditional foods was accepted as necessary for the maintenance of health by the women. We propose that while cultural food practices are integral to identity preservation and identity continuity for Singaporean women from all three racial groups, this is different to other multicultural societies such as Canada where communities preserve their cultural food practices, in part, due to fear of cultural identity loss. In addition, cross-cultural food practices are readily adopted in participants' daily lives for a number of reasons such as the promotion of health, convenience, and variety. At times, this adoption blurred boundaries between different cultural cuisines. Food practices in multicultural societies like Singapore are thus a reflection of everyday multiculturalism, multicultural social policies, and attitudes towards traditional healthful food practices, and these aspects need to be considered in the development of public health policies and interventions.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.007 |
| 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".