Ethnocentrism to Cultural Relativism: A Food Journey of Hassan Haji's Family in Richard C. Morais' the Hundred-Foot Journey
Bibliographic record
Abstract
This paper examines the conflict faced by select characters in Richard C. Morais' The Hundred-Foot Journey between Indian and French food culture through the lens of ethnocentrism and cultural relativism. It probes how Hassan Haji strikes a balance between two food cultures: the French culture and Indian culture meet, interact, compete and experience a collision of cultures related to ethnocentric issues from Madame Gertrude Mallory. Leaving one's cultural territory and migrating to another territory authoritatively represents one's cultural superiority. It takes time to understand the cultural practices of other ethnic groups in terms of their food and cultural contexts, which requires competence in cultural relativism. It examines three aspects of his food culture journey. To begin, it studies how Hassan Haji travels out of his home country and adapts to new food culture. Second, how he experiences blending two food cultures. Third, how well he manages, learns and adjusts to the new food culture and settles in with cultural relativism. The author portrays cross-cultural aspects of food's power through the confrontation between French haute cuisine and an Indian restaurant. Literature has enlightened readers' comprehension of many civilisations all across the world. It takes the readers on a voyage around the world without requiring them to leave their current location. Some literary works, on the other hand, combine two civilisations. These pages reflect how various cultures may reveal various facets of each other, including challenges, dreams, and secret scars shared by those who share space with them. As they learn about new cultures, they strive to maintain a balance between the two. Cross-cultural influences led the Kadam family to abandon their nativity and relocate to a new country after crossing cultural divides.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.035 | 0.017 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".