A historical analysis of the Mediterranean Diet’s rise to prominence through the lens of Critical Race Theory
Bibliographic record
Abstract
Ample evidence indicates that adherence to the Mediterranean diet (MedDiet) decreases the risk of cardiovascular disease, stroke, heart failure, cancer mortality, type 2 diabetes, overweight, and obesity. The MedDiet is widely accepted as a gold standard diet, yet its adoption and promotion as the healthiest cultural diet reflects systemic racism and inherently biased research, rather than evidence-based science. This analysis establishes that while the Mediterranean region is multi-cultural and multi-ethnic, the MedDiet is a White diet. It also asserts that a lack of causal research and other methodologic issues in research about the MedDiet has resulted in a hyperfocus on the MedDiet over other cultural diets. Third, this essay compares the MedDiet to the traditional Chinese and African diets to assert that many cultural diets are healthy and may be as healthy as the MedDiet. Ultimately, health professionals promoting the MedDiet as a gold standard marginalize people from non-White cultures by maintaining White culture as normative. In order to better serve and include people of color, dietary recommendations need to become as diverse as the US population. Doing so will also improve cultural competence among professionals, lead to a more equitable profession
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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.039 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.007 |
| 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".