From Food Desert to Food Mirage: Race, Social Class, and Food Shopping in a Gentrifying Neighborhood
Bibliographic record
Abstract
New supermarkets in previous “food deserts” can benefit residents by improving their access to healthful, affordable food. But in gentrifying neighborhoods characterized by the inflow of middle-class, white residents and the outflow of working class, minorities, who benefits from a new supermarket that emphasizes organic food and environmental sustainability? This paper contributes to the food access literature by examining the food shopping behavior of diverse residents by using survey data and probability sampling in the Alberta neighborhood in Portland, Oregon (USA). Regression results show that college-educated (62%) and white residents (60%) are much more likely to shop there weekly, regardless of age, gender, owner-renter status, distance from supermarket, or length of time living in the neighborhood. These findings indicate that supermarkets that promote healthy living and environmental sustainability need to be sensitive to the racial “symbolic boundaries” and socioeconomic barriers that may create “food mirages” by limiting food access to poor and minority residents.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".