食物获取的人群层面感知测量揭示地理邻近性之外的障碍

中文摘要 AI 辅助

食物获取是多维度的，但人群层面的测量仍主要依赖地理因素，因为感知层面的获取维度难以大规模测量。在此，我们利用北卡罗来纳州罗利市49家杂货店的25,125条谷歌地图评论，测量食物获取的五个维度：可用性、可达性、可负担性、适应性和可接受性。我们使用无监督主题建模识别评论主题，并通过零样本分类将其分配到获取维度，与人工编码的一致性达85.4%。由此产生的店铺层面测量捕捉了食物获取的不同方面，并揭示了仅凭地理邻近性无法捕捉的障碍。同一连锁店邻近店铺之间的比较进一步表明，相同的店铺政策在不同地点可能被感知为截然不同，这与食物获取反映居民与其食物环境之间匹配度的观点一致。感知食物获取还遵循系统性的社会经济和人口统计模式，这些模式与地理获取所观察到的模式大体相似，但并不完全相同。这些结果表明，在线杂货评论可以为食物获取的地理测量提供可扩展的补充。

英文摘要

Food access is multidimensional, but population-level measurement still relies heavily on geography because perceived dimensions of access are difficult to measure at scale. Here, we use 25,125 Google Maps reviews from 49 grocery stores in Raleigh, North Carolina, to measure five dimensions of food access: availability, accessibility, affordability, accommodation, and acceptability. We identify review topics with unsupervised topic modeling and assign them to access dimensions using zero-shot classification, with 85.4% agreement against manual coding. The resulting store-level measures capture distinct aspects of food access and reveal barriers that geographic proximity alone does not capture. Comparisons between nearby stores in the same chain further show that identical store policies can be perceived very differently across locations, consistent with food access reflecting the fit between residents and their food environment. Perceived food access also follows systematic socioeconomic and demographic patterns that broadly parallel, but do not replicate, those observed for geographic access. These results show that online grocery reviews can provide a scalable complement to geographic measures of food access.

发表机构

• North Carolina State University（北卡罗来纳州立大学）

机构由 AI 辅助整理，请以论文原文为准。