High-resolution data are used to evaluate the distribution of job accessibility among workers at the national, state, regional, and urban scales. Annually updated accessibility datasets produced by the National Accessibility Evaluation are paired with Census data to tie accessibility, jobs, and worker information at the block level. Minnesota is selected as a case study for analyzing accessibility and drawing findings from the spatial datasets. The average accessibility by worker age, monthly earnings, educational attainment, race, and sex are calculated using data for the weekday morning commute by automobile and transit. The greatest variation in average accessibility among demographic groups is found for worker race. Based on home location, non-White workers systematically experience far higher accessibility to jobs by both automobile and transit than White workers as a percent difference from the population average. The finding holds at the national, state, and regional geographies. Additional findings are presented for each demographic group. The analyses presented here can be applied to other states and regions to identify where accessibility is distributed most and least equitably.

中文翻译：

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可访问性：分布在不同人群中

高分辨率数据用于评估国家、州、地区和城市范围内工人的工作可及性分布。国家可访问性评估生成的每年更新的可访问性数据集与人口普查数据配对，以在块级别将可访问性、工作和工人信息联系起来。明尼苏达州被选为案例研究，用于分析可访问性并从空间数据集中得出结论。工人年龄、月收入、教育程度、种族和性别的平均可达性是使用工作日早上乘汽车和公交通勤的数据计算的。人口群体之间平均可达性的最大差异是工人种族。根据家庭位置，非白人工人通过汽车和公交系统获得工作的机会比白人工人要高得多，与人口平均水平的百分比差异。这一发现适用于国家、州和地区。为每个人口群体提供了额外的调查结果。这里介绍的分析可以应用于其他州和地区，以确定可访问性分布最公平和最不公平的地方。