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The machines also perform better in areas with: low English proficiency, limited household internet access, low-income residents, uninsured residents, cost-burdened renters, residents with less than a high-school diploma, and unemployed residents, according to this tool.

I wonder why you chose just that one specific stat to highlight.

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You are mixing "over represented" and "under represented" information which could be tricky; they were only looking at over represented.

The data does seem to suggest that in an area annotated as "white" you are more likely to have location and it is less likely to have broken machines, whereas in an are annotated as "black" the opposite is true.

Those are the only two categories showing up as extremal on both tests.

Without digging into the methodology it's hard to get much more out of it. It's also not clear hwy "Low-income" doesn't show up as blue/over-represented on that chart.

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