{
  "alt": "Square scatter plot of the county white-Black math gap against the county income gap, with a diagonal for equal gaps. Dots form an elongated cloud along the diagonal, and ten markers for tenths of counties by income gap run along the diagonal, with the marker for the lowest tenth above it.",
  "caption": "Dots follow the diagonal, which marks equal gaps, and the markers for tenths of counties by income gap run along it, above it in the lowest tenth. Dots are counties and markers are weighted mean race gaps with 95% intervals from a bootstrap over states. A line through the counties has slope {fact:slope_classrace}, and the income gap accounts for {fact:class_var} of the variance of the race gap.",
  "data": [],
  "id": "class_gap_vs_race_gap",
  "notes": [
    "SEDA does not cross race with economic disadvantage, so the two gaps are measured on overlapping but different groups of students, and their estimation errors are correlated. The comparison describes counties and does not isolate a racial gap among students in the same economic circumstances.",
    "Counties are weighted by all-student tests counted. The standard deviation of the race gap around the line is {fact:resid_sd} standard deviations."
  ],
  "source": "Stanford Education Data Archive 6.0, 2009-2019 (county gaps, math); weighted by tests counted, modeled estimates",
  "spec": {
    "identity": true,
    "identityLabel": "Equal gaps",
    "label": "label",
    "overlays": [
      {
        "hi": "hi",
        "kind": "line",
        "label": "Tenths of counties by income gap, with 95% intervals",
        "lo": "lo",
        "rows": [
          {
            "hi": 0.488,
            "lo": 0.332,
            "n_units": 209,
            "x": 0.315,
            "y": 0.409
          },
          {
            "hi": 0.459,
            "lo": 0.401,
            "n_units": 209,
            "x": 0.4,
            "y": 0.428
          },
          {
            "hi": 0.483,
            "lo": 0.436,
            "n_units": 209,
            "x": 0.436,
            "y": 0.463
          },
          {
            "hi": 0.493,
            "lo": 0.417,
            "n_units": 209,
            "x": 0.467,
            "y": 0.45
          },
          {
            "hi": 0.533,
            "lo": 0.473,
            "n_units": 210,
            "x": 0.497,
            "y": 0.503
          },
          {
            "hi": 0.629,
            "lo": 0.556,
            "n_units": 209,
            "x": 0.529,
            "y": 0.594
          },
          {
            "hi": 0.711,
            "lo": 0.568,
            "n_units": 209,
            "x": 0.569,
            "y": 0.655
          },
          {
            "hi": 0.738,
            "lo": 0.652,
            "n_units": 209,
            "x": 0.62,
            "y": 0.694
          },
          {
            "hi": 0.762,
            "lo": 0.704,
            "n_units": 209,
            "x": 0.694,
            "y": 0.737
          },
          {
            "hi": 0.988,
            "lo": 0.914,
            "n_units": 210,
            "x": 0.896,
            "y": 0.951
          }
        ],
        "x": "x",
        "y": "y"
      },
      {
        "kind": "line",
        "label": "Weighted line",
        "rows": [
          {
            "x": -0.027,
            "y": 0.033
          },
          {
            "x": 0.006,
            "y": 0.065
          },
          {
            "x": 0.038,
            "y": 0.098
          },
          {
            "x": 0.071,
            "y": 0.13
          },
          {
            "x": 0.104,
            "y": 0.162
          },
          {
            "x": 0.136,
            "y": 0.195
          },
          {
            "x": 0.169,
            "y": 0.227
          },
          {
            "x": 0.201,
            "y": 0.259
          },
          {
            "x": 0.234,
            "y": 0.291
          },
          {
            "x": 0.267,
            "y": 0.324
          },
          {
            "x": 0.299,
            "y": 0.356
          },
          {
            "x": 0.332,
            "y": 0.388
          },
          {
            "x": 0.364,
            "y": 0.421
          },
          {
            "x": 0.397,
            "y": 0.453
          },
          {
            "x": 0.43,
            "y": 0.485
          },
          {
            "x": 0.462,
            "y": 0.518
          },
          {
            "x": 0.495,
            "y": 0.55
          },
          {
            "x": 0.527,
            "y": 0.582
          },
          {
            "x": 0.56,
            "y": 0.615
          },
          {
            "x": 0.592,
            "y": 0.647
          },
          {
            "x": 0.625,
            "y": 0.679
          },
          {
            "x": 0.658,
            "y": 0.711
          },
          {
            "x": 0.69,
            "y": 0.744
          },
          {
            "x": 0.723,
            "y": 0.776
          },
          {
            "x": 0.755,
            "y": 0.808
          },
          {
            "x": 0.788,
            "y": 0.841
          },
          {
            "x": 0.821,
            "y": 0.873
          },
          {
            "x": 0.853,
            "y": 0.905
          },
          {
            "x": 0.886,
            "y": 0.938
          },
          {
            "x": 0.918,
            "y": 0.97
          },
          {
            "x": 0.951,
            "y": 1.002
          },
          {
            "x": 0.983,
            "y": 1.034
          },
          {
            "x": 1.016,
            "y": 1.067
          },
          {
            "x": 1.049,
            "y": 1.099
          },
          {
            "x": 1.081,
            "y": 1.131
          },
          {
            "x": 1.114,
            "y": 1.164
          },
          {
            "x": 1.146,
            "y": 1.196
          },
          {
            "x": 1.179,
            "y": 1.228
          },
          {
            "x": 1.212,
            "y": 1.261
          },
          {
            "x": 1.244,
            "y": 1.293
          },
          {
            "x": 1.277,
            "y": 1.325
          }
        ],
        "x": "x",
        "y": "y"
      }
    ],
    "payload": "class_gap_vs_race_gap.json",
    "size": "tests",
    "sizeFormat": {
      "thousands": true
    },
    "sizeLabel": "Tests counted (math and reading)",
    "x": "neg",
    "xDomain": [
      -0.2,
      1.6
    ],
    "xFormat": {
      "digits": 1
    },
    "xLabel": "Income gap in math (standard deviations; not disadvantaged minus disadvantaged)",
    "y": "wbg",
    "yDomain": [
      -0.2,
      1.6
    ],
    "yFormat": {
      "digits": 1
    },
    "yLabel": "White minus Black math gap (standard deviations)"
  },
  "subtitle": "White minus Black math gap against the gap between students who are not and are economically disadvantaged, standard deviations of the national cohort, one dot per county; dot area is the tests counted",
  "title": "Counties with a wider income gap have a wider white–Black gap, a correlation of {fact:r_classrace} across {fact:n_classrace} counties, and the two gaps are of similar size",
  "type": "scatter",
  "width": "body"
}