The 9-Point Chasm
Same county. Same governance. 9+ point gaps between best and worst neighborhoods. Internal inequality may matter more than regional differences.
Key Finding
A 9-point gap represents approximately 9 standard deviations of difference—statistically speaking, these are entirely different worlds despite sharing the same county government, school district, and local services.
Counties with Widest Internal Gaps
Counties with at least 10 census tracts, ranked by the difference between highest and lowest resilience scores.
| Rank | County | Tracts | Best Tract | Worst Tract | Gap |
|---|---|---|---|---|---|
| 1 | Cuyahoga, OH | 362 | +3.262 | -6.440 | 9.7 pts |
| 2 | Orleans, LA | 154 | +4.108 | -4.925 | 9.0 pts |
| 3 | Cook, IL | 1234 | +3.318 | -5.211 | 8.5 pts |
| 4 | Mobile, AL | 91 | +1.625 | -6.365 | 8.0 pts |
| 5 | Franklin, OH | 223 | +4.767 | -3.212 | 8.0 pts |
| 6 | Maricopa, AZ | 803 | +3.275 | -4.641 | 7.9 pts |
| 7 | Philadelphia, PA | 321 | +4.386 | -3.502 | 7.9 pts |
| 8 | Hinds, MS | 52 | +2.807 | -5.078 | 7.9 pts |
| 9 | Hamilton, OH | 196 | +3.438 | -4.389 | 7.8 pts |
| 10 | Shelby, TN | 179 | +2.533 | -4.978 | 7.5 pts |
| 11 | Richmond city, VA | 52 | +3.206 | -4.257 | 7.5 pts |
| 12 | Montgomery, OH | 141 | +2.802 | -4.609 | 7.4 pts |
| 13 | Atlantic, NJ | 63 | +1.387 | -5.979 | 7.4 pts |
| 14 | Allegheny, PA | 340 | +3.753 | -3.592 | 7.3 pts |
| 15 | El Paso, TX | 123 | +2.462 | -4.766 | 7.2 pts |
| 16 | Hamilton, TN | 70 | +1.811 | -5.366 | 7.2 pts |
| 17 | Bibb, GA | 34 | +2.193 | -4.980 | 7.2 pts |
| 18 | Milwaukee, WI | 273 | +2.839 | -4.324 | 7.2 pts |
| 19 | Tuscaloosa, AL | 30 | +3.774 | -3.374 | 7.2 pts |
| 20 | Cumberland, NC | 43 | +3.602 | -3.528 | 7.1 pts |
Cuyahoga, OH 9.7 point gap
Highest Resilience
- 39035141100 +3.262
- 39035104200 +3.048
- 39035104300 +2.367
- 39035160700 +2.359
- 39035160200 +2.344
Lowest Resilience
- 39035112100 -6.440
- 39035152701 -6.053
- 39035117201 -5.470
- 39035112500 -4.859
- 39035112800 -4.259
Orleans, LA 9.0 point gap
Highest Resilience
- 22071011900 +4.108
- 22071005603 +2.797
- 22071007700 +2.709
- 22071006400 +2.709
- 22071012600 +2.638
Lowest Resilience
- 22071014000 -4.925
- 22071001751 -2.975
- 22071014300 -2.725
- 22071002800 -2.587
- 22071000904 -2.358
Cook, IL 8.5 point gap
Highest Resilience
- 17031832900 +3.318
- 17031061100 +3.202
- 17031070300 +2.996
- 17031062200 +2.981
- 17031240500 +2.980
Lowest Resilience
- 17031340600 -5.211
- 17031841700 -4.568
- 17031681000 -3.802
- 17031835500 -3.670
- 17031461000 -3.669
Mobile, AL 8.0 point gap
Highest Resilience
- 01097003204 +2.453
- 01097003602 +1.625
- 01097006402 +1.594
- 01097003607 +1.514
- 01097006701 +1.458
Lowest Resilience
- 01097000402 -6.365
- 01097004900 -3.219
- 01097004800 -3.164
- 01097005000 -3.046
- 01097000500 -2.982
Franklin, OH 8.0 point gap
Highest Resilience
- 39049006352 +4.767
- 39049001200 +4.453
- 39049007830 +4.276
- 39049001000 +4.243
- 39049007820 +3.830
Lowest Resilience
- 39049000730 -3.212
- 39049002900 -3.019
- 39049005100 -2.858
- 39049005410 -2.611
- 39049000720 -2.389
Why This Matters
Local Matters Most
Neighborhood-level factors create more variation than state or even city-level policies. Investment, infrastructure, and social cohesion at the hyperlocal level appear to drive outcomes.
Concentrated Advantage
High-resilience tracts often cluster together, creating islands of advantage. Resources, access, and opportunities compound within small geographic areas.
Policy Implications
County-wide or city-wide interventions may miss the mark. Precision targeting at the neighborhood level may be more effective than broad geographic policies.