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Table 10 presents the cluster scores of four distinct groups. Since I include 313 regions in the analysis, the creativity scores will differ from Florida who only uses 258. This is due to the reverse ranking method where a region is given a score by taking total number of regions and subtracting its rank on a particular index. (I.e. 313 - region’s rank of 10 on diversity index = diversity contribution to creativity index of 303) As shown, the highest regions on the creativity index also score the highest in population percentages for every group. The highest creative regions have nearly twice the population percent for bohemians and foreign-born immigrants of all other regions combined, indicating a clear connection between the four groups at the regional level. This confirms hypothesis 1 that these diverse populations and the Creative Class tend to locate in certain regions in similar percentages, especially in the very high creativity group.

Within the metropolitan region, where do these populations live across the four groups? Figure 12 shows the population percent that lives in the central city versus suburbs. The Creative Class overwhelmingly lives in the suburbs. Only about 20% of Creative Class workers reside in the central city. This supports the assertions made by Glaeser and Brooks about the suburban location decisions of knowledge workers. For gays, foreign-born and bohemians, a distinct u-curve exists, most pronounced in foreign-born populations. In the highest creative regions, half of same-sex partnered households and foreign-born immigrants live in the central city of the region, or more than 20 percent more than creative workers. This suggests the creatives and these diverse groups do not live together, especially in the very low and very high groupings. It also mirrors the relationships shown in figure 11.

To what extent do these groups concentrate in residential space? In Florida’s work, creative cities will host diverse ethnic scenes, which signals tolerance. An indirect measure of these scenes are concentrated residential spaces, like those found in Castro in San Francisco or Boystown in Chicago. Figure 13 displays group concentration in central cities versus suburbs for each group across the creativity index. Same-sex partnered households show the largest percentage concentrations both in the central city and suburbs. As the city’s creativity ranking increases, the concentration of same-sex partnered households increases, but tapers off significantly in both the central city and suburbs at the high end of the creativity scores. Foreign-born immigrants display the same pattern. Given that the highest creativity hubs also have the highest numbers of each of these groups, this pattern lends support to the hypothesis that crowding out happens at the tract level in the very creative cities. As a city’s creativity ranking increases, the bohemian population increasingly concentrates, suggesting evidence of bohemian areas, especially within the highest creative regions. Unlike the other populations, the Creative Class does not concentrate in any significant percentage regardless of suburb or central city. Only in the highest creative regions, do creatives concentrate at a discernable level (2%).

To what extent do these populations live together? Florida’s work suggests that extremely creative cities will host strong ethnic communities where all these populations work, live and play . To test this, I use the lowest possible measure where tracts would be considered diverse if they have location quotients of bohemians, same-sex partnered households and foreign-born immigrants greater than one. Table 11 shows the percent of each population that lives in census tracts where all three populations exceeded a location quotient of one. The results show that Creative Class workers and foreign born immigrants were the least likely to live in these diverse tracts while bohemians and same-sex partnered households were more likely.

All four groups show similar patterns, increasingly living with other groups as the region’s creativity index increases, but decreasing in the highest creativity grouping. When the criterion for diversity is increased to a location quotient of three, only same sex households show any concentrations in these tracts (1% or less). These results suggest that across all regions, Creative Class workers do not live in any significant numbers in tracts with diversity. These results suggest that hypothesis 3 is incorrect. Creatives do not, in general, live in ‘diverse’ neighborhoods. It also shows evidence of increasing concentration into particular areas that might be considered tolerant, but tapering off as the individual group population’s increase. This is an interesting result. Since Table 2 measures the percentage that each subgroup lives with the others, the tapering off in the high creativity regions suggests that same-sex partnered households, foreign-born immigrants and bohemians are likely to form their own enclaves as their populations increase.

This makes sense when you consider that many smaller cities contain diverse areas, like a midtown or uptown, with all three populations in visual abundance. But as the critical mass of the population gets larger, these groups can form their own enclaves, even though some will remain in the diverse neighborhoods.

Finally, what is the degree of segregation between Creative Class workers and diversity? I measure diversity by adding foreign-born, bohemian and same-sex populations at the census tract level. Figure 13 displays the exposure index of creatives to diversity across 331 metropolitan areas. As the previous table demonstrated, less than a fifth of creatives live with diversity. This plays out in the very low exposure indices. As creativity scores increase, so does exposure. Creatives are increasingly exposed to diversity as the creativity score and subpopulations increase.

Figure 14 displays the degree of isolation for diversity. It also increases as creativity scores increase, but with more variability than the exposure index. As Table 10 above noted, cities that scored high, but not highest, had higher residential concentration. As figure 14 demonstrates, some of the highest isolation values are in cities with the high creativity scores. However, isolation is still the largest, on average, in the highest creativity grouping of metropolitan regions.

The increasing isolation of diversity supports hypothesis 2 that as the subpopulations increase, so to will the concentration of their enclaves. Enclaves with higher numbers, indicated by higher isolation, provides the critical mass necessary to support a node and garner political support that influences tolerance at the regional level.

Finally, Figure 15 shows the standardized spatial GINI index. Highly creative cities tend to be more uneven and have a higher degree of that unevenness attributed to spatiality. Increasingly negative values of the standardized spatial GINI suggest that a large number of tracts are segregated, causing their rank to adjust as spatiality is taken into account. A larger negative spatial GINI (-.5 or higher) indicates that the region has many segregated pockets of diversity. While the GINI coefficient is on average, similar across the groups, the spatial GINI decreases from around -.2 to almost a -.6, a concentration and segregation trend increase of 40%. This reflects increasing concentration and segregation of both diversity and the Creative Class as the creativity score increases.