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• 1 2013-11-21T10:37:08-08:00 Placing Segregation in the Immigrant Metropolis: The Municipal Scale of Race-Ethnic Isolation and Diversity, 1940-2000 24 image_header 2017-10-09T12:00:04-07:00 Introduction
  The essay “Segregated Diversity” shows how Los Angeles County remained segregated along race and ethnic lines, even as it grew more diverse after the 1965 Immigration Act.  That study was conducted at the metropolitan scale, measuring evenness, exposure, and isolation across one huge, continue space, among millions of persons. This essay shifts attention to the municipal (local) scale, and attempts to provide ways to disentangle two major dynamics that urban researchers have been studying for generations: racial segregation and immigrant assimilation.  For references made to specific places throughout this essay, please refer to the coordinates on the Indexed Map of Los Angeles County Municipal Spaces.
  
  This essay argues that racial segregation in large multiethnic metropolises needs to be “placed” in order to address three unresolved challenges: 1) the entanglement of discriminatory segregation with voluntary immigrant/migrant community formation; 2) the importance of sub-metropolitan municipal territories; 3) the limitations of single-statistic metro-wide segregation indices. As a solution, we develop the Isolation-Diversity Plot (IDP) method, for 109 municipal places within Los Angeles County . The IDP also produces a typology for municipal places: A: integrated diversity; B: minority integration; C: majority isolation; and D: segregated diversity. We find that most African-Americans in the County are integrated in diverse municipal places (“integrated diversity”), while conventional analyses show that African-Americans are segregated at the metropolitan scale. This study seeks to demonstrate that we need to comprehend segregation at both the sub-metropolitan as well as the metropolitan scale and that we need information about the types, as well as the degree, of segregation.
  
  For the background and methodological discussion, see Statistical Methods.
  
  “Los Angeles” is a massive conurbation, numbering, in 2006, 17.8 million residents in its widest definition as the Los Angeles-Riverside-Orange County Consolidated Metropolitan Statistical Area (CMSA). For consistency over a long historical period, we chose the County of Los Angeles as a reasonable boundary for “the metropolis.” The most populous county in the United States, Los Angeles County population numbered nearly 10 million in 2000 and contained 89 incorporated cities. The City of Los Angeles, with 3.8 million residents, is the largest of these. The second largest is Long Beach, with about half a million. The median city size in 2000 (represented by Rosemead) was about 55,000. The average size was 87,000.
  
  The City of Los Angeles is effectively fragmented into at least four distinctive territories: San Fernando Valley, which is separated from the rest of the city by the Santa Monica Mountains, the central city area (from Downtown through “South Central”; the “West Side,” an unofficial area that includes the coastal communities and Westwood and Brentwood (near UCLA) and the Los Angeles Harbor, connected to the rest by the “Shoestring Strip.” This municipal space is simply too attenuated and irregular to treat as comparable with the rest of the municipalities of the County, so we broke it into the fifteen Los Angeles city council districts as they stood in 2000. These council districts, averaging 250,000 in population, are each larger than any other city in the county except Long Beach (460,000, coordinates P-38). The shapes and scale of the Los Angeles City council districts, however, are very similar to those of the municipalities.
  
  Motion cartography visualizes the founding of all 88 Los Angeles County municipalities.
  
  The other challenge that we face when trying to describe and analyze Los Angeles in geostatistical terms, is that about one million Angelenos live in unincorporated County territories. Some of these spaces, like East Los Angeles, closely resemble municipalities. Others are just tiny fragments within and between the incorporated cities. Only some of these are listed as “census designated places” (CDP) by the Bureau of the Census, so they are missed by analyses using that designation. After refining our GIS map of incorporated places, unincorporated places, and LA City Council Districts, we then excluded all spaces with fewer than 10,000 inhabitants (except Malibu, population 5,308, because of its symbolic importance). 
  
  In the Indexed Map of Los Angeles County Municipal Spaces, the fifteen LA City Council Districts are indicated as “LA1, LA 2, etc.” The other 77 incorporated municipalities included in the dataset are listed in order of their date of incorporation. Unincorporated municipal places (N=17), governed and serviced by the County of Los Angeles (counties are the highest level of municipality in California), are indicated as “Co 1, Co 2,” etc. The total of these municipal places is 109. 
  
  The municipal scale is of particular importance, therefore, for mediating between the neighborhood (as represented statistically by census tracts or block groups) and the metropolis (as represented by counties or CMSAs). Perhaps most importantly, the municipality is the most directly responsible authority for the protection and policing of civil rights and freedoms. Historically, with its enormous powers over policing, zoning, regulation and licensing, the municipality has also been the most culpable authority in the creation and reproduction of unjust segregation, as the SCLC’s city-by-city protest strategy of the 1960s illustrates.[1]
  
  Local institutions of government and those of the economy supply the key context for any discussion of segregation, immigrant/migrant integration, and minority empowerment. A wealth of research, including Logan and Molotch’s classic study has shown how the demographics and built environment of urban places are powerfully shaped by the policies of a complex array of municipal, private, and cultural institutions operating at the municipal level.[2] Historical studies by John Mollenkopf (1983), Becky Nicolaides (1999), Tom Sugrue (1996), Robert Self (2005), Matthew Lassiter (2008), have established beyond doubt that sub-metropolitan urban places are the primary source of policies that shape the social composition of cities and suburbs, including patterns in “segregation” or “integration.”[3] Urban economists have also shown, however, that municipal places have strong regional interdependencies.[4]
  
  We turn now to an analysis of race-ethnic diversity and isolation at the municipal scale.
  
  Diversity Dimension
  The degree of municipal diversity varies tremendously across the metropolis. In 2000, for example, forty-two (42) municipal spaces had diversity index scores of 1.0 or higher. Topping the list for that year with a diversity index score of 1.33 was City of Gardena (2000 pop. 55,109; Fig. 1a: M-33), with the following distribution: 12% White, 32% Hispanic, 28% Asian, and 27% Black. The least diverse of the 109 municipal places in our metropolitan sample, with a Diversity Index score of 0.16, was the unincorporated area known as “East LA,” the historic heart of the Mexican-American community. East LA (2000 pop. 125,803, Fig. 1b: P-25) was 2% White, 0.2% Black, 1% Asian, and 97% Hispanic. Indeed, the thirteen least diverse municipal places in 2000 had overwhelming Hispanic majorities. Also at the bottom of the diversity list, however, were several beach cities with overwhelming White majorities, such as Manhattan Beach (2000 pop. 33,887 ; Fig 1a: K-34), with a population distribution that was 86% White, 1% Black, 7% Asian, and 5% Hispanic. At the median of the list for the diversity index was the City of Inglewood (2000 pop. 112,345; Fig 1a: L-28), which, with a diversity index of 0.92, was 4% White, 47% Black, 2% Asian, and 46% Hispanic. Also near the median were cities that illustrate the variation in these patterns. Far in the eastern suburbs, in the San Gabriel Valley, the City of Pomona (2000 pop. 133,547; Fig 1b: X-23), with a diversity index of .94, had a population that was 15% White, 9% Black, 6% Asian, and 69% Hispanic.
  
  These examples indicate the challenge of determining the best boundary between more and less diverse municipal places. Because the unstandardized diversity (H) index is an open-ended value, the boundary between less and more diverse must be set relative to the variance among municipal places within the metropolis as a whole. To achieve the most meaningful boundary, we used the Jenks-Caspall Natural Breaks algorithm (Jenks and Caspall 1971), which is widely recognized as one of the most reliable methods for this purpose.
  
  The Isolation Dimension
  While the degree of diversity (H) is measured for each municipal space and ranked relative to the variation in diversity index scores across the entire metropolis, the isolation index (xP*x) is measured for each group separately for each of those 109 municipal spaces. Measuring the probability that members of a given group will have other members of their own group as neighbors within block groups (which are smaller than census tracts), a high score indicates high levels of isolation from other groups, and a low score indicates high exposure to other groups (low isolation). The isolation index, plotted on the y axis of our IDP scatter plot charts, is far more intuitive than the diversity index, because it is expressed as a percentage and ranges from 0% to 100%. Groups with greater than 50% isolation are “mostly” isolated (exposed mostly to members of their own group); those with less than 50% isolation are “mostly” exposed to other groups. Thus, the degree to which groups fall above and below the 50% mark provides an intuitively-attractive scale of segregation within each metropolitan place. While the 50% boundary is intuitive enough, investigators are free to choose more or less stringent standards of isolation. For this study of Los Angeles, we adopted a level of 50% as our boundary, which is less forgiving than the threshold of 60% used by Massey and Denton (1993). Our 50% boundary has the effect of classifying more groups as “isolated” than in Massey and Denton’s 1993 analysis. In recognition of this difference in judgment, we demarcate a gray zone on the IDP charts to represent the range between our chosen threshold and that of Massey and Denton.
  
  It is vitally important to bear in mind that the isolation index as we have implemented it (using block groups as the unit of analysis) varies independently (except at the asymptotes) of the diversity index. In other words, groups living in a highly diverse municipal place are not automatically highly exposed to other groups. To illustrate, let us return to the most diverse municipal place in all of Los Angeles County, the City of Gardena. There, in 2000, Whites (12% of the population) were very exposed to other groups, having only a 15% probability of living in the same block group as other Whites. Blacks (23% of the population), however, had a 49% chance of living in the same block group as other Blacks. Asians (32% of the population, and therefore the most numerous group in Gardena), had a 39% chance of living with other Asians, and Hispanics, at 32% of the population, had a 29% chance of having other Hispanics as neighbors in their block groups. The City of Carson (2000 pop. 90,957; Fig 2b: N-36) provides an excellent counter-example. The third most diverse city in Los Angeles County, Carson actually advertises itself as the “most diverse” city in the United States, with a remarkable overall balance of 13% White, 24% Black, 26% Asian, and 36% Hispanic. Blacks in Carson, however, were mostly isolated in 2000, having a 57% chance of having only other Blacks as block group neighbors. The other groups were mostly exposed to other groups, however, partially justifying Carson’s slogan. In other words, even the most diverse cities can also be segregated for some groups.
  
  Identifying the Joint Condition of Diversity and Isolation
  To capture these vital interactions between city-level diversity and group isolation or exposure in those cities, each municipal place is plotted in a matrix that we call the "Isolation- Diversity Plot," or IDP.    We plot the IDP separately for each race-ethnic group. The quadrant location of each the plotted data point represents the condition of segregation for a given race-ethnic group, in a given municipal place.  In the IDP diagram, we can see how the IDP helps to sort-out the different ways that people may be segregated in a complex metropolis undergoing dynamic demographic changes. Starting in the lower right quadrant, plot points represent highly diverse municipal places in which race-ethnic groups have low levels of isolation, which we call “integrated diversity.” This condition—being exposed to other groups in a diverse city--is the experience of what in ordinary speech is meant by “integration.” Because this condition of genuine residential integration is widely esteemed, we begin our lettering system here, designating that quadrant “A.”
  
  Moving clockwise around the IDP to the next quadrant, we observe plotted points for municipal places in which a given race-ethnic group also has low levels of isolation. But this condition takes place within municipal places that are less diverse. A household of group x in this kind of municipal place is part of a minority that is integrated within a majority of another group. We call this condition “minority integration,” and designate it with a letter grade of “B,” indicating a second-best condition for investigators who wish to assess the degree or severity of segregation.
  
  The upper left quadrant displays non-diverse municipal places in which members of a given group experience high levels of isolation. These are homogeneous places, segregated in the sense that few members of other groups live within the boundaries of these places. We call this condition “majority isolation” designated with the letter grade “C.” Whether or not such a condition presents a cause for alarm depends on the overall diversity of the metropolis as a whole. Isolation in a homogenous setting is, in itself, not necessarily an indication of segregation. But it is certainly not a condition of integration, and thus the letter grade of C makes sense within the overall schema that we propose here. At the very least, it indicates cause for further investigation of the situation in that particular municipal place.
  
  The IDP is capable of identifying an unambiguous form of segregation, which is found in the upper-right quadrant. These are highly diverse places in which members of a given group are, despite that diversity, highly isolated. We call this type of segregation “segregated diversity” and designate it with the lowest grade of “D.” The difference between “A” type integration and “D” type segregation is clearly set out by the IDP, enabling investigators to say far more than the common practice of considering segregation only along one linear dimension. The “B” and “C” types indicate the ambiguous cases that need to be considered more carefully with respect to the historical dynamics of those municipal places, before drawing conclusions.
  
  In sum, the IDP offers investigators a new tool for assessing the trends in segregation that allows us to sort residential concentrations into categories or types of segregation. While continuing to monitor the degree or “level” of segregation, it also allows us to “see” the geographic context of segregation at the municipal place and metropolitan levels. Its utility is primarily descriptive of segregation, leaving the task of inferring underlying processes that explain the observed patterns to the investigators’ choice of models. But, as we have already argued, we cannot disentangle the underlying contexts of discrimination, immigration, and geographic place until we can see the patterns more clearly, using a method that can recognize the difference between these processes.
  
  RESULTS
  Segregation at the Metropolitan Level by Conventional Measures
  In this section we present two different kinds of segregation analysis. First, we present the metropolitan-level indices of Dissimilarity (D) and Exposure (xP*y) using the Los Angeles County Union Census Tract Data Series, 1940-2000 (Ethington et al. 2006). Next, we present results from the Isolation-Diversity Plot (IDP) based on the municipal spaces dataset. This two-step analysis serves to validate our findings by comparison with other studies, and also allows comparison between the standard single, metro-wide statistic approach, and our IDP approach.
  
  The Index of Dissimilarity (D) is still widely used, despite its known drawbacks. We report it here because of its familiarity and prevalence in many studies. It tells us what proportion of a group would have to move (change locations) into other census tracts in order to even-out the distribution across all census tracts. The metro-wide indices for Los Angeles County are reported in Figure 3.
  
  According to the Index of Dissimilarity, almost 90% of blacks would have had to move their residential locations in 1960 and 1970. That figure dropped to 57% in 2000. Whites reached their peak level of dissimilarity (.71) in 1950, falling until 1970, when the D index leveled-out at a remarkably stable rate of .57 for the rest of the century, almost identical to that for African Americans in 2000. The D index value for Hispanics also peaked in 1950, at .85, then fell sharply until 1980 to .36, and then rose again modestly to .43 by 2000. The D index for Asians, also peaking in 1950, fell until 1970, and like that for Whites, leveled-out at a remarkably stable figure (.5) for the years 1980-2000.
  
  The Exposure Index (xP*y) tells us the probability that members of one group (x) will have members of each of the other race groups (y) as neighbors in their census tracts. Figure 4 displays the results of these calculations for each of the major race-ethnic group.
  
  Because the Exposure Index is asymmetric, it is sensitive to the relative sizes of the groups included in the equations, allowing us to see the differential rates that each group is “exposed” to the other as census tract neighbors. Thus, while Hispanics had less than a 10% probability of having blacks as neighbors in 2000, blacks in that year had a 40% probability of having Hispanics as neighbors. And while whites have been increasingly likely to have Hispanics as neighbors (from nearly zero in 1940 to about 23% in 2000), Hispanics have been steadily less likely to have whites as neighbors (declining from 81% in 1940 to about 18% in 2000).
  
  The overall patterns in the county-wide Exposure index do not speak well for integration, even since the Civil Rights victories of the 1960s. First, Hispanics experienced little change in likelihood of having Asian or black neighbors (always 10% or less since 1940), and a steep decrease in having white neighbors, declining from greater than 80% in 1940 to 18% in 2000. Second, while the probability of whites having non-white neighbors increased steadily as they lost majority status by 2000, whites still had a low likelihood in 2000 of having Hispanic (25%) and Asian (15%) neighbors, and an extremely low probability of having black neighbors (4%) at this metropolitan scale of analysis. Third, the most discouraging result of the metro-wide analysis is the likelihood of blacks and whites to share neighborhoods. Blacks in 2000 had almost the same likelihood of having white neighbors as they had in 1970 (16% compared with 18%). The emblematic goal of the Civil Rights movement to integrate whites and blacks has, by these measures, not advanced at all in Los Angeles County. Blacks were certainly more likely to have Latino neighbors (40% in 2000), but only slightly more likely to have Asian neighbors over the long period (rising from 3% to 9%). Lastly, Asians have been less and less likely to have white neighbors since 1940, a probability declining from 78% to 23% in 2000. Asians’ probability of having a black neighbor has been in decline since 1960, from 18% to only 4% in 2000. Their probability of having Hispanic neighbors increased steadily to just over 30% by 1990 but declined again by 2000. This possibly reflects the larger concentrations of majority-Asian places, with fewer people living at the “edges” between groups and more living internally to the clustered settlements.
  
  The overall results of this metro-wide analysis of Los Angeles County reflect the overall state of scholarship on other North American metropolitan areas. There are certainly some signs that the grip of segregation has lessened since the Second World War, but several key spatial relations, such as those between blacks and whites, have not changed at all since the Civil Rights victories of the 1960s. These figures consider the entire county as one continuous space of probable encounters. We turn now to results of our IDP analysis at the scale of municipal places, to see how they compare with the standard metro-wide approach.
  
  Degree and Types of Segregation in Municipal Places
  The results of the IDP analysis for the year 2000 are presented in the four panels of Figure 5. To review, each race-ethnic group’s isolation index is plotted against the diversity index for each entire municipal place. The data points on the plot represent the location of each municipal place along the isolation and diversity dimensions, for the race-ethnic group analyzed in that plot.
  
  The most obvious observable pattern is that each race-ethnic group presents a distinct “signature” of sorts. The two largest groups, Hispanics and whites, both exhibit a nearly identical plot pattern, with a tight concentration of cities in the Majority Isolation, type “C” quadrant, a sizeable scattering in the Integrated Diversity “A” quadrant, and another distinct curve pattern bunched in the Minority Integration (minimally isolated, non-diverse) “B” quadrant. Asians exhibit a similar signature, except that only two cities in 2000 appeared in the Majority Isolation “C” quadrant, and far fewer places earned a “D” for Asian integration than for Hispanics, and whites.
  
  The African American condition of segregation is distinctly different than that of all three other groups, however. A pronounced concentration of municipal places near the bottom of the chart, across both “A” and “B” quadrants, indicates that in most municipal places, blacks are highly exposed to other groups. In a scattering of municipal places, blacks experienced “D” type segregation, and only barely achieved the majority-type segregation in two municipal places. These initial results support the conclusion that segregation patterns for blacks exhibit distinct differences from those for the other three major race-ethnic groups (Charles 2000).
  
  Figure 5 can only give a visual impression of the distribution of segregation conditions experienced by each of the four race-ethnic groupings. Table 1 summarizes the patterns of these scatterplots by displaying the number of ethnic group members living in each of the four “types” of segregation, A, B, C, or D. Table 1 contrasts sharply with the standard practice of reporting single segregation indices calculated at the metropolitan scale. Instead, we are summarizing the sub-metropolitan, place-based condition of each of the four groups—a much more reasonable picture, we believe, than one that assumes an undifferentiated space of residential opportunity across the giant spaces of the entire metropolis. Table 1, then, shows the proportion of each group that lives in each of the four conditions of segregation identified by the IDP.
  
  In Table 1 we can see that the Los Angeles County Hispanic population experienced mainly three types of segregation in 2000: 29% experienced Type A, integrated diversity, while a nearly equal proportion (30%) experienced Type C isolation in places in which they formed the overwhelming majority. The largest proportion (41%) experienced Type D segregation in diverse places, down from 49% in 1990. The proportion living integrated as minorities declined from 2% to zero by 2000.
  
  By contrast, the majority of whites (57%) experienced Type D, segregated diversity in 2000, (decreasing from 64% in 1990). But the better news for whites is that the proportion living in Type A, diverse and integrated municipal places, increased by fourteen percentage points, from 19% to 33%, while the proportion of whites living in Type C, majority isolation, dropped by more than half, from 16% to only 7% in 2000. By contrast, those living as minorities in mostly homogeneous places increased slightly from 4% to 7%.
  
  Considering most recent studies of black segregation, the most remarkable finding in Table 1 is that 63% of African Americans lived integrated in diverse municipal places (Type A) in 2000, and that this proportion had increased from 47% in 1990. Further, those blacks living segregated in otherwise diverse municipal places dropped dramatically from 47% to 20% in the same period. These findings most clearly show the difference made by our IDP method of studying both types and degree of segregation in municipal places. Massey and Denton (1993) found blacks to be “hypersegregated” in Los Angeles in 1990, but the IDP methods shows that nearly half of African-American Angelenos lived in diverse municipal places in which they were mostly integrated (less than 50% isolated). Indeed, Massey and Denton set their trigger for “highly segregated” on the xP*x isolation index at 60%--much higher than we did—so our study method is more conservative than theirs. We would have identified many more African Americans living in diversely integrated places if we had included scores up to 59%. These findings are also consistent with earlier nationwide studies of 1990-2000 trends, indicating decreasing segregation rates for blacks, especially in cities where other minorities were present (Frey and Myers 2005, Glaeser and Vigdor 2001, Iceland 2009).
  
  Asians are becoming slightly more segregated as their numbers continue to increase, but the baseline for evaluation of this increase was the lowest overall level of isolation among any of the race-ethnic groups. In 1990, fully 91% of Asian Angelenos lived in Type A conditions (integrated in diverse places). That proportion had dropped to 75% by 2000, but Asians still faired well in comparison to Hispanics (29%), whites (33%), and blacks (63%). These trends should not be underestimated, however, as the proportion of Asians in Los Angeles County experiencing Type D segregation rose to 17% in 2000, up from 4% in 1990, in a population that increased by nearly 300,000 persons during that decade. The dispersal of Asians, however, is evident in the zero percent experiencing Type C majority isolation in both 1990 and 2000. Not even the Chinese-majority Monterey Park showed that kind of isolation.
  
  Municipal Places and a New Typology for Urban Segregation: The HWAB Rating
  
  The IDP reveals how each race-ethnic group fairs in each municipality and Table 1 summarizes how each race-ethnic group is fairing overall across the Los Angeles metropolis. In addition, the IDP also allows for a closer look at each municipal place, to understand how each race-ethnic group is fairing relative to other groups in any particular municipality. Each group’s experience in either A, B, C, or D-type integration/segregation conditions, can now be combined for each municipal place, in the form of a “type combination” of the letter-grades given to each group for each place. So, for example, in 2000, in fourteen municipal places, including Pasadena, Long Beach, Gardena, and West Covina, each of the four race-ethnic groups experienced A-Type integrated diversity. These are all highly diverse places in which each group is less than 50% isolated. We call these places “AAAA”-type combinations. The use of these segregation type letters in combination always follows the same population rank-order: Hispanics, whites, Asians, and blacks (H-W-A-B), as shown in Table 2. It can readily be seen that there are only two broad classes of combinations, because all municipal places have been divided into either diverse or non-diverse places. Therefore, only combinations of As and Ds (diverse places) or Cs and Bs (non-diverse places) are possible.
  
  Table 3 summarizes the population totals within municipal places classed in each of the resulting combinations, for the years 1990 and 2000. At the highest level of generalization, there was only negligible change in the population living in diverse places from 1990 to 2000. At the same time, there was an increase in the population living in non-diverse (Type CB) places (from 1.4 to 1.8 million). The population living in “AAAA”-type places in 2000 was more than 1.3 million, an increase of almost 700,000 since 1990. Secondly, the population living in “AAAD”-type places, diverse places in which blacks were segregated, dropped by a quarter million. In addition, the population living in “ADAA”-type places, in which whites are segregated in diverse places, dropped by more than a million persons. It is important to remember that these figures represent the total number of persons in each municipal place of each type combination. While Table 1 reports the number and share of each group experiencing each type of segregation across all places, the type combinations represent the total combined impact of each group’s type of segregation. Knowing whether there are integrated groups living in a municipal place where other groups are segregated is an important dimension of the context of segregation. Indeed, the more alarming finding in Table 3 is that 6.3 million Angelenos (63 %) lived in diverse places where at least one group was still segregated. However, this has decreased from 7.1 million persons in 1990 (71 %).
  
  Within the other broad class of non-diverse places, 1.5 million people lived in “CBBB”-type places, in which Hispanics predominate as an isolated super-majority. At the same time, there was also a sharp decrease in “BCBB”-type places, in which whites predominated as an isolated super-majority. The one place that had a black super-majority in 1990, the unincorporated South Los Angeles community of Athens, had become type “AAAD” by 2000: a diverse place in which blacks were isolated. Blacks filled-up most of the residential space of the unincorporated Athens district in 1990, but by 2000, the growth of the Hispanic population in that district, along with the decrease of the black population, gave it an overall increase in diversity. That meant that blacks, once isolated through numerical predominance, were now isolated in a different way, within a diverse place. A change in the overall demography of a place can play a major role in the segregation/integration experience of any group.
  
  Mapping the Type Combinations for each municipal place reveals some important patterns. In Figure 6, we see that the AAAA-type places are nearly all (with two exceptions) located in the San Gabriel Valley: the most recently developed “suburban” region of Los Angeles, far to the east of Downtown and South Los Angeles. The giant Hispanic population of Los Angeles County is primarily settled on this east side, as are large concentrations of Asians, so the implication may be that the dynamics of immigration have helped to create more diversely integrated municipal places.
  
  We note also that the single-D Type Combinations are found throughout the County. In these municipal places, three of the four major race-ethnic groups are living in Type A “Integrated Diversity,” but yet, and perhaps more importantly, one group is segregated in these diverse places. Even more troubling are municipal places in which two groups are segregated within a diverse context. These cities are shaded red in this map (Fig. 6) and their location is significant. One is the former 10th LA City Council District (council districts were re-drawn in 2002), which included the most homogenous white neighborhood in the County: Pacific Palisades. The other “DD” municipal places were concentrated in the high crime and low income areas of South Los Angeles, where both the 1965 and 1992 riots occurred. Finally, the Type B-C combinations, as we have already discussed, are ambiguous cases, where either the dynamics of immigrant community formation or discriminatory segregation may be taking place. We color these areas yellow, and they lie at the heart of the Latino immigrant community, where new arrivals have concentrated for decades.
  
  The types of segregation that people have experienced throughout Los Angeles County, we have shown, are highly place-specific. Place really matters in the study of segregation of metropolitan areas, because trends can go in either direction for a given group depending on where in the metropolis members of that group live. Table 4 summarizes this phenomenon, showing the number of places that underwent each kind of change in type combinations, along with the groups that experienced the change. We can see, for instance, that in ten (10) diverse places, whites became integrated where they had been segregated in 1990. Blacks had that experience in four (4) places, and so on. But we also see a great many other experiences: Hispanics becoming segregated, integrated, and isolated as a super-majority. Through all this change in both directions, the only common patterns are consistent with growing Hispanic and Asian populations and shrinking black and white populations, which have been summarized above. For example, no new places appeared in which Hispanics experienced B-type integration as a minority in a non-diverse place. Instead, eight (8) more C-type conditions emerged for Hispanics: eight municipal places in which they became the isolated supermajority and changed the place from diversity to non-diversity.
  
  DISCUSSION AND CONCLUSION
  Our study of Los Angeles County, introducing the Isolation-Diversity Plot (IDP) shows the advantage of an approach to residential segregation that identifies types as well as degree of segregation for the metro- and the sub-metropolitan scales. The most striking differences we found are those between the standard, metropolitan-wide indices and those for municipal places. At one level, the trends we report are consistent with recent research: 1) segregation is still a major feature of America’s multiethnic metropolitan areas; 2) the increase in immigrant populations changes the context for African American segregation; and 3) while whites are becoming more exposed to other groups, white/nonwhite segregation remains stubbornly persistent, even while rates of diversity keep increasing.
  
  The Isolation-Diversity Plot, however, also tells a different story than what we have seen to date. The most remarkable finding is that, considered at the scale of municipal places, most African Americans (63%) live integrated in communities that are diverse. For whites and Hispanics, the IDP does not tell a dramatically different story than the metro-wide findings. Rather, it gives us much more detail about the conditions of segregation for those groups.
  
  The often dramatic differences between the metropolitan-wide findings, and those from the municipal-scale IDP results raise a red flag far above Los Angeles for segregation studies. Something is clearly happening at the municipal scale that scrambles the metro-wide picture of segregation in many different ways, as our IDP has demonstrated. Urban sociology and urban economics offer a host of plausible explanations for the extreme variation of type and degree of segregation across the multiethnic metropolis: discrimination, population flows, policy regimes, cultural variation between groups in contact, socioeconomic structures, etc. While some of these processes are collective, impersonal forces, deliberate public policy choices are also possible candidates. Extensive work on place-making by Logan and Molotch (1987) and many others show clearly that municipal-level state powers have great influence (through policies of exclusion, social spending, and regulation) on the social patterns within their jurisdictions.
  
  In this paper, we have not attempted to link any causes to the type and degree findings of the IDP. Instead, ours is an initial study aimed at developing a new approach to the study of multi-ethnic segregation in the age of global metropolises. As an initial study, it is effective for aiming a spotlight on places that deserve closer attention given our A, B, C and D classifications and “type combinations” (Tables 2-4). We intentionally aligned the letter grades with a A = “best” and D = “worst” valuation. Given all that has been said about segregation, “integrated diversity” is most likely the ideal of just living conditions since Martin Luther King Jr.’s “Dream” speech. By the same standard of the Civil Rights movement, we think it appropriate to give a “D” rating to municipal places that are highly diverse but also segregated for at least one group. Our IDP ratings cannot show that discrimination is being practiced, but it can show where to look.
  
  Our findings suggest that a metropolitan-wide index of segregation is too blunt of an instrument for many questions that are of pressing interest in the 21st century. The powerful dynamics that work to shape a great global metropolis criss-cross political economic boundaries that structure most local action in a metropolis. Our comparison of the IDP and the metro-wide analyses suggest that the macro-metropolitan segregation-shaping dynamics are in tension with those that operate at the local level. The underlying dynamics of segregation seem, then, to be enmeshed with the metro-wide/municipal-scale tension, but they are also entangled within the tension between immigration and discrimination dynamics. Among 109 municipal places, the combination of these types of segregation varies a great deal. Metropolitan-wide indices of segregation are like telescopes trained on distant planets: the results can be important but the granularity is very limited, and granularity is exactly what we need in order to understand large multiethnic metros at the outset of the 21st century.
  
  Once we have tools to see the metropolis at both the metro and the municipal level, as the IDP does, then we can move to the next level of attention, which is to identify sources of segregation where discriminatory segregation may persist, or where “spatial assimilation” of immigrants is at work in the initial formation of enclaves. And we certainly can learn from further study of the many municipal places that seem to be diversely integrated (Type A). Further study is needed after identifying municipalities in which there may be cause for concern. For example, the continued high levels of Type D segregation for whites in 2000 is cause for concern, given their status as the group that benefited for centuries while “affirmative action was white” (Katznelson 2006). The areas of highest white concentration in Los Angeles are also the areas of greatest wealth: the seaside communities and those in the upper elevations, such as the Hollywood Hills. Our method has identified the areas warranting further research of specific place-segregations.
  
  The majority of African Americans living integrated in diverse municipal places is a hopeful finding, but it is far from definitive. While studies show continued hypersegregation for blacks at the metropolitan level, there have been signs of improvement (Wilkes and Iceland 2004; Iceland and Scopolitti 2008). As we discussed earlier, Reardon et al.’s geographically-scaled analysis finds that “Los Angeles is the 16th most-segregated metropolitan area at a 500m scale, but the 6th-most segregated at a 4000m scale…” (2006: 17). Place matters, so the study of segregation must also draw on local knowledge. The most noticeable feature of black spatial settlement is the geographic concentration in the Crenshaw area. The conditions of segregation varies a great deal across this large, oval-shaped pattern of African American settlement, which is approximately 30 square miles in extent and overlaps 20 municipal spaces. To further complicate this picture, this great concentration of African American settlement is the result of a secondary, voluntary migration that began in the 1950s, as the walls of discriminatory segregation began to tumble in LA. A former, even more clearly bound African American territory had thrived along South Central Avenue, about 7 miles to the east. Many African Americans take great pride in the high-value neighborhoods of Leimert Park and Baldwin Hills, sometimes called the “Black Beverly Hills,” with some of the best panoramic views in the metropolis. Other portions of this great oval, on the “flats,” are lower income, higher-crime neighborhoods. But many portions of this oval intersect with middle class neighborhoods that are highly integrated, like those of Gardena and Torrance, which are also home to large Japanese-American and white populations.
  
  Given our findings, it is quite possible that the “hypersegregated” oval of African American settlement is more meaningfully studied at the scale where people actually live: municipal places. Black Baldwin Hills and black Watts are worlds apart socioeconomically. Our study did not attempt to include wealth, income, or property values, but these factors will need to be included in future studies that hope to untangle the dynamics of integration and segregation of African Americans in Los Angeles—and presumably any other North American multiethnic metropolis. This brief discussion of the remarkable municipal-scale IDP findings for African Americans indicates that the way forward in racial residential segregation studies will be toward greater attention to the facts on the ground in any given case, and that history will need to be part of the analysis.
  
  Limitations
  We hope that others will find the IDP approach to metropolitan race-ethnic segregation useful, but we hope also that other researchers will help develop more ways to approach the “type” of segregation at the municipal scale as well as the metropolitan. There are many paths that we did not take, and it is important to be clear about the limitations of this study. First, our analysis is limited to Los Angeles. Los Angeles is the test case for our new IDP approach to both degree and type of segregation at municipal scales. We have not done so here but the IDP method can be applied to New York, Chicago, Miami, Houston, or other metros. Second, we did not combine the Diversity or H index with other indices, those measuring evenness, clustering, concentration, and centralization. We chose the Isolation (xP*x) index for reasons stated in the Methods section, but we welcome attempts to extend our approach to include the use of other indices, where appropriate.
  
  Third, we chose to subdivide the metropolis by incorporated, unincorporated, and (for the City of Los Angeles) city council boundaries—but those are not the only possible sub-metropolitan geographies. We have presented a spatial analysis aggregating the data by irregular-shaped places rather than using measures of distance, proximity, adjacency, and other tools that are essentially metric in nature used by others (Reardon et al 2008, Fischer et al 2004). Scholars of segregation are increasingly using Geographic Information Systems (GIS) tools to study urban segregation, which is an important development. In this paper, we used GIS tools for data preparation and visualization, but not for computational spatial analysis. Again, this was a deliberate choice to take a place-based, rather than space-based approach, but the latter is certainly an area of great promise.
  
  Fourth, we did not include socioeconomic (SES) variables in this study. The additional layer of SES considerations would have distracted from the main goal of this paper, which is to introduce the IDP. We recognize that SES clearly intersects with race-ethnic segregation in important ways and it should be an object of further enquiry. Lastly, we cannot address the underlying causes of segregation with the IDP alone. Factors such as preference, race-ethnic discrimination, sheer population pressures, and the real estate market, are all well beyond the scope of this study. However, as stated previously, the IDP does appear to be very effective at identifying specific areas of a metropolis that display distinctive types of segregation warranting further investigation.
• 1 2013-11-21T09:40:19-08:00 Quantitative and Statistical Methods 19 Methodological Essay plain 2015-10-07T04:23:05-07:00 In order to comprehend the vast complexity of demographic change in Los Angeles, I have used quantitative and statistical methods for description, cartographic visualization, and analysis.  This essay explicates the quantitative and statistical methods.
  
  A great deal of this work was conducted collaboratively with colleagues in several disciplines.  The data collection was conducted in collaboration with John P. Wilson and others in the GIS Lab and Spatial Sciences Institute of USC.  The statistical analyses of demographic change and segregation were conducted in collaboration with Dowell Myers and others in the USC Price School of Policy, Population Dynamics Laboratory.
  
  Data: Collection, Scope, and Assembly
   “Los Angeles” is a massive conurbation, numbering in 2006, 17.8 million residents in its widest definition as the Los Angeles-Riverside-Orange County Consolidated Metropolitan Statistical Area (CMSA).  For consistency over a long historical period, we chose the County of Los Angeles as a reasonable boundary for “the metropolis.”  The most populous county in the United States, Los Angeles County population numbered nearly 10 million in 2000 and contained 89 incorporated cities.  The City of Los Angeles, with 3.8 million residents, is the largest of these.  The second largest is Long Beach, with about half a million.  The median city size in 2000 (represented by Rosemead) was about 55,000.  The average size was 87,000.
  
  We assembled two datasets.  First, in order to generate the standard set of metro-wide segregation indices, we developed the Los Angeles County Union Census Tract Data Series, 1940-2000 (Ethington et al. 2006), which consists of tract-level data from the 1940-2000 U.S. Censuses, fitted to 2000 tract geography by area apportionment.     Second, in order to conduct municipal-level analyses, we assembled another data set composed of block group data (Summary Tape File 1 in 1990 and Summary File 1 in 2000) from 1990 and 2000 for “municipal places.” We use the conventional four major race-ethnic groups, defined as: white, African American or black, Latino or Hispanic, and Asian and Pacific Islander.  For our purposes here, we use the “Hispanic categorical dominance” method, which means that Hispanics can be of any race and the other 3 groups are non-Hispanic.  The categorization of race for Census 2000 is particularly tricky because respondents could choose more than one race. The method used here is the “fractional apportionment of multiracials” which means that persons reporting more than one race are equally apportioned to each of the races they report (reporting 3 races, a respondent would be split .33 to each race-ethnic group).
  
  We faced several challenges constructing the 1990-2000 municipal places dataset. First, the City of Los Angeles, with a 2000 population of nearly 4 million, is far and away the largest municipality in the county.  It has an extremely irregular shape, resulting from decades of annexations and consolidations (absorption of preexisting municipalities, like Hollywood in 1910 and Watts in 1924).  The Indexed Map of Los Angeles County Municipal Spaces shows the City of Los Angeles in bold black outline. A coordinate grid (x=A-Z y=1-40) is provided in this map to facilitate the location of municipal places discussed in this paper.
  
  The City of Los Angeles is effectively fragmented into at least four distinctive territories: San Fernando Valley, which is separated from the rest of the city by the Santa Monica Mountains, the central city area (from Downtown through “South Central”; the “West Side,” an unofficial area that includes the coastal communities and Westwood and Brentwood (near UCLA) and the Los Angeles Harbor, connected to the rest by the “Shoestring Strip.”  This municipal space is simply too attenuated and irregular to treat as comparable with the rest of the municipalities of the County, so we broke it into the fifteen Los Angeles city council districts as they stood in 2000.  These council districts, averaging 250,000 in population, are each larger than any other city in the county except Long Beach (460,000, coordinates P-38).  The shapes and scale of the Los Angeles City council districts, however, are very similar to those of the municipalities.
  
  The other challenge we faced is that about one million Angelenos live in unincorporated County territories.  Some of these spaces, like East Los Angeles, closely resemble municipalities. Others are just tiny fragments within and between the incorporated cities.  Only some of these are listed as “census designated places” (CDP) by the Bureau of the Census, so they are missed by analyses using that designation.  After refining our GIS map of incorporated places, unincorporated places, and LA City Council Districts, we then excluded all spaces with fewer than 10,000 inhabitants (except Malibu, population 5,308, because of its symbolic importance). 
  
  In the map, the fifteen LA City Council Districts are indicated as “LA1, LA 2, etc.”  The other 77 incorporated municipalities included in the dataset are listed in order of their date of incorporation.  Unincorporated municipal places (N=17), governed and serviced by the County of Los Angeles (counties are the highest level of municipality in California), are indicated as “Co 1, Co 2,” etc.   The total of these municipal places is 109. 
  
  Segregation Indices
  
  The long history of urban segregation research has undergone two major periods of re-adjustment: At the beginning of the Civil Rights movement, Duncan and Duncan (1955) settled a period of methodological confusion and established the Index of Dissimilarity as the standard tool.   That standardization lasted until the mid-1970s, when the Index of Dissimilarity was shown by Cortese, Falk and Cohen (1976) to be seriously flawed, a finding confirmed by others.  Among its many weaknesses, the Index of Dissimilarity cannot distinguish between single and multiple residential clusters for a group, and is insensitive to population size (the D for a population of 1,000,000 can be the same as that for a population of 100).
  
  Consequently, by the early 1980s, more robust measures proliferated, but the agreement on a preferred index disappeared.  Massey and Denton (1988), finding “the field of segregation studies…in a state of theoretical and methodological disarray, with different researchers advocating different definitions and measures of segregation” (282), deftly sorted such measures into five “dimensions” of segregation: evenness, exposure, concentration, clustering, and centralization.  For each of these, they tested and advocated the most effective statistical index.  They went on to postulate the condition of “hypersegregation,” for groups that score high on all five dimensions, and summarized their influential results in the landmark book American Apartheid (1993).   Research since the early 1990s on residential segregation has proven highly productive, compatible, and comparable, with a broad acceptance of the five dimensions and the condition of “hypersegregation” as conceptual referents.
  
  Because our approach in this study is to incorporate spatial scale by adopting the irregular institutional boundaries of municipal places, we do not use the three geometrically spatial dimensions of segregation: clustering, concentration, and centralization.  Indices of those dimensions operate on the basis of measured distance, and that approach  overlaps in confusing ways with our territorial, place-based framework.  This is not to suggest that geometrically spatial methods are less effective than our place-based territorial approach to spatial scale.  Indeed, we applaud the important uses of those approaches to spatial scale by other researchers.  We simply propose another approach to the crucial importance of scale, within which the geometric approaches are not appropriate.  We therefore focus on the other two major dimensions of segregation: evenness and exposure.
  
  The recent re-examinations of segregation indices by Reardon and coauthors (2002, 2004) evaluated the utility of these measures for multi-group segregation and their effectiveness in spatial analyses.   On the basis of a series of rigorous tests and comparisons, they conclude that the two most robust measures are the P* family of exposure/isolation indices, and the H, Entropy or Diversity index.  Therefore, we utilize the Diversity Index (H) and the Exposure or Isolation Index (P*) as the basis for our analysis in describing the conditions of diversity for a given spatial setting and simultaneously, the isolation of a given group within that setting.

  Diversity Index

  Population  diversity in a large multiethnic metropolis like Los Angeles could be classified by a wide range of categorical variables, such as language, religion, national origin, and race.  For practical reasons and for comparability with most contemporary studies of residential segregation, residents are herein divided into four race-ethnic groups: Hispanic (also called Latino herein); White (always non-Hispanic herein); Asian and Pacific Islander (also called Asian and always non-Hispanic herein), and African American (also called black and always non-Hispanic herein).
  
  For the measurement of evenness, the most common tool for decades was the Index of Dissimilarity (D).   The
  weaknesses of that index have long been understood (Cortese, Falk and Cohen 1976).  Just as important as its statistical limitations, the Index of Dissimilarity is also limited because it only operates on two paired groups at a time.  The multiracial metropolis requires measures that operate robustly on more than two groups.
  
  Instead, we have selected the H index of diversity to represent evenness of group representation within each municipal place.  While there are many variants of diversity measures, the most basic and widely-used of these is the H or Shannon index.  The methodological lineage of this index grew from Claude Shannon’s theories of information (Shannon 1948; Shannon and Weaver  1949), to studies of biodiversity, linguistic diversity, and studies of segregation (Lieberson 1964). Accordingly, there are many important variations and levels of sophistication available in the family of diversity indices (Thiel and Finizza 1971; Lieberson 1969).  But most are built atop Shannon’s original index, which satisfies the following conditions, among others:  “1)  diversity should be maximized when all groups are present in equal proportions.  2) in two populations in which all groups are equally represented, the population with the greatest number of groups will be more diverse” (White 1986: 200).  To avoid confusion and recognize its most common purpose, we shall refer to the Entropy (H) index as defined by White (1986) as the Diversity Index (H):
  
  Diversity Index
  There is considerable confusion about the proper name for this index.  White (1986) refers to this formula as the Entropy Index, but most, including Massey and Denton (1988: 285), reserve the name “Entropy” for a modification of that formula proposed by Thiel (1972; Theil and Finizza 1971), which norms the index, gives it an upper bound of 1.0,  and makes it comparable across different geographic cases.  We use the simpler, unweighted version, as in the displayed formula, and use the name Diversity rather than “Entropy."
  
  
  
  Where:
  N=total population size
  Nk =number of persons in Kth group
  Pk = Nk/N

  Isolation Index

  The next main consideration is to determine, within a known context of high or low diversity, how “segregated” those groups are within each municipal place.   For this purpose, we use the P* family of indices, one the biggest winners in the marathon contest between segregation indices.  The P* family of indices is known both as the “exposure” (xP*y) or “isolation” (xP*x) index.  The P* family of indices measures the probability that members of one group will have members of any other group (or the member’s own group) as neighbors.  It is sensitive to relative population sizes, and is asymmetric (Lieberson 1981).  If groups are of unequal population size (as they nearly always are), then the probability that members of group x will have group y neighbors is not the mere inverse of the probability that members of group y will have group x neighbors.  As Lieberson and Carter (1982) observe, the asymmetrical and size-sensitive qualities of the P* family of indices help us to explain “why racial and ethnic groups have different perceptions about the magnitude of and trends in segregation” (1982: 296). Sensitivity to population size and direction of exposure is also of great utility for studying the changing dynamics of multiethnic metropolises.  The Exposure and Isolation Index (P*) are given by Massey and Denton (1988: 288) as:
  
  
  
  Where:
  xi = number of X members in the areal subunit i
  yi =number of Y members in the areal subunit i
  ti  = Total population of number of the areal subunit i
  X =Number of X members county-wide

  The Isolation-Diversity Plot (IDP)

  We also developed  a new approach for studying metropolitan residential segregation, which accomplishes the goals we have so far identified: of capturing the spatial scale, the levels of diversity, the degree of segregation, and also categorical “types” of segregation.  Additionally, this approach also allows the identification of municipal places that exhibit different types and degrees (from good to bad) of segregation.  We developed the Isolation-Diversity Plot (IDP) method to measure both the degree of segregation for groups and to begin sorting the type of their segregation.   The IDP rests on three basic premises: 1) That the geographic scale of “municipal place” is a crucial scale of interest, yet needing to be contextualized within its metropolis and region;  2) That the diversity of municipal places and metros is fundamental to understanding the “context” of segregation; and 3) That by pairing the diversity (H) index with the isolation (xP*x) index, the resulting analysis of municipal places can simultaneously sort the condition of a given group into clearer categories (the type of segregation experienced) and indicate the degree of segregation.  It also displays the metropolitan context in a single graphic format.
  
  The Isolation-Diversity Plot charts the Diversity Index (H) for each municipal place against the isolation index (xP*x) for each group within that place, with diversity plotted along the x axis and isolation along the y axis.  The schematic form of the resulting matrix is illustrated in Figure 1.   The IDP displays the contextualized segregation condition of each of the race-ethnic component groups separately, stratified by the municipal places of the overall metro.  Thus, if a metropolis is being analyzed by four race-ethnic groups, African-American, Asian, Hispanic, and White, stratified by 109 municipal places (as in our analyses of Los Angeles), then an IDP analysis of the entire metro by municipal places would generate four IDP charts: one chart for each race-ethnic group, and each chart composed of 109 plotted points.
  
  Figure 1 displays four logical combinations of isolation and diversity, each representing a distinct way that a given race-ethnic group can be segregated.  People live in places that are either more diverse or less diverse, and their group is either more or less isolated within those municipal places.