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THE GEOGRAPHY OF RACE AND INCOME IN NEW YORK CITY By Professor
Juliana Maantay |
New York City
1990
(Shown with major manufacturing zones)
The Term "Minority"
Race and ethnicity are self-reported on the census forms. This means that people classify themselves as one race or another, and tell the Census Bureau that's what they are. They "choose" their race, in effect, based on the limited number and types of options given by the Census Bureau. Race was categorized very differently in the 1990 Census than it was in the 1960 Census, and this is one of the difficulties in making valid comparisons across time periods. In 1960, for instance, there were no "Hispanic" categories as such in the Census, but there were Puerto Rican categories (born in US, or born in PR), and a category for people with Spanish surnames. Because the racial and ethnic categories did not remain consistent between 1960-1990, some comparisons may not be accurate.
1960
The Census Bureau is still grappling with racial and ethnic classifications. For the first time, the 2000 Census allowed people to select more than one race to describe themselves. This has been controversial for a number of reasons. Some civil rights activists say it will dilute the majority status that "minorities" have achieved in many places, and hinder attempts to demonstrate inequities and receive fair representation. Others say that it is about time that the Census Bureau got realistic about race in the U.S., where many people can not "choose" just one racial or ethnic category, as no single category adequately reflects who they are. Since race is not biologically determined, but is defined by each society, this category will continue to evolve in the official arena as well as in the popular culture.
1970
Why is it important to know which people live where?
Far from being just an academic exercise, getting an accurate count of people and knowledge about their demographic and socio-economic characteristics is important in many ways: it helps determine voting districts (which has great impact on the potential for proper representation of minority populations in legislative bodies); it helps policy makers allocate funds and resources based on need; and it can point out and address deficiencies regarding unequal distributions of benefits and burdens within a region or city.Mapping by the Standard Deviation:
The standard deviation is a measure of how much the data varies from the arithmetic mean, or average. Using the standard
1980
deviation to classify data allows us to compare things using a constant baseline (the "Mean," or average). The maps might have shown the data classified instead by absolute numbers of minority people or by the percentages of minorities in relation to total population. However, since we are comparing data over several decades, we would really be comparing "apples to oranges," since the absolute numbers and the overall percentage of the minority population has increased significantly in our study time period (1960-1990). Because we are comparing data over a forty-year time period, we must establish some common reference point: the average for each decade. Although the average for each decade changes, we are comparing the data within each decade to the average, so we can compare across decades as to how much variation away from the average occurs at that time.
1990
The data are assigned colors that range from light to dark tones using two different color hues. This represents the different directions away from the average. With the % Minority maps, the deeper the color orange, the more the data for that tract diverges away from the mean, e.g., is a higher standard deviation above the average. The deeper the pink color, the more the tract diverges away from the average in the opposite direction, e.g., is a higher standard deviation below the average. The lighter tones in either orange or pink indicate values closer to the average, above or below, respectively, according to the color. With the Mean Family Income maps, the darker orange colors signify data values with higher standard deviations below the average (the locations of poorer families). The darker pink colors denote higher standard deviations above the average (the locations of more affluent families).
Interpreting the Maps:
The maps can be compared with each other in a variety of ways. The income distribution maps can be looked at by contrasting each year with the next year, or the income map can be compared with the same year's % Minority Population map.New York City
1990
(Shown with major manufacturing zones)
Looking at the Mean Family Income maps for 1970 - 1990 (the 1960 data for income was not available), we can trace the pattern of a widening discrepancy between the very wealthy and the very poor. The map of 1980 Mean Family Income reflects a relatively even distribution of income throughout the city, with most tracts averaging close to the city-wide mean (being within one standard deviation above or below the average). The 1990 map, on the other hand, shows growing areas of extreme wealth, where average household income is far in excess of the city-wide mean, as well as growing areas of impoverishment, where average household income is far below the city-wide mean.
There are a greater number of tracts in 1990 that are more than 3 standard deviations above the mean, and more tracts that are between 1 and 2 standard deviations below the mean in 1990 than in either of the other two decades. Assuming that a person's economic status is a function of many factors other than his or her own individual merits and efforts, we must ask what other forces were at work to redistribute income in this way? National programs and policies of the 1960s and 1970s, such as President Johnson's "Great Society" reforms, may have been responsible for some of the equalizing of income levels that can be observed on the 1980 map. These programs were virtually eliminated by President Reagan in the 1980s, which may be reflected in the extremes of wealth and poverty observed on the 1990 Mean Household Income map. What other factors may account for these changes?
1970
By comparing the Mean Family Income Map with the % Minority Map for any given year, we can see some degree of correlation between these two variables. Areas of extreme poverty are more likely to be areas of higher than average % Minority, and conversely, areas of extreme wealth are more likely to be areas of lower than average % Minority.
Future Studies:
These maps are part of a larger study on the impacts that zoning changes to industrial areas have had on poor communities and peoples of color. Zoning is a legal and public policy determination of what the appropriate land use is for each area in the city. Land use, in turn, governs the type of activities that are allowable by law in each area. The activities permitted in each area may result in environmental burdens that may have animpact on the people living in or nearby these land uses. Areas
1980
zoned for industrial activities, for instance, generally carry a higher environmental burden than do areas zoned for purely residential uses. Preliminary findings suggest that industrial areas that have been enlarged by re-zoning are generally located in or near poor neighborhoods and communities of color, while industrial areas that have been reduced in size are generally located in or near more affluent neighborhoods with a lower percentage of minorities. Archival zoning maps, zoning change applications, and other data from the New York City Department of City Planning (1961-1998) and the Municipal Archives (1916-1999) have been consulted for this study.
1990
