Understanding Geographic Relationships: Geographic Summary Levels

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By Katy Rossiter

The third installment of our geographic relationships series discusses geographic summary levels and how American FactFinder uses them to provide tabulated data.

To protect individual privacy, the Census Bureau provides summaries of data for geographic areas. For example, you cannot find the median household income for a particular house, but you can find the median household income for the census tract or county for where that house is located. Each summary level, identified by a unique three-digit number, represents a different geographic entity for which the Census Bureau summarizes data.

Summary levels specify the content and hierarchical relationships of the geographic entities so that the data can be tabulated. American FactFinder utilizes these summary levels so you can get to a specific piece of geography. When you are choosing your geography in American FactFinder, you are choosing which summary level you would like to use. For example, when you choose Madison County, IN, in American FactFinder, you are choosing to work with summary level 050 State-County.

Summary Level Geographic Component
040 State
050 State-County
060 State-County-County Subdivision
140 State-County-Census Tract
150 State-County-Census Tract-Block Group

 

The table above describes some of the basic summary levels that are also clearly shown in the geographic hierarchy.  Census data are available for these summary levels and for all entities on the hierarchy. Census data are also available for some more complicated geographic relationships.

The table below shows some examples of relationships that are not clear on the hierarchy. These relationships are not as straightforward, and they require the Census Bureau to create special geographic units. These summary levels provide data for areas that might be difficult for the public to tabulate on their own so the Census Bureau does the work for you and makes these available in American FactFinder.

Summary Level Geographic Component Description
070 State-County-County Subdivision – Place/Remainder provides data for a place, but just the portion the place that falls in a specific county subdivision
158 State-Place-County-Census Tract provides data for a census tract, or part of a census tract, that falls within a particular place
159 State-County-Place provides data for a place, but just the portion that falls in a particular county

 

There are a couple of keys to understanding summary levels. First, the last geography listed in the summary level is the one you will get data for and you need to know all of the proceeding geography in order to get to the correct geographic unit. Using summary level 060 State-County-County Subdivision, for instance, will get you county subdivision data but you will need to pick the correct state and county first. For example, if you want data for Oak Bluffs town, you need to enter the state (Massachusetts) and the county (Dukes) first.

Secondly, the most important component to the list of summary levels, like this one, is not the three-digit identifier but the hierarchical relationships between geographies. While the identifiers are useful and kept constant, the Census Bureau has introduced so many new summary levels over the years, the sequential order of the IDs is not very meaningful. More meaningful are the indentions on the list.  These show how summary levels, and geographic units, fall within one another.  American FactFinder makes the three-digit identifier for each summary level available in their search functions and you can pick your geography by searching for a particular summary level. American FactFinder also shows the hierarchical relationships in their search functions by also using indentions. An example is below.

IMG1

Summary levels do not cover all possible geographic relationships. There are still some geographic units not covered by a summary level, and therefore, data users need to calculate the data themselves. For example, sometimes data users are interested in the population of a county that is unincorporated, in other words, the portion of a county that is not covered by a city, town or village. However, this summary level and dataset do not exist in American FactFinder, so data users would need to calculate the data themselves. They could use summary level 050 (State-County) to obtain the county population. Then, they could use summary level 159 (State-County-Place) to determine the population of each incorporated place that falls within the county and subtract the two.

Summary levels are one way to understand geographic relationships and understanding geographic relationships is important in order to get to the correct census data.

It is the 25 year anniversary of the TIGER (Topologically Integrated Geographic Encoding and Referencing) database. Stay tuned for more on this important milestone in geographic history.

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Understanding Geographic Relationships: American Indian Areas

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Written by: Katy Rossiter

Part two in the Understanding Geographic Relationships series focuses on relationships that exist between different types of American Indian Areas. Part one in this series provided an overview of how Census Bureau geographies relate to one another.

The Hierarchy of American Indian, Alaska Native, and Native Hawaiian Areas displays the relationship between both legal and statistical American Indian Area boundaries. The hierarchy portrays relationships with a line and shows where relationships do not exist by displaying entities on different line tracks. For example, you can see how tribal census tracts and tribal block groups are related.

It is important to note that the only entities on the American Indian Area hierarchy that are also on the standard hierarchy are states and census blocks. These are the only two standard geographic units that have a relationship with American Indian Area geographic units.

Hierarchy of American Indian, Alaska Native, and Native Hawaiian Areas

Federal American Indian Areas and off-reservation trust lands do not need to fall with any other geography like states or counties. In fact, they often cross stae and county lines. In 2010, there were 311 reservations and all are on the same level as the nation on the standard hierarchy.

Map of Reservations

Here is an example of federal American Indian Areas with trust lands.

Federal American Indian Areas can be divided into four other geographic entities, including tribal subdivisions, tribal census tracts, tribal block groups and census blocks.

1. Tribal subdivisions split a reservation and its trust lands into areas such as communities, chapters, districts and administrative areas. It is up to each tribal government whether it delineates subdivisions in order to receive data for these areas, which are smaller than the reservation boundary. Currently, 24 federal American Indian Areas contain tribal subdivisions.

2. All federal American Indian Areas with land contain tribal census tracts. Tribal census tracts must fall within the reservation boundary but do not need to coincide within any other geography and are delineated separately than the standard state-county census tracts. In addition, they may be discontinuous in order to cover off-reservation trust lands. Tribal census tracts are based on population, so smaller reservations may only have one tribal census tract.

3. All federal American Indian Areas with land also contain tribal block groups, although smaller populated reservations may only have one. Tribal block groups must fall within tribal census tracts and are delineated separately than the standard state-county block groups. They may also be discontinuous to include off-reservation trust lands.

4. Census blocks fall within everything. Just like in the standard hierarchy, census blocks are the building blocks for all American Indian Areas.

Moving across the hierarchy, another American Indian Area entity that does not fall within any other geography is the Tribal Designated Statistical Area (TDSA). TSDAs are statistical areas for federally recognized tribes that do not have a federally recognized land base. The only other geographic unit that falls within a TDSA is the census blocks.

Finally, three entities on the hierarchy must stay within state boundaries.

1. Oklahoma Tribal Statistical Areas (OTSAs) fall within the state of Oklahoma. Similar to federal American Indian Areas, OTSAs can be divided into tribal subdivisions, although not all OTSAs are. Subdivisions must stay within each OTSA. Census blocks must also stay within each OTSA.

2. Alaska Native Regional Corporations, Alaska Native Village Statistical Areas, and Hawaiian Home Lands must fall within their respective states (Alaska or Hawaii). Census blocks are the only geography that fall within each area.

3. State American Indian Reservations and State Designated Tribal Statistical Areas must also stay within their respective state boundary and have census blocks that fall within them. Not every state contains these areas. In 2013, six states have state American Indian Reservations and six states have state designated tribal statistical areas.

The hierarchy provides a quick and easy way for data users to see how the different American Indian Areas relate to one another. It is important to understand the hierarchy to get to the correct data. The next Understanding Geographic Relationships post will shed some light on summary levels and their role in accessing different geographic relationships in American FactFinder.

It is the 25 year anniversary of the TIGER (Topologically Integrated Geographic Encoding and Referencing) database. Stay tuned for more on this important milestone in geographic history.

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Understanding Geographic Relationships: Counties, Places, Tracts and More

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By Katy Rossiter

Geography is at the center of taking a census. We do not just count people; we count people where they live. Geography is important because it is the basis for taking a census and for tabulating census data. The Census Bureau also maintains unique geographic areas that other local, state and federal agencies use.

Understanding geographic relationships is key to understanding how to properly use Census Bureau data. This is the first in a series of posts that will shed some light on how these different entities relate to one another. Part one focuses on geographic relationships that exist below the national level, such as ZIP Code tabulation areas and school districts.

The Standard Hierarchy of Census Geographic Entities displays the relationships between legal, administrative and statistical boundaries maintained by the Census Bureau. It depicts relationships with a line and shows where relationships do not exist by displaying entities on different line tracks. In short, it shows how different geographic areas may, or may not, be related.
geo1

Here are some examples to explain how some of the relationships on the hierarchy work.

  • ZIP Code Tabulation Areas (ZCTAs) are based on the U.S. Postal Services ZIP Codes and must fall within the national boundary only. Many data users think that ZCTAs must stay within the state boundary, but in a few cases, ZCTAs can cross into bordering states.
  • School districts must fall within each state. States are responsible for updating their boundaries, and districts may cross county and place boundaries.
  • County subdivisions, as the name suggests, must fall within the county. Many county subdivision names repeat throughout the nation and throughout the same state, so it is important you know which county you are working in. For example, in 2010, Beaver was used as the name of 45 different county subdivisions.
  • Places stay within state boundaries. Many place names repeat throughout the country (e.g. Kansas City, Kan.  vs. Kansas City, Mo. ), but each is unique, with different mayors, schools and services. In a few cases, place names can even repeat in the same state (e.g. Aaronsburg CDP in Pennsylvania occurs twice).
  • Urban areas fall within the nation because they do not have to conform to place, county or even state boundaries.
  • Core Based Statistical Areas (CBSAs) (metropolitan/micropolitan statistical areas) fall within the nation and often cross state lines.
  • Census tracts must stay within a county and therefore a state. They do not necessarily coincide within any other geography. For example, although some census tracts follow place boundaries, there is no rule that says they must stay within a place.
  • Block groups must stay within each census tract, so they must also stay within a county and state.
  • Blocks fall within everything! They are the building blocks for all other geographies and therefore nest within all other geographies. Their four-digit codes correspond to the block group that they fall within. So, if you want data for a specific block, you must also know the block group, census tract, county and state it exists in.

The hierarchy provides a quick and easy way for data users to see how the different geographic entities at the Census Bureau relate to one another. It is important to understand the hierarchy to get to the correct data. The next Understanding Geographic Relationships post will discuss the hierarchy of geographic entities related to American Indian Areas.

It is the 25 year anniversary of the TIGER (Topologically Integrated Geographic Encoding and Referencing) database. Stay tuned for more on this important milestone in geographic history.

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Where do STEM Graduates Work?

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Written By: Liana Christin Landivar and Anthony Martinez

In 2012, 14.8 million employed college graduates reported having a bachelor’s degree in science, technology, engineering and mathematics (STEM).  About one-quarter of these graduates work in a STEM occupation, so where do the others work?

Many STEM graduates go into non-STEM management, health care or education. However, not all workers in a STEM occupation have a STEM degree or a STEM degree related to their specific occupation. For example, many employed in computer occupations have a degree in computers, math or statistics, but this occupation also draws from a variety of majors, such as engineering, business and social sciences.

You can see the relationship between college major and occupation in a new interactive graphic that highlights the diverse employment patterns of college graduates. You can also explore how these patterns differ by sex, race and Hispanic origin.

The length of each circle segment shows the proportion of people who graduated in each college major and are employed in each occupation group. The thickness of the lines between majors and occupations indicates the share of people in that major-occupation combination. Lines highlighted in color show the proportion of college graduates who work in STEM. You can hover over majors individually to see which occupations employ them.

For example, if you hover over engineering or computers, math and statistics majors, you can see that about half go into a STEM occupation. If you hover over science graduates, you can see that most are not employed in STEM.

STEM

Engineering majors and Biological, environmental, and agricultural science majors

This visualization lets you look at college major and employment patterns by sex, race and Hispanic origin. Comparing the graphics for men and women who are STEM majors, for example, we see that men are more likely to major in engineering and are more likely to be employed in STEM occupations. Women are more likely to major in psychology, a major that sends a larger share of its graduates into non-STEM occupations.

When comparing the graphics by race, Asians have the largest percentage of STEM workers, partially explained by their representation in specific college majors. Of all college majors, engineering has the largest percentage of Asian graduates (22 percent), while education has the smallest percentage of Asian graduates (3 percent).

Searching for the numbers behind the data visualization? Take a look at the new tables on field of degree and occupation by sex, race and Hispanic origin.

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Who Faces More Family Instability: Married or Nonmarried First-Time Mothers?

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Written by: Lindsay M. Monte

In the Fertility of Women in the United States: 2012 report, we use June 2012 Current Population Survey data to examine family instability. A common definition of family instability is considered to be changes in the composition of a family that are not caused by either birth or death — such as divorce.  Studying instability is important because other research has linked family instability to negative outcomes for both adults and children.

New questions were added to the June 2012 Current Population Survey Fertility Supplement asking about women’s relationship status — married or cohabiting — at the time of their first birth. The data from these questions allow us to look at trends in nonmarital births over time, as well as explore the characteristics of women who have had nonmarital births.

To examine the implications of first-birth circumstances for later familial instability, we used logistic regression models to predict, based on her relationship status at first birth, the likelihood that a woman was married at the time of the survey, as well as the likelihood that she lived in a blended family. By blended family, we mean that she had a stepchild in the home or had a spouse or partner present who was a stepfather to at least one of her children.

After accounting for women’s demographic characteristics (such as their race, nativity and number of children ever born), we found that women who were not married when they had their first child were less likely than women who were married when they became mothers to be married at the time of the survey. This suggests either that women who were not married at their first birth were less likely to ever marry or that their marriages did not last.

Furthermore, among women who were living with a child, women who were not married at their first birth were more likely to live in a blended family at the time of the survey than women who were married when they became mothers. This suggests that women with nonmarital first births experience higher family turbulence than women whose first birth was in marriage.

Taken together, these data suggest that women with nonmarital first births may face greater family instability than women with marital first births do.

Posted in Families, Marriage | Tagged , , | 3 Comments