What do we mean by a neighborhood?
NeighborhoodScout® uses the official government designation for neighborhoods - the census tract.
Census tracts are small, relatively permanent subdivisions of a county that are defined by the U.S. Census Bureau in conjunction with local authorities all across the country to define real neighborhoods that are bounded to contain areas with homogeneous population characteristics (including economic status, lifestyle, and living conditions). Census tracts usually have 4,000 persons, but can range between 1,500 and 8,000 persons. This is the most fine-grained area for which detailed information is made available from the government, to protect the individual privacy of each of us. Because census tracts are based on population, they vary in size depending on the density of settlement. In urban areas, they are small, and in rural areas they can cover an entire small town or even a few small towns in very rural areas.
Since census tracts are subdivisions of a county, we did a spatial overlay of the census tracts onto city and town boundaries using a geographic information system to properly assign each census tract to its appropriate city or town. Then we named each census tract to the local colloquially recognized neighborhood name for that spot (e.g., Boston, MA (Dorchester). If there was not a name available, we named the census tract by the largest street intersection in the census tract (e.g., Worcester, MA (Lincoln St/Plantation St)
Why we don't use Zip Codes as neighborhoods
Zip codes were developed by the Postal Service for the purpose of delivering mail, but were never intended to define coherent neighborhoods. In addition, Zip Codes can have as many as 10 distinctly different census tracts contained within them. When distinct census tracts are blended together in a single Zip Code, the data reflects their average conditions and often gives a false sense of the area. The result is that potentially great matching neighborhoods can be missed, and erroneous matches can also be produced and delivered to you.
Using census tracts makes great matches possible, and helps people find the areas that are best for them and their families. Because we are committed to providing the highest possible quality and finding the neighborhoods that best meet your criteria, we use census tracts. And, as always, we show you the actual street map of the neighborhood so you know exactly where your best matching neighborhood is located.
What is a Condition Alert?
A condition alert is a condition in the neighborhood that triggers an alert. NeighborhoodScout contains condition alerts to highlight conditions that are extreme, whether good or bad. This helps answer crucial questions about the state of the neighborhood being evaluated, such as:
What are the risks of violent crime here?
Is the risk of home break-ins or other property crimes increasing?
Does real estate here hold its value?
Are the trends in local vacancies or unemployment concerning?
...and dozens more.
Information at a glance that you need to know to invest, appraise or finance a property.
Saxeville median real estate price is $329,593, which is more expensive than 58.2% of the neighborhoods in Wisconsin and 44.3% of the neighborhoods in the U.S.
The average rental price in Saxeville is currently $1,106, based on NeighborhoodScout's exclusive analysis. Rents here are currently lower in price than 92.2% of Wisconsin neighborhoods.
Saxeville is a remote neighborhood (based on population density) located in Wild Rose, Wisconsin.
Saxeville real estate is primarily made up of small (studio to two bedroom) to medium sized (three or four bedroom) single-family homes and mobile homes. Most of the residential real estate is owner occupied. Many of the residences in the Saxeville neighborhood are established but not old, having been built between 1970 and 1999. A number of residences were also built between 1940 and 1969.
Vacant apartments or homes are a major fact of life in Saxeville. The current real estate vacancy rate here is 62.8%. This is higher than the rate of vacancies in 99.5% of all U.S. neighborhoods. A relatively large percentage of housing here is seasonally occupied (58.4%). This can occur in vacation areas, and occasionally it is also found in neighborhoods that are primarily filled with college students, as some apartments could be vacant when school is not in session. If you live here year round, you may find that a number of buildings in your neighborhood are actually empty.
Notable & Unique Neighborhood Characteristics
The way a neighborhood looks and feels when you walk or drive around it, from its setting, its buildings, and its flavor, can make all the difference. This neighborhood has some really cool things about the way it looks and feels as revealed by NeighborhoodScout's exclusive research. This might include anything from the housing stock to the types of households living here to how people get around.
Real Estate
Vacant homes and apartments are a significant characteristic of this neighborhood. In fact, with 62.8% of the residential real estate vacant, the Saxeville neighborhood claims the distinction of having a higher vacancy rate than 99.5% of the neighborhoods in America. This can either be because much of the property is seasonally occupied, like in many vacation areas, or that much of the real estate is more permanently abandoned.
In addition, this neighborhood has wide open spaces, few people, and lots of space to stretch out. If you like locations that fit that description, you may like this neighborhood. Based on NeighborhoodScout's exclusive analysis, with only 37 people per square mile living here, this neighborhood is less crowded than 91.3% of America.
Diversity
Did you know that the Saxeville neighborhood has more German and Polish ancestry people living in it than nearly any neighborhood in America? It's true! In fact, 44.5% of this neighborhood's residents have German ancestry and 14.6% have Polish ancestry.
Saxeville is also pretty special linguistically. Significantly, 11.6% of its residents five years old and above primarily speak Polish at home. While this may seem like a small percentage, it is higher than 98.7% of the neighborhoods in America.
The Neighbors
There are two complementary measures for understanding the income of a neighborhood's residents: the average and the extremes. While a neighborhood may be relatively wealthy overall, it is equally important to understand the rate of people - particularly children - who are living at or below the federal poverty line, which is extremely low income. Some neighborhoods with a lower average income may actually have a lower childhood poverty rate than another with a higher average income, and this helps us understand the conditions and character of a neighborhood.
The neighbors in the Saxeville neighborhood in Wild Rose are lower-middle income, making it a below average income neighborhood. NeighborhoodScout's research shows that this neighborhood has an income lower than 63.6% of U.S. neighborhoods. With 22.8% of the children here below the federal poverty line, this neighborhood has a higher rate of childhood poverty than 72.7% of U.S. neighborhoods.
The old saying "you are what you eat" is true. But it is also true that you are what you do for a living. The types of occupations your neighbors have shape their character, and together as a group, their collective occupations shape the culture of a place.
In the Saxeville neighborhood, 27.2% of the working population is employed in executive, management, and professional occupations. The second most important occupational group in this neighborhood is sales and service jobs, from major sales accounts, to working in fast food restaurants, with 26.7% of the residents employed. Other residents here are employed in manufacturing and laborer occupations (26.2%), and 17.3% in clerical, assistant, and tech support occupations.
Languages
The languages spoken by people in this neighborhood are diverse. These are tabulated as the languages people preferentially speak when they are at home with their families. The most common language spoken in the Saxeville neighborhood is English, spoken by 96.9% of households. Other important languages spoken here include Polish and German/Yiddish.
Ethnicity / Ancestry
Culture is the shared learned behavior of peoples. Undeniably, different ethnicities and ancestries have different cultural traditions, and as a result, neighborhoods with concentrations of residents of one or another ethnicities or ancestries will express those cultures. It is what makes the North End in Boston so fun to visit for the Italian restaurants, bakeries, culture, and charm, and similarly, why people enjoy visiting Chinatown in San Francisco.
In the Saxeville neighborhood in Wild Rose, WI, residents most commonly identify their ethnicity or ancestry as German (44.5%). There are also a number of people of Polish ancestry (14.6%), and residents who report English roots (9.2%), and some of the residents are also of Irish ancestry (7.9%), along with some Mexican ancestry residents (5.1%), among others.
Getting to Work
How you get to work – car, bus, train or other means – and how much of your day it takes to do so is a large quality of life and financial issue. Especially with gasoline prices rising and expected to continue doing so, the length and means of one's commute can be a financial burden. Some neighborhoods are physically located so that many residents have to drive in their own car, others are set up so many walk to work, or can take a train, bus, or bike. The greatest number of commuters in Saxeville neighborhood spend between 15 and 30 minutes commuting one-way to work (43.7% of working residents), which is shorter than the time spent commuting to work for most Americans.
Here most residents (80.8%) drive alone in a private automobile to get to work. In addition, quite a number also carpool with coworkers, friends, or neighbors to get to work (5.3%) . In a neighborhood like this, as in most of the nation, many residents find owning a car useful for getting to work.
SCOUT’s patented match algorithm identifies the most similar neighborhoods to a subject location, and quantifies the similarity to the subject location. This allows analysts to identify the most similar neighborhoods in a local market area for appraisals, investments, and research.
The algorithm uses 273 neighborhood conditions, identifies the dominant dimensions underlying the conditions and calculates the similarity. This captures the true culture and character of locations, economic conditions, and trends.
The closer to 100% means the locations are nearly identical. 80% is a very good, but not excellent match, and so forth.
