This is a small community in a single neighborhood.
As throughout the site, some neighborhood-level data are reserved for subscribers.
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.
Belle is a very small town located in the state of West Virginia. With a population of 1,125 people and just one neighborhood, Belle is the 146th largest community in West Virginia.
Occupations and Workforce
Unlike some towns, Belle isn’t mainly white- or blue-collar. Instead, the most prevalent occupations for people in Belle are a mix of both white- and blue-collar jobs. Overall, Belle is a town of professionals, sales and office workers, and service providers. There are especially a lot of people living in Belle who work in office and administrative support (11.11%), sales jobs (11.11%), and business and financial occupations (8.64%).
Also of interest is that Belle has more people living here who work in computers and math than 95% of the places in the US.
One interesting thing about the economy is that relatively large numbers of people worked from their home: 13.91% of the workforce. While this number may seem small overall, as a fraction of the total workforce this is high compared to the rest of the county. These workers are often telecommuters who work in knowledge-based, white-collar professions. For example, Silicon Valley has large numbers of people who telecommute. Other at-home workers may be self-employed people who operate small businesses out of their homes.
Setting & Lifestyle
Demographics
The education level of Belle citizens is a little higher than the average for US cities and towns: 21.90% of adults in Belle have at least a bachelor's degree.
The per capita income in Belle in 2022 was $29,026, which is upper middle income relative to West Virginia, and lower middle income relative to the rest of the US. This equates to an annual income of $116,104 for a family of four. However, Belle contains both very wealthy and poor people as well.
The people who call Belle home describe themselves as belonging to a variety of racial and ethnic groups. The greatest number of Belle residents report their race to be White, followed by Black or African-American. Important ancestries of people in Belle include English, Irish, German, Scottish, and Swedish.
The most common language spoken in Belle is English. Other important languages spoken here include Italian and Spanish.
Notable & Unique Neighborhood Characteristics
Many things matter about a neighborhood, but the first thing most people notice is the way a neighborhood looks and its particular character. For example, one might notice whether the buildings all date from a certain time period or whether shop signs are in multiple languages. This particular neighborhood in Belle, the neighborhood, has some outstanding things about the way it looks and its way of life that are worth highlighting.
Occupations
The government often provides some of the more stable jobs in the economy. From local, to state, to federal government workers, the government can also be a major employer. What NeighborhoodScout's analysis revealed, is that the neighborhood in particular stands out when compared nationally for the proportion of its working residents who are employed by the government. At 14.8% of its workforce, this neighborhood has a greater concentration of government workers than 97.0% of U.S. neighborhoods.
The Neighbors
How wealthy a neighborhood is, from very wealthy, to middle income, to low income is very formative with regard to the personality and character of a neighborhood. Equally important is the rate of people, particularly children, who live below the federal poverty line. In some wealthy gated communities, the areas immediately surrounding can have high rates of childhood poverty, which indicates other social issues. NeighborhoodScout's analysis reveals both aspects of income and poverty for this neighborhood.
The neighbors in the neighborhood in Belle are lower-middle income, making it a below average income neighborhood. NeighborhoodScout's research shows that this neighborhood has an income lower than 71.5% of U.S. neighborhoods. With 12.9% of the children here below the federal poverty line, this neighborhood has a higher rate of childhood poverty than 55.9% of U.S. neighborhoods.
A neighborhood is far different if it is dominated by enlisted military personnel rather than people who earn their living by farming. It is also different if most of the neighbors are clerical support or managers. What is wonderful is the sheer diversity of neighborhoods, allowing you to find the type that fits your lifestyle and aspirations.
In the neighborhood, 44.4% 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 25.4% of the residents employed. Other residents here are employed in manufacturing and laborer occupations (19.1%), and 14.8% in government jobs, whether they are in local, state, or federal positions.
Languages
The most common language spoken in the neighborhood is English, spoken by 99.6% of households. Some people also speak Italian (3.0%).
Ethnicity / Ancestry
Culture is shared learned behavior. We learn it from our parents, their parents, our houses of worship, and much of our culture – our learned behavior – comes from our ancestors. That is why ancestry and ethnicity can be so interesting and important to understand: places with concentrations of people of one or more ancestries often express those shared learned behaviors and this gives each neighborhood its own culture. Even different neighborhoods in the same city can have drastically different cultures.
In the neighborhood in Belle, WV, residents most commonly identify their ethnicity or ancestry as Irish (9.1%). There are also a number of people of English ancestry (8.2%), and residents who report German roots (7.6%), and some of the residents are also of Scottish ancestry (3.1%), along with some Dutch ancestry residents (2.0%), 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 neighborhood spend between 15 and 30 minutes commuting one-way to work (53.7% of working residents), which is shorter than the time spent commuting to work for most Americans.
Here most residents (83.4%) 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 (12.1%) . 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.
