Kerry McCarthy – Cities, Suburbs & Schools Project at Trinity College

Does buying a home also buy you entrance into a school?

November 27, 2012Kerry McCarthy

This home-buying simulation is designed to help readers discover how wealth and housing affects schooling opportunity. Readers will randomly choose a demographic of a Hartford family and will navigate the home-buying and school selection process, based on this demographic, using numerous online resources. The objective of this simulation is to help readers discover the relationship between housing policy and educational policy in the city of Hartford and in the United States.

Demographics: What does your family look like?

Each family currently lives in Hartford and would like to move to the suburbs. Each family has one child in third grade and might have another child in the future. That being said, a two-bedroom house is necessary but a three-bedroom house is ideal. (Readers: it is also important to note the other demographic factors of each family other than just income). Renting an apartment is also an option for families if they cannot afford a house.

1) Family A has an annual gross income of $40,000 and has $5,000 saved for down payment. Family does not own a car and has no monthly debt payments.

2) Family B has an annual gross income of $80,000 and has $10,000 saved for down payment. Family does not own a car and has $200 monthly debt payments.

3) Family C has an annual gross income of $120,000 and has $20,000 saved for down payment. Family owns a car and has no monthly debt payments.

As a reader, randomly choose a demographic profile. Once you have done this, you must navigate the remaining aspects of the simulation fitting this demographic and noting your results in the Home Buyers Notepad, found at the bottom of this post. (Note: please do not click “submit” until all of your information is entered).

Mortgages: What can you afford?

Click to Open BankRates Mortgage Rates

In order to get the home-buying process started, find the current rate for a 30-year fixed mortgage (pictured to the right). Jot down the current rate in the Home Buyer’s Notepad, found at the bottom of this post.

Click to Open CNN House Affordability Calculator

Now, utilize the internet mortgage affordability calculator (pictured to the left) to estimate purchase prices of homes that you can afford. By entering your mortgage and income information, this calculator will give you an idea of what you can afford to pay for a home. It gives you both the “minimum house price” and the “maximum house price”; for the purpose of this simulation, you may shop for any home that falls in this range.

While a house is ideal, the family will settle for an apartment. In order to calculate monthly rent affordability, calculate 33% of monthly gross income. Note your monthly rent affordability at the bottom of the post.

House Hunting: What are your options?

According to your affordable price range for buying and renting, start looking for houses in Hartford and the surrounding suburbs. You may use the internet or newspaper listings in order to find residences in suburban towns, keeping in mind that the space must accommodate two parents plus one child (and possibly another on the way). Also, keep in mind that both parents hold jobs in the city of Hartford. That being said, it would not be advisable to move too far outside the city of Hartford if one does not have a car. Internet listings on craigslist and zillow.com are great places to start, while other online resources are useful as well. It is important to note the address of the town, including street name and town name. Note 3 home or apartment listings in the Home Buyer’s Notepad at the bottom of the post.

The School Search

Click to Navigate the SmartChoices Website

Once you have determined 3 homes or apartments that you can afford, it is time to find out which schools your child will attend. By utilizing the Smart Choices website, you can see listings of schools that are available to your family, both district and inter-district. You can also access information about each school, such as racial balance, test goal, and test gain. Once you enter the address of your potential home, note the “quality” of education that your child would receive if you lived in that particular district. Any other information online that you can find about schools in your district will be helpful as well. Note this information in the Home Buyer’s Notepad, below.

Reflections: What did you learn?

Once you have completed your search, explore what other readers have discovered through this simulation through this Google Spreadsheet. Look for patterns and trends in the data. Also, it may be helpful to read what the author discovered in her simulation in order to connect housing options to school opportunities.

In order to understand the reasoning behind this simulation process, please read the “How It Was Made” post.

Below, please note the information that you are asked to record throughout the simulation. Do not click submit until all of the questions are answered.

How To Lie With Maps

November 5, 2012Kerry McCarthy

As explained by Mark Monmonier in “How to Lie With Maps”, data can easily be skewed when a researcher converts it into a map. By fiddling with the settings on a map, one can portray two completely different stories with the same data. By merging Connecticut Census Data with School District Data in our class, we were able to combine the two sets of information and create maps. However, it is evident that different maps can be made in order to show differing stories.

Racial Makeup of Hartford and Surrounding Towns, 2009-2010

Key of Racial Makeup of Hartford and Surrounding Towns, 2009-2010

For the purpose of this post, I focused on the Percent Minority Data (2009-2010) for Hartford and the surrounding towns. In the map on the left, one would assume that there is widespread racial diversity throughout the towns. In order to create this effect, I changed the map settings so that there were six shades of maroon; each shade signified a certain percentage of minorities in a specific town. Because there were so many shades, the map portrays a large number and range of minorities in Hartford and the surrounding towns. The designations for the colors and percent minorities can be found in the key to the left.

Racial Makeup of Hartford and Surrounding Towns, 2009-2010

Key of Racial Makeup of Hartford and Surrounding Towns, 2009-2010

In contrast, the map on the right portrays sharp racial differences between Hartford and the surrounding towns. While Hartford and Bloomfield are shaded black, all of the other surrounding towns are shaded gray. This portrays stark differences in the racial makeup of Hartford and the surrounding areas. I made the map look this way by only using two colors: black and gray (see the key to the right). This effect was further portrayed by the fact that I designated the towns with 0-90% minorities to be colored gray, while the towns who are comprised of 90-100% minorities to be colored black. It does not look like there is a wide range of racial diversity in this map, as it does in the first map.

Lying With Statistics

October 26, 2012Kerry McCarthy

Data can easily be skewed in order to prove or disprove a point or area of research. When looking at progress towards the Sheff I goal, information portrayed in a graph can be situated to look like schools are making either grand leaps in progress, or small steps. After taking data from Figure 5.1, titled “Actual and Legal Progress toward Sheff I Goal, 2003-2007″, and making it into a line graph, it is easy to see that data can be skewed in order to prove a point.

Slow Progress Toward Sheff I Goals

Looking at the graph to the right, it looks like schools are not making a lot of progress in regards to meeting the 2006-07 goal. The slope of the line is not very steep because the y-values are separated by increments of 20%. This makes the progress line seem horizontal and slow-moving. It looks like it will take some time before schools meet their goal of 30%. I made this graph by utilizing the “Insert Chart” option on Google Spreadsheet. By fiddling with the minimum and maximum values, along with the scale of the y-axis, I made the graph look like schools are not making progress towards meeting the 2006-07 Sheff I goals.

Quick Progress Toward Sheff I Goals

Looking at the graph to the left, one would assume that the schools are making steady progress towards meeting the 2006-07 goals. I purposely did not include the “Goal” line of 30% integration because I wanted to make the line as steep as possible (within reason). In order to do this, I made the y-interval scale .1 and only showed five percentage points. Since the y-interval maximum was 14%, the line goes beyond the graph, which makes it seem like schools are making great progress. If one were to glance at this map without looking closely at the y-intervals, one would assume that schools are making progress.

I found this exercise very helpful in terms of understanding how people can play with graphs in order to prove their point.