As a journalist, I would choose a classification method that distinctly shows the differences of class by color. Out of the four classification methods, Natural Breaks depicts the most differences between classes, and clearly shows variation. It is more easily comprehensible for the average reader. It also reflects different business districts in the city. Standard Deviation also shows differences, and may be useful to show how how much house costs differ from the average.

As a real estate agent, I would use equal interval because it shows more variation in house cost in areas around UBC. Standard Deviation also shows some variation around UBC, but the red color of these areas make these areas seem expensive, and could deter prospective home buyers.

Although choosing a classification method may be useful to convey different types of information or messages, it may also have the potential to be misleading. As a journalist, the natural breaks method may be chosen to make a message more sensational or dramatic to the reader, making Vancouver appear unaffordable. As a real estate agent, choosing equal interval may make house costs more affordable than they are to the potential buyer.

What does affordability measure, and why is it a better indicator of housing affordability than housing cost alone?

Affordability is defined by two sets of data: Cost of housing and income. It is a better indicator of affordability because it takes income into account, and measures local purchasing power in each census tract.

What are the housing affordability rating categories? Who determined them and are they to be “trusted”? 

Housing affordability is rated by several categories: Affordable (Green), moderately affordable (light green), unaffordable (orange), and severely unaffordable (red). These classes are made by the map maker, so it is subject to bias depending on the message the map maker is trying to convey.  

To compare two cities, is to compare two different data sets. When using natural breaks, the class ranges will differ for the two data sets of the two cities. Therefore, using manual breaks is more effective to directly compare two different cities is more effective. By using manual breaks, the data is standardized and can be directly compared. For example, by looking at Vancouver, the map looks more crowded with red areas than Ottawa. This means that there is a higher density of more expensive housing in Vancouver than in Ottawa. If natural breaks classification methods were used, then the maps would be more similar in color.

Is affordability a good indicator of the city’s “livability”?

Affordability is only one aspect of livability, and cannot stand alone as a sole indicator of livability. Features that make a city livable would improve quality of life and increasing standard of living. For each city, livability may be defined differently based on differing local economies and political climate and social values. Other factors that may be used to measure livability may include crime rates, sanitation standards, health standards, and economic municipal investments in public services. Depending on the city, these factors may vary greatly – for example, public interest in maintaining environmental protection standards may be highly dependent on local culture and geography.