Lab 4: Housing Affordability
Data Class Map:
Different methods of data classification affect the different interpretations of data on maps. For example, if I were a journalist, I would use natural breaks, because it gives a more realistic depiction of housing costs, and takes in the distribution of the data; showing the price differences between each area. However, if I were a real estate agent, I would use equal interval to make the area near UBC to appear cheaper and more affordable than what it actually is in order to draw in buyers. Indeed, there are ethical implications for the classification methods, because equal interval doesn’t take in account the distribution of the data, making it appear cheaper and more spread out. Thus, providing unreliable and perhaps biased data. Additionally, because this data is from 2011, it is not reliable, because within 6 years, the housing prices have skyrocketed, and housing affordability is even more unreasonable now
Affordability Map:
1.What is affordability measuring, and why is it a better indicator of housing affordability than housing cost alone
The affordability is measuring the the income of the residences in relation to the cost of their homes. This is a better indicator of housing costs, because different areas have higher incomes than others, resulting in a majority of the locals being able to afford more expensive homes.
2. What are the housing affordability rating categories? Who determined them and are they to be ‘trusted’?
The housing affordability rating categories are affordable, moderately unaffordable, seriously unaffordable, and severely unaffordable. These are determined by Census Canada. These categories cannot be trust, because different maps can produce different distributions of affordability. Therefore, the portrayal of affordability is biased
3. Is affordability a good indicator of a city’s ‘livability’?
Affordability is a good indicator of a city’s livability because shelter is a basic need, and if we are unable to afford shelter, then we are not fulfilling one of our basic needs to survive. Therefore, the area can be considered unlivable if it is severely unaffordable.
Accomplishment Statement:
- Developed a working knowledge on Census data through researching its terms and extracting specific attributes from the data.
- Developed an understanding on the implications of the different data classifications through creating an affordability map with each data classification.
- Practiced normalizing data by normalizing house cost by income to create an affordability map.