A selection of frequently asked questions for your perusal.
It’s a website that allows you to learn more about the neighbourhood you work, play or live in.
Wellbeing Toronto can help you to find out more neighbourhoods when you’re moving to a new house, planning a business investment, concerned about crime trends, locating a specific demographic group or simply interested in Toronto neighbourhoods. It’s an information tool.
There are 140 neighbourhoods. These were built for City planning and analysis purposes and may not exactly align with the boundaries of historical neighbourhoods such as Swansea or The Beach.
We expect to update the indicators every 2 years. Demographics data will be updated according to the Census schedule (new data from the 2011 Census will be released in 2012).
Many City of Toronto divisions, Agencies, Boards and Commissions were involved in the project. You can see a list of contributors on the application’s Acknowledgments page.
Yes, possibly, but this is no different from what Statistics Canada does when it releases large datasets. Any data can be misused, and Wellbeing Toronto tries to provide data that had not previously been available to the public. This helps researchers to confront problems and remove error. When evaluating any output from Wellbeing Toronto, one has to keep in mind the credibility of the person or institution which created that output, as is the case with any research.
Potential indicators were vetted through a long process that involved data providers and expert evaluation. Seven major criteria were used to evaluate shortlisted datasets: Accessibility, Comparability, Consistency, Credibility, Relevance, Measurability and Validity.
Wellbeing Toronto works best in modern browsers with fast Javascript engines, such as, Google Chrome or Firefox. It works reasonably well in some older browsers like Internet Explorer 8, but does not work properly in IE7 or IE6.
They allow you to weight your indicators. By sliding the value of an indicator to 5, you make it more important; by sliding it to 1 you make it less important. Sliding it to 0 (zero) temporarily removes it from the screen.
1 to 5 was chosen for its simplicity. Technically speaking, the large variation in many datasets may not be affected by a very granular scale such as 1-100; for example, moving the slider from 63 to 66 may not shift the underlying value enough to affect the picture on the map, leading the user to think the slider is broken. User experience testing has shown the 1-5 scale to be fairly easy to comprehend and it usually shows instant results. Wellbeing Toronto v1 used a 0-5 scale, but some users found the 0 to be confusing. Previously 0 turned an indicator completely off, but this has been removed.
When layers of information such as indicators are added together the result is called a Composite Index. It’s a composite because it combines data layers, and it’s an index because the result is a single number for each neighbourhood. The Wellbeing Toronto Composite Index which you control shows the highest, middling and lowest neighbourhoods for whatever combination of indicators you have selected.
For example, if you select Library Activity and Voting Turnout, your Composite Index will show those neighbourhoods with the highest library activity and highest voting turnout (the darkest colours) and also the lowest neighbourhoods (the lighter colours), plus everything in between. This does not necessarily mean that library activity and voting turnout are related to each; whether they are is beyond the scope of Wellbeing Toronto.
Each indicator shows the occurrence of some phenomena, such as Thefts or University Applicants. High occurrences (a lot of something) are shown in darker colours on the map; fewer occurences (very little of something) are shown in lighter colours.
A histogram is a bar chart that shows the distribution of values in a dataset. For example, when looking at the Seniors Living Alone indicator, most of the values are in the 1-40 range, with only a few in the 41-100 range. The histogram shows this distribution visually.
A Reference Period is a single year that may represent data from multiple years. For example, the Reference Period 2008 contains datasets from 2008, 2007 and Census data from the year 2006. The reason Wellbeing Toronto uses Reference Periods rather than just years is because it is very hard to collect data for every single year. In some cases the data is only available every few years, for example, the Census is only taken every 5 years (2006, 2011, 2016, etc.), so no data would be available in the years 2007, 2008, 2009 and 2010. Wellbeing Toronto groups these multi-year datasets together so that the user can see them all under one menu without having to skip between dozens of years. Indicators within a Reference Period are roughly comparable.
| REFERENCE PERIOD | MAY CONTAIN DATA FROM |
| 2008 | 2005 (Census income data) 2006 (Census year) 2007 2008 2009 |
| 2011 | 2009 2010 (Census income data) 2011 (Census year) 2012 2013 |
| 2016 | 2014 2015 (Census income data) 2016 (Census year) 2017 2018 2019 |
A score is a number between 1 and 100 that has represents a low amount of something (1) or a high amount of something (100). That something depends on which indicator is being looked at. Scores are calculated from raw numbers (eg, the # of trees in a neighbourhood) using a formula. Scaling the raw numbers to scores allows them to be added together to create a composite index. It is also referred to as a Scaled Value.
A Time Series in Wellbeing Toronto is an indicator showing the amount of change over time. For each indicator a % change over the Reference Period 2008-2011 is calculated. This percent change is then converted to a 1-100 score, with a 1 indicating a very large decrease (-100%, the phenomena disappears essentially) in an indicator, a 50 indicating no change (0%) and 100 indicating a lot of change (+100% or higher). The table below illustrates how percent changes in an indicator are converted to scores:
|
% CHANGE |
SCORE |
|
-100% |
1 |
|
Between -99.9% and -0.1% |
Between 1 and 49.9 |
|
0% |
50 |
|
Between +0.1% and +99.9% |
Between 50.1 and 99.9 |
|
+100% or higher |
100 |
It is important not to confuse percent change with scores, even though they may look similar.