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The Risk of Homelessness
1.
2. Table of Contents
• Introduction
• Indicator Source
• GraphoMap: QoLRS City Indicators Across Time
• City of Calgary: LICO & 30% of Income Spent on Rent
• City of Toronto: Aging Social Housing Stock
• Grand Montréal: Grand Montréal: Logements sociaux et populations
ayant des difficultés financières pour se loger
• Data Issues
• Municipal Data Collection Tool
• Programmable City & Indicators
3. Introduction - Pilot Atlas of the Risk of Homelessness
• Funded by:
– Data Development Projects on Homelessness Program, Homelessness
Knowledge Development Program, Homelessness Partnering Secretariat of
Human Resources and Social Development Canada (HRSDC)
• Partnership:
– Federation of Canadian Municipalities (FCM) Quality of Life Reporting
System (QOLRS) (24 cities) and the Geomatics and Cartographic Research
Centre
• 2 cities and 1 metropolitan area:
– City of Calgary
– City of Toronto
– Communauté métropolitaine de Montréal
• Geomatics and Cartographic Research Centre Research Team:
(https://gcrc.carleton.ca/confluence/display/GCRCWEB/Pilot+Atlas+of+the+Ri
sk+of+Homelessness):
– Research Leader: Tracey P. Lauriault (Tracey.Lauriault@NUIM.ie)
– Cartographer: Dr. Sebastien Cacquard,
– Geomatician: Christine Homuth
– Primary Investigator: Dr. D. R. Fraser Taylor
– Thanks to: Glenn Brauen, Amos Hayes and Jean-Pierre Fiset
15. Data Issues
• Statistics Canada Geographies change
• Health districts, wards, neighbourhoods and StatCan boundaries differ
• Formats differ
• The cost of StatCan special tabulations are cost prohibitive
• Restrictive access to some datasets – HIFIS
• CMHC data is very expensive
• Licenses are restrictive
• City data are the richest
The stories we can tell about Canada's social-policital-economy is impeded with
due to data cost and access issues
Vacancy rates:
Cicle total number of Rental Units
The Radial Line is Vacancy Rates
50% +
Circles #f Lone-parent family households with 50% or more of HH Income Spent on Rent
Radial Line % of these private households over the total number of Private Households Renters for each year.
Social Housing Waiting Lists
Circles total number of households on the Social Housing Waiting List
Radial Line percentage of households on the Social Housing Waiting List over to the total number of Rent Geared to Income (RGI) Units
Housing Starts for Rental, Condos and Private Homes
Circles total Number of Housing Starts for Rental Unit, or Condo or Private Homes
Radial Line is percentage of a type of Housing Starts over the Total Housing Starts
EA for for 1991
DA for 2001 and 2006
This series of maps represents the spatial interpolation of the percentage of both the Low Income Cut Off (LICO) and the households spending more than 30% in rent (30% plus). This interpolation is based on data provided at the EA scale (1991) and DA scale (2001 and 2006).
How to read this map: the darker areas represent the higher percentages, either in terms of LICO or 30% plus. For instance we can see an important increase of the percentage of households spending more than 30% in rent (30% plus) between 1996 and 2001.
Low income cut-offs (LICOs)
are income thresholds,
family expenditure data, below which families will devote a larger share of income to the necessities of food, shelter and clothing than the average family would.
Wanted to include the sSignpost study but could not as we could not get a boundary file of the health districts
Points display absolute values (numbers)
Colors display percentages for the same criteria.
Logements sociaux et communautaires : NPO, Coop, total des logements sociaux et abordables existants peu importe leur année de création, le loyer est fixé en fonction du revenu des locataires et indépendamment du marché du logement.
HLM : habitations à loyer modique
• PSL : Programme de supplément au loyer
• LAQ : Programme Logement Abordable Québec - Volet social et communautaire
• ACL : Programme AccèsLogis
* % = total number of rental housing by municipality, except for the 50% rate of effort which is calculated based on the total number of renter households.
* The quantile method has been used to discretise the % (bottom map). This method allows comparison between series of maps (e.g. for each criteria once can see in which part of the distribution each specific municipality is located). For some criteria (e.g. % LAQ), the high number of zeros affect the classification.