This document summarizes a presentation about using local census data to conduct neighborhood-level research in Canada. It discusses two examples: a pilot atlas of homelessness risk that mapped census data at the neighborhood level for three cities, and the Community Social Data Strategy, which provides municipalities and non-profits access to census and other data to understand social trends in their communities. The presentation argues that neighborhood-level research is important but difficult due to limitations of available data sources and organizational mandates. It shows examples of how the atlas and data strategy projects have overcome these challenges to map indicators like income, housing, and donations at small geographic levels.
ENGLISH 7_Q4_LESSON 2_ Employing a Variety of Strategies for Effective Interp...
The Real LF-Census informs Neighbourhood Research in Canada
1. The Real LF-Census informs Neighbourhood
Research in Canada
Statistical Society of Ottawa
8th annual seminar – Our Statistics Community
Monday the 25th of October., 2010
Desmarais DMS1160
Presenter: Tracey P. Lauriault, tlauriau@gmail.com
Sources: Geomatics and Cartographic Research Centre, Acacia
Consulting and Research, Community Social Data Strategy (CSDS)
2. Table of Contents
• Introduction
• Local Scale Research
• Example 1: Pilot Atlas of the Risk of Homelessness
• Example 2: Community Social Data Strategy (CSDS)
4. Mandate - Scale
• Jurisdiction
– Federal – National, Departments, Programs, Agencies
– Provincial and Territorial
– City, Municipality, Metropolitan Regions
– Wards & Neigbhourhood
• Mandates
– Health
– School Boards
– Postal, etc.
• Who does
– Thematic national scale research – Homelessness? Social Policy?
– Trans-Provincial & Territorial Research?
– Between cities?
– Neighbourhoods?
Mandates and/or jurisdictions limit the scale at which research can be
conducted, what can be told and the types of data to be accessed
5. Community based research
• Research conducted at municipal and sub-municipal scales
– Cities
– Wards
– Neighbourhoods
– Health Districts
– School catchments
– Etc.
• Conducted by or for:
– Non-Profit community based organizations
• Social planning councils, community development councils,
United Way's, Community Foundations, Canadian Council on
Social Development, Culture specific groups, Religious Groups,
etc.
– School Boards
– Police Forces
– Municipalities, cities, counties,
– Business Improvement Associations
– Neighbourhood associations
– etc.
6. Sub-Municipal Census Alternatives
Theme Data Souce Geography Sub-Municipal Useable
Activities of daily
Living
Participation and
Activity Limitation
Survey (PALS)
Provincial NO NO, Canceled
Sociocultural
Information
Citizen Immigration
Canada Landings CSD Only NO
NO, Incomplete
Sample
Ancestral Origin No Alternative NO
First Nations DIAND, Admin. Data ? ? ?
Mobility No Alternative NO
Place of Birth of
Parents
Citizen Immigration
Canada Landings CSD Only NO
NO, Incomplete
Sample
Household Activities
National Survey of
Giving, Volunteering
and Participating
Provincial NO NO, Canceled
Labour Market
Activities
HRSDC Admin.Data
? ? ?
Income SAAD - Taxfiler Postal Code Yes, not rural areas Big Cities
Dwellings CMHC CMA NO NO
No possibility for cross
tabulations
8. 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)
• 2 cities and 1 metropolitan area:
– City of Calgary
– City of Toronto
– Communauté métropolitaine de Montréal
9. Data Sources
• Federation of Canadian Municipalities (FCM) Quality of Life Reporting System
(QOLRS)
– Canada Housing and Mortgage Corporation (CMHC)
– Statistics Canada, LF-Census and LF-Census Special Cross Tabulations
• Maps, Data, and Government Information (MADGIC), Library, Carleton University
– Data Liberation Initiative (DLI) Statistics Canada LF-Census
– Statistics Canada Geography Division digital maps (EA, DA, CT, CD, CSD,
Provinces, Canada Political)
• City of Toronto
– Social Policy Analysis and Research Section: Neighbourhood file
– Toronto Housing Connections: Social Housing Registry
– Toronto Community Housing Corporation: Social Housing Data
• City of Calgary
– Community and Neighbourhood, Social Policy and Planning Division:
Neighbourhood file
• Communauté Métropolitaine de Montréal (CMM),
– Direction des Politiques et interventions de développement: Special tabulation
LF-Census data, CMM framework base map, Housing data
10. Why focus on the Risk of Homelessness?
The main objective of the Pilot Atlas of the Risk of Homelessness is to create
useful, tangible, engaging and accessible mapped data to inform public
policy, decision makers and the public
19. Community Social Data Strategy
• CSDS is led by the Canadian
Council on Social Development
(CCSD)
• It is a gateway for municipalities
and community-based
organizations to access data to
identify and better understand the
social and economic trends within
their individual communities
• 250 organizations in seventeen
urban regions, including more
than 50 Canadian cities and towns
located in 5 provinces
• Brings together municipal
governments, social planning
networks, health and family
service agencies, school boards,
police services, United Ways, and
many others...
Source:
https://csds-sacass.ca/drupal/MembersList
21. City of Hamilton
Source:
CSDS Consortium Member – Social Planning and Research Council of Hamilton
http://www.sprc.hamilton.on.ca/CommunityMappingService.php
22. RM-Halton Geography Examples
Source:
CSDS Consortium Members – Halton Region - Our Kids Our Community Report Card
http://www.ourkidsnetwork.ca/about/partners.shtml
Report Card Partners
• Halton Catholic District
School Board
• ROCK Reach Out Centre
for Kids
• Halton Children's Aid
Society
• Halton District School
Board
• Halton Region,
Departments of Health
and Social & Community
Services
• Halton Regional Police
Services
• Transitions for Youth
26. Sault Ste. Marie
Source:
CSDS Consortium Member Sault Ste. Marie Innovation Centre presentation entitled 2009
United Way Donation and Socio-Demographic Maps
27. Sault Ste. Marie
Source:
CSDS Consortium Member Sault Ste. Marie Innovation Centre presentation entitled 2009
United Way Donation and Socio-Demographic Maps
28. Sault Ste. Marie – Census Tracts
Source:
CSDS Consortium Member Sault Ste. Marie Innovation Centre Community Geomatics
Centre CT Framework Data Maps
30. Thanks!
Atlas of the Risk of Homelessness:
http://gcrc.carleton.ca/homelessness
Community Social Data Strategy
https://www.csds-sacass.ca/drupal/
Contact:
tlauriau@gmail.com, #TraceyLauriault,
http://traceyplauriault.ca
Hinweis der Redaktion
“those facing the risk of losing their shelter either by eviction or the expiry of the lease, with no other possibility of shelter in view. Prisoners or people living in other institutions facing their release and having no place to go to are considered as part of this population.” (Springer, 2000:480). These are also individuals or families whose living spaces do not meet minimum health and safety standards, and do not offer security of tenure, personal safety and/or affordability. In the FCM QOLRS, the technical team has selected a variety of indicators associated with the risk of homelessness and these are: those that spend more than 50% of their income on rent, people living in substandard housing, those on social housing waiting lists, the poor and those who are living on low, insecure or feeble incomes, people on fixed incomes such as seniors or those receiving social assistance, and some demographic groups such as lone parent families. Also see the definition Affordable, Appropriate Housing (AAH).
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.
Canada Post has these: http://www.canadapost.ca/cpc2/addrm/hh/maps/fsa/ON34.pdf and http://www.canadapost.ca/cpc2/addrm/hh/maps/FSA/ON36.pdf.
By looking at these maps, you may notice that the FSA’s for Northern Ontario are huge in size. Most of the rural area of the Algoma District is covered in two FSA’s (P0S, P0R), with some area’s lying within the gigantic P0M area. There are 3 FSA’s for Sault Ste. Marie, and one for Elliot Lake. The P6A area stands out in SSM, as it covers the downtown core, the east side of the city and parts of two First Nation Reserves. In short, any data grouped by FSA (including the SAAD dataset) cannot be used at a meaningful sub-municipal level. For SSM, if we had to rely on the SAAD dataset to replace some information found in the census long form, we would need at least CT level geography. As far as I know, CT level SAAD data is prohibitively expensive. I’m pretty sure it doesn’t come at the DA level either. If it does, I can’t even imagine what it would cost.
The problem with CTs is that the SSM Census Agglomeration area is tracted, while the rest of the Algoma District is not. Therefore, CT level data is not useful for rural Algoma. We have to rely on CSDs or DAs.
I’m sure these problems exist in other municipalities, but I have attached a rudimentary map showing the CTs in and immediately surrounding the urban area of SSM. It seems, in areas with low population density, neighbourhoods can be grouped together rather haphazardly. Take a look at tracts 5900008.00 and 5900018.01. Notice how they both group neighbourhoods that are fairly far apart from each other?