The Loss of the Long-Form Census and the effects on the ability to do Neighbourhood Analysis


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The Census is the only national public policy tool that collects data with a large enough sample size to report findings at small sub-municipal geographic scales.  The loss of the long-form census may impede researchers and community based organizations from conducting neighbourhood analysis.  Other surveys conducted by Statistics Canada do not have a large enough sample size to fill this gap. Canadians may be left with analyzes on a variety of public policy issues only at the city or metropolitan area scale.  This would impede the ability for place based analysis and location specific action.  Neighbourhood scale research using Census data will be discussed, The Cybercartographic Pilot Atlas of the Risk of Homelessness created at the Geomatics and Cartographic Research and other examples from community based research initiatives such as the Community Data Consortium will be presented. This will include maps and data about social issues in Canadian cities & metropolitan areas (e.g. Calgary, Toronto, Halton, Sault Ste. Marie, Hamilton, Ottawa, Montreal, & others) to demonstrate the importance of local analysis.  The impact of the loss for evidence based decision making for communities in Canada’s will be the key element of the discussion.

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  • “ 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: and 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?
  • The Loss of the Long-Form Census and the effects on the ability to do Neighbourhood Analysis

    1. 1. The Loss of the Long-Form Census and the effects on the ability to do Neighbourhood Analysis Coming to Our Senses: Theorizing the Contexts and Impacts of Making the Census Long-Form Voluntary A Multidisciplinary Graduate Student Conference Saturday the 26th March., 201 Simard 129 Presenter: Tracey P. Lauriault, [email_address] Sources: Geomatics and Cartographic Research Centre, Acacia Consulting and Research, Community Social Data Strategy (CSDS)
    2. 2. Table of Contents <ul><li>Introduction </li></ul><ul><li>Local Scale Research </li></ul><ul><li>Example 1: Pilot Atlas of the Risk of Homelessness </li></ul><ul><li>Example 2: Community Social Data Strategy (CSDS) </li></ul>
    3. 3. Local Scale Research
    4. 4. Mandate - Scale <ul><li>Jurisdiction </li></ul><ul><ul><li>Federal – National, Departments, Programs, Agencies </li></ul></ul><ul><ul><li>Provincial and Territorial </li></ul></ul><ul><ul><li>City, Municipality, Metropolitan Regions </li></ul></ul><ul><ul><li>Wards & Neigbhourhood </li></ul></ul><ul><li>Mandates </li></ul><ul><ul><li>Health </li></ul></ul><ul><ul><li>School Boards </li></ul></ul><ul><ul><li>Postal, etc. </li></ul></ul><ul><li>Who does </li></ul><ul><ul><li>Thematic national scale research – Homelessness? Social Policy? </li></ul></ul><ul><ul><li>Trans-Provincial & Territorial Research? </li></ul></ul><ul><ul><li>Between cities? </li></ul></ul><ul><ul><li>Neighbourhoods? </li></ul></ul><ul><li>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 </li></ul>
    5. 5. Community based research <ul><li>Research conducted at municipal and sub-municipal scales </li></ul><ul><ul><li>Cities </li></ul></ul><ul><ul><li>Wards </li></ul></ul><ul><ul><li>Neighbourhoods </li></ul></ul><ul><ul><li>Health Districts </li></ul></ul><ul><ul><li>School catchments </li></ul></ul><ul><ul><li>Etc. </li></ul></ul><ul><li>Conducted by or for: </li></ul><ul><ul><li>Non-Profit community based organizations </li></ul></ul><ul><ul><ul><li>Social planning councils, community development councils, United Way's, Community Foundations, Canadian Council on Social Development, Culture specific groups, Religious Groups, etc. </li></ul></ul></ul><ul><ul><li>School Boards </li></ul></ul><ul><ul><li>Police Forces </li></ul></ul><ul><ul><li>Municipalities, cities, counties, </li></ul></ul><ul><ul><li>Business Improvement Associations </li></ul></ul><ul><ul><li>Neighbourhood associations </li></ul></ul><ul><ul><li>etc. </li></ul></ul>
    6. 6. Sub-Municipal Census Alternatives No possibility for cross tabulations 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
    7. 7. Pilot Atlas of the Risk of Homelessness
    8. 8. Introduction <ul><li>Pilot Atlas of the Risk of Homelessness </li></ul><ul><li>Funded by: </li></ul><ul><ul><li>Data Development Projects on Homelessness Program, Homelessness Knowledge Development Program, Homelessness Partnering Secretariat of Human Resources and Social Development Canada (HRSDC) ‏ </li></ul></ul><ul><li>Partnership: </li></ul><ul><ul><li>Federation of Canadian Municipalities (FCM) Quality of Life Reporting System (QOLRS) (24 cities) ‏ </li></ul></ul><ul><li>2 cities and 1 metropolitan area: </li></ul><ul><ul><li>City of Calgary </li></ul></ul><ul><ul><li>City of Toronto </li></ul></ul><ul><ul><li>Communaut é m é tropolitaine de Montr é al </li></ul></ul>
    9. 9. Data Sources <ul><li>Federation of Canadian Municipalities ( FCM ) Quality of Life Reporting System ( QOLRS ) </li></ul><ul><ul><li>Canada Housing and Mortgage Corporation ( CMHC )‏ </li></ul></ul><ul><ul><li>Statistics Canada , LF-Census and LF-Census Special Cross Tabulations </li></ul></ul><ul><li>Maps, Data, and Government Information ( MADGIC ), Library, Carleton University </li></ul><ul><ul><li>Data Liberation Initiative (DLI) Statistics Canada LF-Census </li></ul></ul><ul><ul><li>Statistics Canada Geography Division digital maps ( EA, DA, CT, CD, CSD , Provinces, Canada Political)‏ </li></ul></ul><ul><li>City of Toronto </li></ul><ul><ul><li>Social Policy Analysis and Research Section: Neighbourhood file </li></ul></ul><ul><ul><li>Toronto Housing Connections: Social Housing Registry </li></ul></ul><ul><ul><li>Toronto Community Housing Corporation: Social Housing Data </li></ul></ul><ul><li>City of Calgary </li></ul><ul><ul><li>Community and Neighbourhood, Social Policy and Planning Division: Neighbourhood file </li></ul></ul><ul><li>Communauté Métropolitaine de Montréal (CMM), </li></ul><ul><ul><li>Direction des Politiques et interventions de développement: Special tabulation LF-Census data, CMM framework base map , Housing data </li></ul></ul>
    10. 10. Why focus on the Risk of Homelessness? <ul><li>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 </li></ul>
    11. 11. Big Cities: QoLRS City Indicators Across Time <ul><li>Housing Starts </li></ul>
    12. 12. GraphoMap: QoLRS City Indicators Across Time 50% + Income Spent on Rent
    13. 13. City of Calgary: LICO & 30% of Income Spent on Rent
    14. 14. City of Calgary: LICO & 30% of Income Spent on Rent 30% + Income Spent on Rent LICO
    15. 15. Grand Montréal: Grand Montréal: Logements sociaux et populations ayant des difficultés financières pour se loger
    16. 16. Aging Social Housing Stock by Neighbourhood: Toronto
    17. 17. Details by Neighbourhood: Toronto
    18. 18. Community Social Data Strategy
    19. 19. Community Social Data Strategy <ul><li>CSDS is led by the Canadian Council on Social Development (CCSD) </li></ul><ul><li>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 </li></ul><ul><li>250 organizations in seventeen urban regions, including more than 50 Canadian cities and towns located in 5 provinces </li></ul><ul><li>Brings together municipal governments, social planning networks, health and family service agencies, school boards, police services, United Ways, and many others... </li></ul>Source:
    20. 20. City of Winnipeg Source: CSDS Consortium Member – Social Planning Council of Winnipeg
    21. 21. City of Hamilton Source: CSDS Consortium Member – Social Planning and Research Council of Hamilton
    22. 22. RM-Halton Geography Examples <ul><li>Report Card Partners </li></ul><ul><li>Halton Catholic District School Board </li></ul><ul><li>ROCK Reach Out Centre for Kids </li></ul><ul><li>Halton Children's Aid Society </li></ul><ul><li>Halton District School Board </li></ul><ul><li>Halton Region, Departments of Health and Social & Community Services </li></ul><ul><li>Halton Regional Police Services </li></ul><ul><li>Transitions for Youth </li></ul>Source: CSDS Consortium Members – Halton Region - Our Kids Our Community Report Card
    23. 23. RM-Halton Geography Examples Source: CSDS Consortium Member - Regional Municipality of Halton Framework Data
    24. 24. RM-Halton Geography Examples Source: CSDS Consortium Member – Community Development Halton Framework Data
    25. 25. RM-Halton Geography Examples Source: CSDS Consortium Member – Community Development Halton : Community Lens 0
    26. 26. Sault Ste. Marie Source: CSDS Consortium Member Sault Ste. Marie Innovation Centre presentation entitled 2009 United Way Donation and Socio-Demographic Maps
    27. 27. Sault Ste. Marie Source: CSDS Consortium Member Sault Ste. Marie Innovation Centre presentation entitled 2009 United Way Donation and Socio-Demographic Maps
    28. 28. Sault Ste. Marie – Census Tracts Source: CSDS Consortium Member Sault Ste. Marie Innovation Centre Community Geomatics Centre CT Framework Data Maps
    29. 29. 372 want the LF-Census back and counting...
    30. 30. Thanks! Atlas of the Risk of Homelessness: Community Data Consortium https://communitydata-donneescommunautaires.c a/ Contact: [email_address] , #TraceyLauriault,