Here are the responses to some of the more frequently asked questions the CIMI team have received. If there are any additional inquiries, please feel free to contact us and get in touch with one of the CIMI team members.
How do I use the CIMI?
The CIMI can be used as an evidence-based tool to inform policy, service and program delivery as it relates to immigration and integration in Canada. While it does not offer causal evidence of the effectiveness of a particular government policy, it can provide valuable guidance for the development of policies and programs.
Generated over specific time periods, how should the CIMI rankings be interpreted?
“Based on scores reflecting geographic differences on immigrant integration outcomes, CIMI rankings have been constructed for various geographies over selected time periods (1991-1995, 1996-2000, 2001-2005, 2006-2010, 2011-).
CIMI rankings make it possible to analyze large datasets to provide valuable insights into to the process of immigrant integration in Canada. CIMI rankings are based on statistical models using socio-demographic controls in order to ensure an “apples to apples” comparison across Canadian geographies.
Rankings by geography (provinces and cities) should be interpreted with caution because differences between rankings are not equal and can be minimal in some cases. These rankings should be looked at as ranges that can enable government and civil society to improve practices in provinces and cities; even geographies with high rankings can improve their overall performance. “
What geographies are included in the CIMI?
While ensuring an appropriate sample size of immigrants, the CIMI examines 10 Canadian provinces and 33 selected cities (both Census Metropolitan Areas and Census Agglomerations). Please refer to the map on the home page to see all cities included in the CIMI.
Why is my region not represented in the CIMI?
If you do not see your city or province (or territory) represented, it is because it either has a low immigrant population or does not meet the minimum population criteria to be considered a Census Metropolitan Area (CMA) or Census Agglomeration (CA).
What is the CIMI study population?
The CIMI study population is the sub-population determined by a combination of samples from the Canadian Census and other large Canadian data sets. The sub-population varies depending on the indicator chosen. For example, the sub-population for the economic dimension cover persons of working age between 18 and 65, as reported in the Census. Please refer to our Methodology Report for an outline of all CIMI sub-populations.
What is the difference between a dimension and an indicator?
Indicators offer specific measures for each of the four dimensions of integration: Economic, Social, Civic and Democratic Participation, and Health. For example, employment status is one indicator used to measure economic integration.
How are the CIMI indicators selected?
“CIMI indicators are carefully selected on the basis of whether they are deemed a reliable measure of immigrant integration. Reliability was determined by reflecting on the key concepts of immigrant integration, the advice of our Expert Advisory Committee (EAC), and taking into account the methodological considerations that permit for immigrant/non-immigrant multivariate analysis at both the provincial and city level.
Dozens of indicators not included in the CIMI were assessed for their feasibility. As an example, after considerable reflection the EAC determined that “homeownership” could not be deemed a meaningful measure of integration for the economic dimension. The EAC concluded that successful integration does not depend on whether an immigrant owned or rented their residence. If there are any indicators of particular interest to you, please feel free to contact us.
What is the overall CIMI ranking?
The CIMI provides an overall composite ranking across all four domains for geographies (see home page), based on an average of indicator scores within each dimension across all time periods. The CIMI overall or “big” score for each of the four dimensions is calculated based on assigned weights. Please refer to our Methodology Report for further details on the weighting process.
What methodological approach was used to construct the CIMI and why?
“Multivariate regression analyses were conducted to model CIMI indicators for each of the four dimensions of immigrant integration (Economic, Social, Civic and Democratic Participation, and Health). This approach allows for a level playing field for comparing integration outcomes between Canadian immigrants and non-immigrants across geographies and over time.
Descriptive data analysis was also conducted to: 1) examine both snapshots and trends of immigrant integration outcomes over time; and 2) complement the multivariate approach when interpreting immigrant rankings.
All data has been standardized using various weighting techniques in order to ensure reliable outcomes. Various diagnostics were also conducted to ensure data quality. Please refer to our Methodology Report for further details.”
How does the CIMI compare the outcomes of immigrants to non-immigrants?
“The CIMI compares immigrant to non-immigrants in two ways: 1) by looking at various outcomes (Economic, Social, Civic and Democratic Participation, and Health-related) while adjusting for socio-demographic differences* and allowing for more equal comparisons across geographies; and 2) through the use of descriptive data to demonstrate differences between immigrants and non-immigrants per indicator (without controlling for socio-demographics), which offers snapshots of integration trends at a specific point in time.
*CIMI control variables are socio-demographic variables such as sex, age, knowledge of official languages, education, visible minority status, occupation, mobility and applicable geographies. The consistent use of such control variables across all CIMI models ensures an “apples to apples” comparison of immigrant outcomes across geographies. Self-perceived physical and mental health were the only exceptional “thematic” controls added to the models in the health dimension due to their relevance and added value. “
What data sources are used to compile the CIMI?
“The CIMI is based on national survey responses to the following Statistics Canada Public Use Micro Data Files, Master data files and customized tabulations for the following datasets: the Canadian Census (cycles 1991, 1996, 2001, 2006 and 2011); the Ethnic Diversity Survey (2003); the General Social Survey (cycles 2003, 2008 and 2013); the Canadian Community Health Survey (cycles 2000-2001, 2005, 2011-2012, 2014).
Please note that for the Canadian Community Health Survey, data cycles have been adjusted to match the CIMI time periods. Accordingly, the 2000-2001 cycle data has been included into the CIMI 1996-2000 time period. This is also the case for the 2011-2012 cycle, found in the 2006-2010 time period, and the 2014 cycle found in the 2011- time period.”
Within the economic dimension, what makes up the low income measures indicator?
Until 2011, the CIMI low income measures indicator is primarily based on the low income cut-off (LICO) variable. With additional data in the 2011 Census, the CIMI low income measures indicator is made up of the average of four low income measures: LICO; low income measure (LIM); low income measure market income (LIM-MI); and market basket measure (MBM).
Why are rankings and data missing for certain time periods?
Certain geographic and indicator rankings may be missing due to any of the following three reasons: (i) the data is not available (i.e., the survey question does not exist for that particular data cycle); (ii) the data does not have a high enough immigrant count to support provincial or city-level analyses; or (iii) the data is of poor quality and/or statistical reliability.
Why are some profiles, data and/or content duplicated for some geographies on this site?
Some geographies are amalgamated (grouped together) for certain indicators and time periods because of the way in which the data is reported by the source. This usually occurs due to small population sizes in some regions or for other statistical purposes (e.g., unreliable data in smaller geographies). This is the case in certain time periods for the Atlantic provinces, Sherbrooke-Trois-Rivières, Greater Sudbury-Thunder Bay, Regina-Saskatoon, Kelowna-Abbotsford, Moncton-Saint John, Brantford-Guelph-Barrie, as well as Kingston-Peterborough.