Recent Immigrants, Earlier Immigrants and the Canadian-Born: Personal and Social Trust

3. Methodology

The World Values Survey (WVS) is a survey-based “worldwide investigation of sociocultural and political change. The longitudinal survey has been conducted by a network of social scientists at leading universities all around world” (World Values Survey 2008). Five waves of the survey have been carried out: in 1981, 1990-1991, 1995-1997, 1999-2001 and most recently in 2005-2006.

The WVS presents a national representative sample of Canadians 18 years of age and older. The core survey sample (total population N=1,765) was expanded for the second time in 2006 (first boosted in 2000) to include a larger sample of recent immigrants which allows for the comparison of the responses of recent immigrants – defined as persons not born in Canada and who have lived in the country for a period of 10 years or less – with those of earlier immigrants – persons not born in Canada who have lived in the country for more than 10 years – and those of the Canadian-born respondents. The new immigrant sample targeted new immigrants in Vancouver (N=151), Toronto (N=157), and Montreal (N=192) and supplemented the core survey [Note 4]. For each question, the reported results do not include respondents who did not, or refused to, answer the question. The core World Values Survey sample was combined with the new immigrant sample, and then the population was sorted into three groups: those born in Canada (N=1,766), recent immigrants (N=570), and earlier immigrants (N=298).

CIC has provided on-going funding to the project (including the money for the boosted immigrant sample) and has an agreement to receive some of the Canadian data prior to its public release. Since the microdata was not accessible, the statistical analyses for this report are drawn from the work of Professor Neil Nevitte, University of Toronto – Canada’s principal investigator for the World Values Survey.

This research is based on the question:

Could you tell me for each whether you trust people from this group (e.g. your family, people you know personally, your neighbourhood) completely, somewhat, not very much or not at all?

In order to see how the patterns of trust compare across the population groups, the responses (“completely”, “somewhat”, “not very much” and “not at all”) were contrasted and p-values were calculated using a chi-square test for significance. A factor analysis was used to investigate whether there is a clustering around the two theoretical dimensions of trust: personal and social. From the factors identified, two indices were created – personal trust index which is based on three indicators (trust in your family, trust in your neighbourhood and trust in people you know personally) and social trust index which is based on four indicators (trust in Canadian people in general, trust in Americans, trust in recent immigrants and trust in people you meet for the first time) in order to look at personal and social trust overall amongst the three population groups under study. Further cross-tabulations were run in order to obtain more detail about the response patterns of the three population groups. Layers were added using various socio-economic and demographic variables. The additional socio-economic and demographic variables considered were the following: sex, age groups, educational attainment, household income quartiles, occupation (major groupings), labour market status, ethnic groups (broad categories) and size of town. The cross-tabulations using occupation, labour market status, and ethnic group were not considered, because numerous cells had an insufficient number of cases.

It should be noted that in order to deal with missing data, “don’t know” and refused responses were excluded from the calculations.

Note: Factor analysis is used to uncover the latent structure of a set of variables. This type of analysis is used “when the researcher is interested in which variables in the set form coherent subsets that are relatively independent of one another. Variables that are correlated with one another but largely independent of other subsets of variables are combined into factors” (Tabachnick & Fidell 2007, 607). More specifically, a principal component analysis (with varimax rotation) was used, which simplified the interpretation of the observed variables (in this case, the levels of trust toward the seven groups of people listed in the previous paragraph).
 

Notes

  • [Note 4] Within Montreal, Toronto and Vancouver, the survey data was weighted to ensure that it accurately reflects the profile of new immigrants within that city by age and gender. The weights were calculated using the data from the 2006 Canadian Census for the Montreal, Toronto, and Vancouver census metropolitan areas.

Page details

2017-10-16