The Economics of Minority Language Identity
Peter S. Li
University of Saskatchewan
Commissioned by the Department of Canadian Heritage for the
Ethnocultural, Racial, Religious, and Linguistic Diversity and Identity Seminar
Halifax, Nova Scotia
November 1-2, 2001
Available on-line at www.metropolis.net
The views expressed in this paper do not necessarily reflect
those of the Department of Canadian Heritage.
1
This paper is written for the Policy-Research Seminar on Identity, Halifax,
November 1-2, 2001, under the auspices of the Multiculuralism Program, Department
of Canadian Heritage. Harley Dickinson, Li Zong and several anonymous reviewers
read a draft of this paper and provided helpful comment. The author is solely
responsible for the analysis, interpretation and views expressed in the paper.
2
Abstract
It is unclear whether ethnic identity constitutes an advantage or a disadvantage for
social mobility. The inconclusive debate largely arises from the complexity and
confusion in framing and measuring “ethic identity.” This paper focuses on a more
refined dimension of minority language identity as an aspect of ethnic minority identity,
to see how it changes and what kind of market returns it brings. Using microdata of the
1996 Census, this study finds substantial variations in the adoption of a non-official
language as mother tongue and home language, but such variations are more
pronounced among foreign-born Canadians than among the native-born. By and large,
non-official home languages and mother tongues produce net market penalties,
whereas English mother tongue or home language yields positive net returns for both
men and women. The paper suggests that the market disincentives associated with
non-official languages and the incentives associated with English mother tongue or
home language probably explain why minority language identity declines in Canada in
favour of the English language. Although the study shows that minority language
identity jeopardizes market outcomes, the debate regarding whether ethnic identity
helps or hurts social mobility cannot be resolved without further studies treating ethnic
identity as a multidimensional concept and determining how each dimension influences
economic performance.
3
Social scientists have used different approaches in defining and measuring ethnic
identity, and have come to conflicting conclusions regarding whether ethnic identity is a
resource or a penalty for social mobility in Canadian society (Isajiw, Sev’er and
Driedger, 1993; Kalbach and Kalbach, 1995). The controversy stems partly from the
complexity in capturing the multidimensionality of ethnic identity, and partly from
generalizing narrow interpretations based on different measurements of ethnicity or
ethnic identity. Nevertheless, claims about whether ethnic identity improves or retards
economic performance have serious theoretical implications. If ethnic identity
contributes to economic betterment, then economic improvement also provides the
material incentives for strengthening the preservation of ethnic identity. Conversely, if
ethnic identity produces negative economic outcomes, such outcomes serve as
penalties for maintaining a distinct ethnic identity, and its future retention, is likely to be
weakened.
Rather than trying to study ethnic identity as an all-embracing concept in order to
determine its multidimensional effects on an equally encompassing concept of social
mobility, this paper examines a more focused dimension pertaining specifically to
minority language identity in Canadian society. The purpose is to determine the extent
to which non-official languages are being adopted as mother tongue and home
language, and to examine the economic value of minority language identity in the
labour market. To the extent that non-official language identity provides positive market
returns, such returns can be seen as providing incentives for its maintenance in the
home setting. Conversely, earning penalties of non-official language identity can be
interpreted as disincentives that discourage its being preserved as mother tongue or
home language. In this way, the market value of non-official languages provides an
economic basis for strengthening or weakening minority language identity. Studying
the economic returns of minority language identity consequently represents one way of
assessing whether a specific component of ethnic identity helps or hurts labour market
performance. In turn, the economic value of minority language identity provides a basis
for understanding why minority language identity prospers or declines over time in
Canadian society.
Ethnicity, Ethnic Identity and Minority Language Identity
The term “ethnicity” comes from the Greek word ethnikos, the adjective of ethnos,
which means heathen nations or peoples not converted to Christianity. In the
contemporary context, “ethnicity” is often used to designate the notion of a people of a
similar heritage, the members of which have a sense of common origins and share
some experiences of life, past and present (Cashmore, 1984:85-90). Thus, the concept
of ethnicity implies an identity or a sentiment of likeness based on descent, language,
religion, tradition, and other common experiences (Weber, 1968:385-398).
The internationalization of capital and labour under capitalism has greatly fractured the
solidarity of ethnic identity that used to correspond more closely to nations and
peoples. At the same time, increased international migration as a part of the trend of
4
globalization has resulted in people moving across nation-states in large numbers; in
doing so, destination societies have seen hybrids of ethnic identities emerge, often
reflecting the exigencies of contemporary life and only nominally the endurance of
cultural traditions (Yancey, Ericksen and Juliani, 1976). Today, modern states are likely
to be polyethnic in the sense that many ethnic groups can be found within the same
nation-state (Driedger, 1996:2-3; Kymlicka, 1995:11-26). As well, these states are
witnessing what Krotki and Odynak (1990:415) call “the emergence of multiethnicities,”
that is, the mixing of origins of people.
In an immigrant society such as Canada, there is no simple and direct correspondence
between “ethnicity” and “ethnic identity.” A common ethnic label does not automatically
imply a common identity because members of an ethnic origin are likely to have
originated from many backgrounds and are exposed to different life experiences based
on social class, gender, and other social features (Li, 1999:164-170). The end result is
that there can be many identities even within the same ethnic group, with overlapping
cultural and behavioural features. Thus, individual or group differences in attachment to
various linguistic, social and cultural components that delineate ethnic identity may
reflect less the robustness of common past traditions than the viability of present
conditions that nourish or stifle such components.
Ethnic identities, as Jenkins (1994:218) puts it, “are practical accomplishments rather
than static forms.” However, the conventional theoretical approach to ethnic identity
tends to stress the collective internal definitions of distinctiveness at the expense of
external definition and categorization (Jenkins, 1994). Ethnic identity cannot simply be
a product of individual or group choices premised upon ascription and traditions, since
unequal power relations exert substantial external pressures in the social construction
of ethnic identity (Jenkins, 1994). As Gans (1997:882) points out, the retention and
resurgence of ethnic identity can also be reactions to events in the larger society. Thus,
the undue emphasis of ethnic identity as adherence to cultural tradition and internal
solidarity has meant that external conditions and market forces are often overlooked as
important sources in shaping ethnic identity.
Studies of ethnic identity are further complicated by the fact that there are substantial
differences in how “ethnic identity” is framed and measured. For example, the debate
over Porter’s Vertical Mosaic Thesis regarding whether ethnic affiliation determines the
occupational opportunity in Canada is in fact premised upon the narrow empirical
question of whether ethnic categories as indicated in Canadian censuses are related to
the occupational distribution, and whether such a statistical association increases or
decreases in strength over different censuses (Porter, 1965; Darroch, 1979; Lautard
and Loree, 1984; Lautard and Guppy, 1999). While these studies may have
implications on the theoretical debate about ethnic identity and social mobility, such
implications can only be extrapolated, not inferred.
Since “ethnic identity” encompasses many elements and since there is no consensus in
adopting a universal set of dimensions in studying “ethnic identity,” there are substantial
variations in theorizing the concept of ethnic identity (see Cornell and Hartmann, 1998:
5
153-194; Gans, 1997; Hutnik, 1986; Jenkins, 1994; Tilley, 1997), as well as its
measurement (see Isajiw, 1974; Driedger, 1996:129-151; Kalin and Berry, 1995;
Statistics Canada and US Bureau of the Census, 1993). Consequently, conclusions
regarding “ethnic identity” are influenced by different elements being included or
excluded in mapping out the composite concept. For example, a study of ethnic identity
and social mobility among four European groups in Toronto used four dimensions to
measure ethnic attachments to one’s ethnic community, and found a small but
significant correlation between the external/cultural dimension of ethnic identity and
social mobility in several tests (Isajiw, Sev’er and Driedger, 1993). The external/cultural
dimension includes items which mainly measure ethnic language use and preference of
ethnic food and ethnic media, while social mobility is constructed from occupational and
educational differences between the respondent and his/her father (Isajiw, Sev’er and
Driedger, 1993). The authors concluded that ethnic identity can be as much a resource
as a drawback to social mobility (Isajiw, Sev’er and Driedger, 1993).
Kalbach and Kalbach (1995) analyzed data from the 1981 and 1991 Census to see if
socio-economic status is related to what they call “ethnic connectedness” or “ethnic
identity,” as measured by the proportion of an ethno-religious group reporting the use of
an ethnic language at home. They concluded that “individuals in the more traditional
ethno-religious groups, who exhibit their greater ethnic commitment or connectedness
through greater use of their ethnic language in the home, tend to report lower levels of
educational and economic status attainment than those who are less ethnically
connected…” and that among immigrants in particular, those who are more ethnically
connected tend to be more disadvantaged (Kalbach and Kalbach, 1995: 31).
In another study, Pendakur and Pendakur (forthcoming) used the detailed microdata file
of the 1991 Census to examine the returns of official languages and non-official
languages, and found that while official language ability brings positive market returns,
knowledge of non-official languages rarely improves and in fact penalizes labour market
outcomes. It is difficult to extrapolate from the study whether knowledge of non-official
languages can be equated with ethnic identity since, as the authors pointed out,
individuals may be endowed with a non-official language as mother tongue, or may
acquire such language ability in later socialization. Nevertheless, the study by Pendakur
and Pendakur (forthcoming) casts serious doubts on the general conclusion regarding
the positive effects of ethnic identity on market performance.
The present analysis assesses the economic value of minority language identity using
the 1996 Census in order to better understand the retention or demise of minority
languages. Minority language identity is defined as the adoption of a non-official
language as mother tongue or home language. This is not to say that those who adopt a
non-official language as mother tongue or home language would necessarily have a
strong sense of belonging to one’s ethnic group. However, it is clear that the retention of
a minority language as mother tongue or home language constitutes an added
component in the construction of ethnic minority identity, and that people who retain
such a mother tongue or home language have a stronger linguistic capacity to link
themselves with their ethnic community than others who do not retain such language.
6
Since the adoption of a minority language as mother tongue or home language
represents an ethnic endowment and an ethnic language choice respectively, it can be
described as a phenomenon of minority language identity.
Data and Method
The analysis uses the 1996 Census to see the extent to which non-official languages
are being adopted as mother tongue and home language among immigrants and nativeborn Canadians of various ethnic origins. The market value of minority languages is
then assessed in terms of the returns of non-official languages as mother tongue and
home language, while controlling for variations in other individual and labour market
features.
This analysis is based on the Public Use Microdata File on Individuals of the 1996
Census of Canada, which is a 2.8 per cent probability sample of the population
enumerated in the census. The file contains 792,448 records of individuals.1 For the
purpose of this analysis, only permanent residents of Canada, including landed
immigrants and native-born Canadians, are included.2 A further restriction is applied to
the analysis of the market value of mother tongue and home language. Those who were
less than 15 years of age and those who did not work in 1995, as well as those with no
wages, salaries or self-employment income are excluded. The resulting file has 401,653
cases, including 215,839 men and 185,814 women, at least 15 years of age, who
worked in 1995 and had an earning from employment or self-employment.
The dependent variable is "annual earnings from employment and self-employment,”
which is the sum of gross wages and salaries, and net self-employment income before
paying individual income taxes. Statistics Canada applies upper and lower limits to
individual earnings to ensure confidentiality.3 Wages and salaries are always positive,
but net self-employment income can have a negative value. Earnings from employment
and self-employment are used here to indicate labour market outcomes, and some
individuals had earnings from both sources. Actual earnings are retained for easy
interpretation.
The independent variables measuring individual variations in human capital and workrelated features include: years of schooling, experience estimated by subtracting from
age the years of schooling and the six years before schooling began, experience
squared, knowledge of the official languages, mother tongue or home language, the
number of weeks worked in 1995 (1 to 52), the nature of work in terms of whether the
weeks worked were full-time or part-time,4 occupation (14 categories),5 and the industry
of work (14 categories).6 In addition, a variable—“years since landing in Canada”—is
used as a proxy of Canadian experience for immigrants. The variable is measured as
the number of years since an immigrant has immigrated to Canada, and native-born
Canadians are coded as 0. The "years of schooling" is constructed from several
variables. For individuals with post-secondary education, the variable “years of
schooling” is the sum of years of university or non-university education, whichever is
higher, and 12 years of elementary and secondary grades. For those with secondary
7
school graduation certificate, it is coded as 12. For those with less than secondary
school graduation certificate, the highest grade coded is 11 even though higher
completed grades may have been reported. Individuals with only "grade 5-8" education
are coded as having an average of 6.5 years of schooling, and those with "less than
grade 5,” an average of 2 years of schooling. In addition, two other variables measuring
the characteristics of the local market are used in the analysis; they pertain to the
unemployment rate and the percentage of immigrant population in the CMA as
calculated from the 1996 census microdata file.
The inclusion of occupation and industry of work as independent variables reduces the
magnitude of income differences that can be attributed to language ability and language
identity. Indeed, language capacity and identity can be seen as exogenous factors that
determine the type of industry in which a person works and the type of job a person
holds. In turn, the job type and industry of work affect the level of earnings. Thus,
earning differences, associated with language characteristics after variations in industry
of work and job type, are taken into account and may be seen as direct net effects of
language characteristics on earnings, as opposed to their indirect effects on earnings
which operate via the influence of job type and industry of work. In other words, the
inclusion of occupation and industry creates a more restrictive condition for assessing
the impact of language characteristics on earnings.
Multiple Classification Analysis (Andrews et al., 1976) is used to analyze the gross and
net differences in earnings which can be attributed to language abilities, including
mother tongue or home language and knowledge of the official languages. The
statistical procedure is essentially a least-squares solution which treats the dependent
variable as a linear combination of a set of categorical and interval variables. For each
interval variable in the equation, Multiple Classification Analysis calculates the
unstandardized multiple regression coefficient; for categorical variables, it produces a
regression coefficient for each category and expresses it as a deviation from the grand
mean of the dependent variable. The gross deviations measure the effects when
variations in other independent variables have not been adjusted; the net deviations are
effects when inter-group variations in other independent variables have been taken into
account.
Patterns of Minority Language Identity
The extent to which Canadians adopt a non-official language as mother tongue or home
language reflects the linguistic diversity in Canada as well as the degree of commitment
or identity towards non-official languages. Findings from previous Canadian censuses
indicate that (1) linguistic diversity in Canada has increased in more recent censuses
largely as a result of more immigrants coming to Canada from diverse cultural and
linguistic backgrounds; and that (2) the pull towards adopting English as mother tongue
and home language has been strong over time. For example, Richmond and Kalbach
(1980: 435) showed from the data of the 1971 Census that more recent immigrants
were more likely to speak a home language similar to their mother tongue, but as
succeeding cohorts of immigrants increased their period of residence in Canada, there
8
was a corresponding increase in the use of English as home language by those whose
mother tongue was not English. Also using the 1971 Census, de Vries and Vallee
(1980: 109) found that there was a strong tendency for those not of British or French
origin to shift to English mother tongue, especially among those born in Canada. An
analysis of language data of the 1986 Census also indicates that Canada’s linguistic
diversity, most notable in metropolitan centres, has been increasing as a result of
changing immigration patterns, but at the same time, there has been a strong pressure
to convert to English mother tongue and home language (Bourbeau, 1989).
Data from the 1996 Census reveal that there is substantial linguistic diversity among
foreign-born Canadians, in terms of adopting a non-official language as mother tongue
or home language; however, this diversity declines dramatically among native-born
Canadians. In other words, a large proportion of those born outside of Canada adopts a
mother tongue or home language other than English or French, but this pattern is not
sustained among those born in Canada. For example, those with a non-official language
mother tongue account for 67 per cent of foreign-born Canadians, while those with a
non-official home language account for 45 per cent (Table 1).
9
Table 1
Non-Official Language Mother Tongue and Home Language of Racial and Ethnic Groups, Canada,
1996 Census
Foreign Born
Non-official Languages
Mother
Home
Tongue
Language
%
%
1,0
0,2
1,9
0,8
90,0
11,6
89,5
25,9
72,4
17,8
93,6
43,3
95,2
69,8
91,7
56,3
96,3
65,4
96,5
70,5
94,8
59,8
94,0
64,2
91,3
51,6
63,6
33,4
87,9
38,6
9,6
4,0
35,4
13,1
3,4
1,2
71,5
37,8
13,7
5,8
703 800
59 436
118 944
213 444
36 504
51 012
155 160
42 804
108 000
73 332
330 372
158 472
17 388
62 640
166 896
118 656
30 168
36 288
260 028
27 396
Visible Minorities
Arab
West Asian
South Asian
Chinese
Filipino
Vietnamese
Other East/South East Asian
Latin/Central/South American
Black
Other single & multiple origins
97 380
56 628
458 172
633 996
155 772
81 360
87 408
76 464
314 928
213 624
91,5
94,5
76,1
94,1
88,1
94,2
91,4
93,7
30,0
66,0
67,4
74,8
61,3
84,2
62,3
86,8
72,6
75,9
19,9
47,7
28 548
8 784
188 496
205 272
37 476
20 772
48 960
15 660
246 708
121 248
59,5
78,3
51,7
57,9
23,7
80,9
47,4
77,2
5,3
27,0
42,9
66,8
40,4
38,1
17,4
73,5
23,8
67,8
4,8
20,2
5 364
12,1
7,4
782 676
26,1
18,3
66,8
45,1
23 412 456
6,2
2,8
Total
4 951 836
Number
Non-official Languages
Mother
Home
Tongue
Language
%
%
0,1
0,1
0,1
0,1
13,5
2,1
27,0
7,8
18,0
6,5
39,9
5,9
42,6
14,3
37,0
4,8
56,1
21,7
67,9
37,0
44,9
11,9
60,9
31,5
55,2
33,9
9,5
3,2
24,0
3,7
0,7
0,2
1,4
0,5
0,2
0,1
10,1
3,1
0,5
0,3
Racial and Ethnic Groups
Not Visible Minorities
British, British Isles, British and Canadian
French, French and Canadian
Dutch
German
Other West European
Hungarian
Polish
Ukrainian
Balkan
Greek
Italian
Portugal
Spanish
Jewish
Other European
Other British multiple origins
Other French multiple origins
British & French, British & French & other
Other single & multiple origins
Canadian
Aboriginal People
Number
Native Born
5 295 276
3 208 896
180 936
506 340
45 756
41 724
103 680
283 392
51 840
68 580
385 344
80 568
7 956
128 916
219 528
2 508 444
441 792
1 645 344
1 274 148
5 229 396
Source: Calculated from Statistics Canada, 1996 Census of Canada, Public Use Microdata File on Individuals.
The numbers have been weighted to population size.
10
However, only 6.2 per cent of native-born Canadians speak a non-official language
mother tongue and only 2.8 per cent speak a home language other than English or
French.
Comparing foreign-born Canadians to native-born Canadians, the decline in percentage
of people with a non-official language mother tongue or home language for the same
ethnic group may be viewed as the rate of loss of minority language identity. Table 1
shows that the loss of minority language identity is more severe among those not of
visible minority origins, and less so among those of visible minority origin. For example,
26 per cent of those of German origin born outside of Canada, compared with only 7.8
per cent of the same origin born in Canada, adopt a home language other than English
or French. The rate of minority language loss in home language for those of Italian
origin is from 60 per cent among those born outside of Canada to 12 per cent among
those native born. In contrast, the decline is from 67 per cent among foreign-born Arab
Canadians to 43 per cent among native-born Arab Canadians, and from 84 per cent
foreign-born Chinese Canadians to 38 per cent native-born Chinese Canadians. These
differences partly reflect the changing patterns of immigration.
Since Europeans have been immigrating to Canada for a longer period of time due to
the past bias in favour of European immigration, and since immigrants from Asia, Africa
and other non-European source countries only began to enter Canada in large numbers
beginning in the late 1960s, there is a difference in the duration in Canada for European
Canadians and for visible minority Canadians. Thus, native-born Canadians of
European origin are more likely to have been in Canada for several generations than
native-born visible minorities. Consequently, there is a longer timeframe for non-English
and non-French speaking European Canadians to lose their ethnic language identity
and to convert to official languages than for visible minority Canadians. These
differences would explain why the rate of minority language identity loss varies
substantially among Canadians of different origins. No doubt, there are also other
differences in ethnic groups in that some groups have developed a stronger sense of
distinct community in enabling their members to preserve their identity. However,
differences in these factors are insufficient to explain why, over time, all non-official
language groups tend to lose the ethnic language and convert to official languages.
Market Value of Official Language and Minority Language Identity
Why official languages in Canada—especially the English language—have such a
strong pull in attracting newcomers to convert to them over time can perhaps be
explained by the definite labour market returns (Beaujot, Basavarajappa and Verma,
1988; Shapiro and Stelcner, 1997) that the ability to speak official languages yields. In
contrast, knowledge of non-official languages has been shown to carry an income
penalty, based on an analysis of the 1991 Census (Pendakur and Pendakur,
forthcoming).
Table 2 calculates the market returns of “knowledge of the official languages” as well as
“mother tongue,” based on the 1996 Census. The data show that for male and female
11
Canadians, there are positive returns associated with bilingualism in English and
French, and with unilingualism in English. However, there are penalties for those who
speak only French, and even greater penalties for those who speak neither official
language. When variations in schooling, experience, job characteristics, nativity, years
of residence in Canada, and labour market features are taken into account, male
Table 2
Gross and Net Effects of Official Language Knowledge, and Mother Tongue, on Earnings,
Canada, 1996 Census
Male
Gross
Net
Number
Effects
Effects
(Deviation from Mean
Earning of $31,792)
Knowledge of official languages:
English only
147,123
French only
23,074
Both English and French
44,377
Neither English nor French
1,265
Mother Tongue:
English single response
129,954
French single response
49,880
English and French
636
Aboriginal languages
1,049
German
3,382
Netherlandic languages
1,241
Italian
4,181
Spanish
1,457
Portuguese
1,788
Polish
1,503
Ukrainian
916
Greek
1,089
Chinese
4,594
Austro-Asiatic languages
864
Arabic
1,028
Punjabi
1,486
Other Indo-Iranian languages
1,632
Other non-official languages
8,766
Other non-official languages
393
(Atlantic & Territories only)
Source: Appendix 1
Female
Gross
Net
Number
Effects
Effects
(Deviation from Mean
Earning of $20,400)
462
-5,959
1,922
-12,436
-199
-1,101
1,278
-1,621
124,673
21,110
38,715
1,316
161
-2,906
1,327
-7,668
-118
-668
774
-831
1,166
-1,423
-3,904
-14,231
2,842
5,730
2,728
-6,369
-2,830
-490
2,204
-7,950
-4,699
-7,435
-4,276
-6,859
-3,811
-2,330
-918
911
-807
-1,488
-1,943
-1,385
-1,811
-833
-1,271
838
-1,137
-2,965
-4,995
-3,747
-2,835
-1,895
-754
-2,703
-3,094
-523
114,440
42,109
562
761
2,609
937
3,123
1,171
1,408
1,330
819
847
4,302
587
477
1,218
1,085
7,763
266
307
-328
-798
-4,139
565
168
2,036
-3,878
-1,837
-244
2,267
-1,844
-393
-4,271
-2,014
-6,032
-2,330
-424
-1,025
267
-236
-847
-93
-366
-730
-223
-1,423
450
-993
-541
-858
-766
-750
760
-1,142
-1,910
-995
1,429
12
Canadians who only speak English earn about $199 below the average ($31,792)
yearly, as compared to those who speak only French earning $1,101 below the
average. Bilingual male Canadians have a definite income advantage, but those who
speak neither official language suffer the largest income penalty. The pattern is
essentially the same for female Canadians, although the magnitudes of income
difference that can be attributed to knowledge of official languages tend to be smaller.
The effect of the mother tongue on earnings is unequivocal. For males, those who
speak English as mother tongue have a definite earning advantage, and this advantage
is maintained in the magnitude of $911 above the mean even after controlling for other
variables. However, those who speak French as mother tongue and those who speak
English and French as mother tongues suffer an income disadvantage. Most male
speakers of mother tongues in non-official languages also suffer an earning penalty,
except those who speak German, Netherlandic languages, and Italian. However, even
male speakers of these mother tongues have an earning disadvantage when variations
in other factors have been taken into account. The only speakers of a non-official
mother tongue who do not suffer an income penalty are those who speak Portuguese
as mother tongue, and their net earnings remain $838 above the average every year.
Among the speakers of non-official mother tongues, those who speak Greek suffer the
most, followed by Chinese, then by Ukrainian and by other Indo-Iranian languages.
For female Canadians, the income advantage of those who speak English as mother
tongue is also maintained after variations in other factors are taken into account, but
their advantage tends to be smaller than their male counterparts. Similarly, the income
penalty for those female Canadians who speak French only, or both French and English
as mother tongue tends to be smaller than their male counterparts. Like male
Canadians, all female speakers of a non-official language as mother tongue suffer an
income penalty, except for those who speak an Arabic mother tongue, and those who
speak a Portuguese mother tongue.7 The magnitudes of earning disparity among those
who speak a non-official language as mother tongue tend to be smaller among females
than among males. Women who speak Spanish as mother tongue suffer the most, with
earnings approximately $1,423 below the average ($20,400) yearly. Women who speak
Polish or Greek as mother tongue suffer a penalty of $993 and $858 respectively.
The data on official languages and mother tongue indicate that those who speak the
official languages have an income advantage than those who don’t. When all the
mother tongues are considered with other variables, English mother tongue has an
income advantage for both male and female Canadians, whereas speakers of most
non-official mother tongue suffer a net income penalty.
When the effect of home language is considered with knowledge to speak the official
languages and other variables, the data show that men and women who speak both
official languages have a net yearly income gain that is above the average, while those
who speak only English have a nominal income disadvantage marginally below the
mean (Table 3). Male Canadians who only know French suffer the most net earning
disadvantage, about $1,066 a year below the mean, whereas those who speak neither
13
official languages suffer a net income penalty of $781 a year. For female Canadians,
the pattern is much the same, with those unilingual in French suffering the largest
income disadvantage, followed by those who speak neither official language.
Table 3
Gross and Net Effects of Official Language Knowledge, and Home Language, on Earnings,
Canada, 1996 Census
Male
Gross
Net
Number
Effects
Effects
(Deviation from Mean
Earning of $31,792)
Knowledge of official languages:
English only
147,123
French only
23,074
Both English and French
44,377
Neither English nor French
1,265
Home Language:
English single response
148,968
French single response
47,354
English and French
751
Aboriginal languages
610
German
511
Italian
1,233
Spanish
849
Portuguese
940
Polish
829
Chinese
3,578
Austro-Asiatic languages
711
Arabic
490
Punjabi
1,064
Other Indo-Iranian languages
888
Other non-official languages
6,897
Other non-official languages
166
(Atlantic & Territories only)
Source: Appendix 2
Female
Gross
Net
Number
Effects
Effects
(Deviation from Mean
Earning of $20,400)
462
-5,959
1,922
-12,436
-184
-1,066
1,187
-781
124,673
21,110
38,715
1,316
161
-2,906
1,327
-7,668
-98
-728
720
-272
1,467
-1,740
-1,957
-16,095
-6,762
-4,235
8,968
-4,330
4,913
-6,856
-7,496
-11,741
-8,939
-7,443
-6,926
-5,788
776
-944
-2,198
-1,837
-2,914
-2,851
-3,612
-1,611
-3,242
-5,702
-4,206
-7,351
-1,784
-4,660
-3,737
-791
130,512
39,633
737
387
351
887
647
647
704
3,243
479
237
874
575
5,786
115
558
-543
1,425
-6,000
-3,602
-1,900
-5,346
-4,052
-3,763
-2,184
-4,454
-5,670
-7,332
-4,654
-3,146
-4,951
247
-133
-533
486
610
-786
-1,666
15
-2,619
-2,851
-1,673
-2,883
-1,241
-1,884
-1,809
289
14
The pattern of returns associated with home language is similar to that associated with
mother tongue. Male Canadians who speak English as home language have a net
income advantage of about $776 a year. Male speakers of all other languages suffer a
net income penalty. The penalty is most severe for speakers of Chinese home language
(-$5,702), followed by other Indo-Iranian languages (-$4,660), then Austro-Asiatic
languages (-$4,206), and then by Spanish (-$3,612).
Female speakers of English home language also maintained a net income advantage
similar to their male counterparts, but the gain is only $247 a year. Most female
speakers of a non-official home language also suffer a net income penalty, except for
those who speak Aboriginal languages, German, and Portuguese. Again it is not clear
why female speakers of these languages do not suffer an income penalty like their male
counterparts. But in general the income disparity among female Canadians tends to be
much smaller.
The data on home language also show that English home language carries a definite
market advantage, whereas most speakers of a non-official home language suffer an
income penalty. The penalty tends to be particularly severe for male speakers of
Chinese and other Asian languages.
Implications of Market Disincentives on Minority Language Retention
The analysis of the 1996 Census pertaining to mother tongue and home language
confirms a general finding. The adoption of a non-official language as mother tongue or
home language brings no earning advantage, but rather a net income penalty (except
for a few language groups among women), whereas having English as mother tongue
or home language yields a consistent income gain for both men and women. Pendakur
and Pendakur (forthcoming) found a similar pattern when they analyzed the ability to
speak official languages and non-official languages, using the 1991 Census. They
concluded that non-official language knowledge rarely improves labour market outcome.
They also suspected that the ability to speak non-official languages is closely
associated with immigrant communities and such penalties may not necessarily reflect
returns to non-official languages but rather penalties for other cultural features.
The present analysis finds that people who adhere to a non-English mother tongue or
home language suffer an earning penalty. It does not really matter whether the income
disadvantage is reflecting the true value of non-official languages or what non-official
languages symbolize. As far as speakers of non-official mother tongue or home
language are concerned, there are negative returns attributed to non-official languages
or to features associated with non-official languages. Examples of such features include
a foreign accent, a foreign image, and in some instances, a foreign (non-white) race.
These features often associate with non-official mother tongue and home language to
serve as social markers in discounting the earnings of those identified with such
unfavourable characteristics.
15
Over time, as most non-official language mother tongues and home languages are
repeatedly paired with income penalties, speakers of minority languages learn to
dissociate themselves with such “foreign” languages and with characteristics associated
with such languages. In short, the market disincentives to non-official mother tongue
and home language serve to discourage the retention of minority languages. At the
same time, the rewards of the English language in the labour market become incentives
to encourage Canadians, especially immigrants and their children, to convert to English
as mother tongue and home language. Thus, the combination of market disincentives
associated with non-official languages and the net income advantage of English mother
tongue and home language probably explains why minority language identity declines
dramatically over time, especially among native-born Canadians.
Conclusion
The literature is inconclusive about whether ethnic identity is a resource or a penalty for
social mobility. The unresolved debate has to do with the complexity in conceptualizing
and measuring ethnic identity. Studies differ in conclusions largely because there is a
lack of consensus regarding how ethnic identity should be framed and gauged.
This study examines the use of minority languages as an aspect of ethnic minority
identity, to see how such language use varies, and whether minority languages carry
differential returns in the labour market. Minority language identity is only one
component of ethnic minority identity. However, it is clear that ethnic minority members
who adopt a language similar to their origin as mother tongue or home language have a
greater linguistic capacity in maintaining a sense of attachment to their ethnic group
than those who do not adopt such a language as mother tongue or home language. At
the very least, the study of non-official mother tongues and home languages yields a
more refined approach to assessing the relationship between minority language identity
and labour market returns.
The analysis of the 1996 Census shows that there is a substantial variation in linguistic
diversity in Canada, in terms of Canadians adopting a non-official language as mother
tongue or home language, although such diversity tends to be much stronger among
foreign-born Canadians than native-born Canadians. The decline of non-official
languages as mother tongue or home language among native-born Canadians,
compared to those born outside the country, is an indication that over time, there is a
loss of minority language identity in Canada. Neither demographic configuration
associated with the immigration pattern nor cultural variations of ethnic groups is
sufficient to explain why minority language identity systematically declines over time.
The analysis of the market returns of official languages and non-official mother tongue
or home language indicates that those who have knowledge of the official languages
have an income advantage over those who do not have such knowledge, and that
English mother tongue or home language yields an income gain for both men and
women when variations in other factors have been taken into account. In contrast, most
non-official language mother tongues or home languages result in a net earning penalty;
16
the negative returns vary depending on the language, however, and depending on the
gender. In general, the income disadvantage tends to be larger for male speakers of
non-official languages than for their female counterparts.
The prevailing pattern of net income disadvantage associated with non-official mother
tongue or home language means that there are substantial market disincentives that
can be attributed to non-official languages. At the same time, the net income gain
associated with English tongue or home language serves as incentives to attract nonEnglish speakers to convert to English mother tongue or home language. Over time,
these market disincentives and incentives probably encourage Canadians to abandon
non-official languages as mother tongue and home language in favour of the English
language. These market forces would explain why linguistic diversity is a social feature
associated mainly with the immigrant population and why there is a substantial decline
in minority language identity among native-born Canadians.
The analysis in the paper merely shows that different market values are associated with
minority languages and the official languages, and further research is need to
empirically establish the causal relationship between market value and minority
language loss. The analysis strongly suggests that market forces probably play an
important role in the maintenance or loss of minority language identity. However,
cultural and social variations among ethnic groups probably also influence the rate of
minority language decline.8 In the long run, it is doubtful that cultural factors alone would
succeed in slowing down or reversing the process of minority language identity loss.
Naturally, minority language identity represents only one component of ethnic minority
identity. It is possible that despite the decline of minority language identity, there can be
revivals of other aspects of ethnic identity, perhaps more of a symbolic nature as
suggested by Gans (1979). But as far as language diversity in Canada is concerned, it
appears that there is not much economic basis to sustain it beyond the first generation
of immigrants; conversely, there are sufficient market conditions in favour of the English
language.
Regarding the debate about the effect of ethnic identity on social mobility, the present
analysis merely suggests that minority language identity, as an aspect of ethnic minority
identity, jeopardizes economic performance in the Canadian labour market. Whether
other dimensions of ethnic identity produce similar market outcomes cannot be
ascertained in this study. Too little is known at the present time about how different
aspects of ethnic identity affect economic performance. Until more is known about
ethnic identity as a multidimensional concept and about how its various dimensions
influence market outcomes, claims regarding whether ethnic identity helps or hurts
social mobility can only be partial and tentative.
17
Endnotes
1
The target population in the 1996 Census includes native-born Canadian citizens, landed
immigrants and non-permanent residents who, on Census Day, were residing in a private
dwelling in Canada. Institutional residents and residents of 77 incompletely enumerated
Indian reserves were not included. However, the 1996 Census, like the 1991 Census, includes
non-permanent residents in Canada, who are defined as persons who held a student or
employment authorization, Minister’s permit, or who were refugee claimants, as well as
family members living with them at the time the census was taken (Statistics Canada, 1996).
2
The 1996 Public Use Sample File on Individuals contains records of 4,498 non-permanent
residents, which made up 0.6 per cent of the total sample. In the 1996 census population,
there were 166,715 non-permanent residents, or 0.6 per cent of the total population (Statistics
Canada, 1996).
3
Positive or negatives limits were applied to 837 individuals with wages and salaries and to
403 individuals with self-employment income in the census microdata. Assuming these were
unique individuals, they made up at most 0.3 per cent of the labour force in the sample
(Statistics Canada, 1996, Table 7).
4
"Full-time" refers to those who worked mainly full-time weeks in 1995, and "part-time"
refers to those who worked mainly part-time weeks in 1995. A full-time week involves
working 30 hours or more in one week (Statistics Canada, 1996).
5
The microdata file of the 1996 Census provides two occupational classifications, based on
the 1991 Standard Occupational Classification (25 categories) and on the National
Occupational Classification (14 categories) developed by Statistics Canada and Human
Resources Development Canada. The former takes into account industrial sectors in addition
to using education, training, skill level, duties and responsibilities of work as bases of
classification, whereas the latter mainly relies upon education, training, skill level, duties and
responsibilities of work and does not make distinctions about the industry of work. Since this
analysis also uses the variable “industry of work,” the National Occupational Classification
of occupation is used to avoid the overlap between the variables “occupation” and “industry.”
6
The microdata file of the 1996 Census uses the 1980 Standard Industrial Classification to
produce 16 classifications. In this analysis, agriculture and other primary industries are
collapsed, and federal and other government services are also recoded into one group.
7
It is not clear why women who speak a Portuguese mother tongue and women who speak an
Arabic mother tongue do not suffer an income disadvantage like other speakers of minority
languages. The data on these two groups do not change the fact that most speakers of a
minority language tend to suffer an income penalty.
8
Many factors beside market forces, would influence the rate of minority language decline or
retention. For example, ethnic groups which emphasize family ties and disciplined
socialization would have a strong influence on their children in inciting them to learn and to
18
use their ethnic language at home. However, Gans (1997: 879) suggests distinguishing
between involuntary and voluntary ethnic language retention, and treating involuntary
retention as a measurement of family obligations and not ethnic identity. Whether it is out of
obligation or commitment, family influences would affect the ability of children to retain
their ethnic language.
19
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22
Appendix 1
Gr oss and Net E ffects of Ethnic Origin, Official Language Ability, and Mother Tongue on E arnings,
Canada, 1996 Census
Male
Gros s
Net
Number Earnings Earnings
($, Deviation from
Mean)
Female
Gros s
Net
Number Earnings Earnings
($, Deviation from
Mean)
F-Tes t
Rac ial and E thnic Groups :
Not V is ible Minorities
Britis h, B ritis h Is les , Britis h & Canadian
Frenc h, Frenc h and Canadian
Dutc h
German
Other W es t European
Hungarian
Polis h
Ukrainian
Balkan
Greek
Italian
Portugues e
Spanis h
J ewis h
Other E uropean
Other B ritis h multiple origins
Other Frenc h multiple origins
Britis h & Frenc h, Britis h & Frenc h & other
Other s ingle & multiple origins
Canadian
49
25
2
6
2
2
1
1
6
2
1
3
19
3
11
12
38
633
957
837
263
747
820
007
637
301
314
178
039
218
481
240
082
517
228
228
297
3 873
16
2 874
1 791
3 750
1 081
514
3 036
-241
-7 100
1 837
-3 543
-117
18 249
3 071
249
184
-1 325
1 671
-2 623
788
380
203
-357
348
-691
-778
280
751
-1 382
-693
-647
-664
8 738
708
607
576
263
728
-243
-1
-4
-2
-2
-2
-2
-1
-3
-5
Vis ible Minorities
Arab
Wes t A s ian
South A s ian
Chines e
Filipino
Vietnames e
Other E as t/South E as t As ian
Latin/Central/S outh Americ an
Blac k
895
463
4 709
5 510
1 275
706
980
612
3 305
-5
-9
-3
-4
-7
-6
-2
-10
-8
Aboriginal P eople
4 209
-11 878
838
271
942
177
698
820
420
740
166
F-Tes t
41
21
2
4
960
077
170
794
522
567
671
220
040
983
809
592
158
240
457
760
422
565
042
659
1 664
678
-819
66
1 747
1 821
387
1 591
-201
-1 733
1 613
-2 150
1 537
7 297
2 244
-214
-38
-223
334
-1 777
83
374
-409
-133
248
279
720
56
-87
-579
-271
-927
516
2 789
917
131
-21
47
164
-203
450
271
3 618
5 113
1 901
488
870
460
3 353
-3 425
-3 720
-2 561
-57
-950
-3 558
-172
-5 865
-1 295
-1 261
1 008
-183
59
-255
-473
796
-271
-1 451
3 629
-5 279
-1 522
673
110
715
316
161
-2 906
1 327
-7 668
-118
-668
774
-831
114 440
42 109
562
761
2 609
937
3 123
1 171
307
-328
-798
-4 139
565
168
2 036
-3 878
267
-236
-847
-93
-366
-730
-223
-1 423
1
2
1
4
1
1
2
18
3
11
11
31
261
558
164
313
817
567
505
160
087
-3 067
22*
Knowledge of offic ial languages :
Englis h only
Frenc h only
Both E nglis h and Frenc h
Neither E nglis h nor Frenc h
147
23
44
1
Mother T ongue:
Englis h s ingle res pons e
Frenc h s ingle res pons e
Englis h and Frenc h
Aboriginal languages
German
Netherlandic languages
Italian
Spanis h
129 954
49 880
636
1 049
3 382
1 241
4 181
1 457
123
074
377
265
462
-5 959
1 922
-12 436
-199
-1 101
1 278
-1 621
1
-1
-3
-14
2
5
2
-6
911
-807
-1 488
-1 943
-1 385
-1 811
-833
-1 271
7*
124
21
38
1
68*
Oc c upation:
166
423
904
231
842
730
728
369
66*
23
Spanish
Portuguese
Polish
Ukrainian
Greek
Chinese
Austro-Asiatic languages
Arabic
Punjabi
Other Indo-Iranian languages
Other non-official languages
Other non-official languages
(Atlantic and Territories only)
1,457
1,788
1,503
916
1,089
4,594
864
1,028
1,486
1,632
8,766
393
-6,369
-2,830
-490
2,204
-7,950
-4,699
-7,435
-4,276
-6,859
-3,811
-2,330
-918
-1,271
838
-1,137
-2,965
-4,995
-3,747
-2,835
-1,895
-754
-2,703
-3,094
-523
1,171
1,408
1,330
819
847
4,302
587
477
1,218
1,085
7,763
266
-3,878
-1,837
-244
2,267
-1,844
-393
-4,271
-2,014
-6,032
-2,330
-424
-1,025
-1,423
450
-993
-541
-858
-766
-750
760
-1,142
-1,910
-995
1,429
17*
Nativity:
Native born
Foreign born
174,772
41,067
-277
1,177
1,166
-4,963
5*
151,555
34,259
-173
765
772
-3,413
421*
Full/Part time work:
Full time
Part time
184,580
31,259
3,910
-23,087
1,220
-7,204
498*
125,189
60,625
5,077
-10,484
2,783
-5,746
3023*
Industry of work:
Agriculture & primary
Manufacturing
Construction
Transportation & storage
Communication & utility
Wholesale trade
Retail trade
Finance/insurance/real estate
Business services
Governement services
Educational services
Health/social services
Accommodation/food & beverage services
Other services
16,146
40,243
20,165
13,405
7,965
13,618
23,985
8,307
14,230
15,010
10,494
7,451
11,301
13,519
-4,665
4,030
-5,972
1,595
9,763
2,344
-10,684
12,123
7,313
8,257
8,472
12,669
-17,767
-11,276
2,068
4,318
-2,072
2,946
5,830
517
-6,562
3,897
-366
2,630
-2,400
6,340
-8,565
-6,868
15687*
5,749
16,565
2,745
3,332
4,604
6,097
25,965
13,515
11,864
11,105
18,379
32,240
16,547
17,107
-5,155
876
-1,690
2,299
9,333
2,301
-7,219
5,244
2,732
7,524
7,792
3,560
-10,701
-7,318
145
2,156
366
3,017
6,340
1,294
-2,946
1,980
167
3,997
1,175
715
-3,729
-3,756
592*
Occupation:
Senior managers
Middle & other managers
Professionals
Semi-professionals & technicians
Supervisors: clerical/sales services
Supervisors: crafts/trades
Administrative & senior clerical personnel
Skilled sales & service personnel
Skilled crafts & trades workers
Clerical personnel
Intermediate sales & service personnel
Semi-skilled manual workers
Other sales & service personnel
Other manual workers
3,151
21,063
27,372
12,866
2,346
11,791
3,340
10,673
28,354
12,670
15,603
36,378
18,135
12,097
38,466
14,496
17,080
242
3,645
-112
6,980
293
-688
-7,471
-7,193
-6,114
-17,857
-13,074
29,047
9,336
11,298
-1,075
202
-4,285
-124
1,456
-1,025
-7,750
-3,227
-6,244
-4,167
-5,651
438*
814
10,543
30,389
10,559
2,821
2,109
18,882
7,832
1,459
31,994
33,993
9,306
21,441
3,672
22,515
11,204
12,948
1,496
4,888
-2,712
3,076
-2,578
-4,380
-194
-8,209
-5,367
-10,381
-7,501
15,575
6,749
8,666
1,197
1,146
-4,874
-919
-1,033
-2,754
-3,121
-3,206
-5,143
-2,312
-4,637
1431*
Census Metropolitan Area (CMA)
Not CMA
CMA less than 500,000
CMA 5000,000 to less than 1 million
CMA 1 million and over
84,520
24,904
28,690
77,725
-3,322
1,486
1,016
2,761
-56
1,019
138
-317
1494*
68,972
22,452
25,164
69,226
15*
-3,133
-14
-98
3,162
-155
-1
-500
337
14*
24
Years of schooling
805
1001*
694
1638*
Work experience:
1106
7435*
510
4166*
Work experience squared:
-17
4684*
-8
2426*
Number of weeks worked:
444 14400*
325 23818*
Years since landing in Canada:
230
555*
151
552*
Per cent immigrant in CMA
175
407*
121
518*
Per cent unemployed in CMA
-64
1
-144
9*
0.40
1602*
0.49
1976*
R2
Source:
Calculated from Statistics Canada, 1996 Census of Canada, Public Use Microdata File on Individuals.
25
Appendix 2
Gr oss and Net E ffects of Ethnic Origin, Official Language Ability, and Home Language on E arnings,
Canada, 1996 Census
Male
Gros s
Net
Number Earnings Earnings
($, Deviation from
Mean)
Female
Gros s
Net
Number Earnings Earnings
($, Deviation from
Mean)
F-Tes t
Rac ial and E thnic Groups :
Not V is ible Minorities
Britis h, B ritis h Is les , Britis h and Canadian
Frenc h, Frenc h and Canadian
Dutc h
German
Other W es t European
Hungarian
Polis h
Ukrainian
Balkan
Greek
Italian
Portugues e
Spanis h
J ewis h
Other E uropean
Other B ritis h multiple origins
Other Frenc h multiple origins
Britis h & Frenc h, Britis h & Frenc h & other
Other s ingle and multiple origins
Canadian
Vis ible Minorities
Arab
Wes t A s ian
South A s ian
Chines e
Filipino
Vietnames e
Other E as t/South E as t As ian
Latin/Central/S outh Americ an
Blac k
Other s ingle and multiple origins
Aboriginal P eople
49
25
2
6
3 873
16
2 874
1 791
3 750
1 081
514
3 036
-241
-7 100
1 837
-3 543
-117
18 249
3 071
249
184
-1 325
1 671
-2 623
975
369
-437
-751
0
-1 981
-437
-465
-417
-3 758
-682
-842
-460
8 513
-208
756
554
356
612
-147
895
463
4 709
5 510
1 275
706
980
612
3 305
2 151
-5
-9
-3
-4
-7
-6
-2
-10
-8
-6
-4
-2
-2
-3
-2
-2
-2
-5
-2
4 209
-11 878
-3 276
462
-5 959
1 922
-12 436
-184
-1 066
1 187
-781
1
-1
-1
-16
-6
-4
8
-4
4
-6
-7
-11
-8
-7
-6
-5
467
740
957
095
762
235
968
330
913
856
496
741
939
443
926
788
776
-944
-2 198
-1 837
-2 914
-2 851
-3 612
-1 611
-3 242
-5 702
-4 206
-7 351
-1 784
-4 660
-3 737
-791
2
2
1
1
6
2
1
3
19
3
11
12
38
633
957
837
263
747
820
007
637
301
314
178
039
218
481
240
082
517
228
228
297
838
271
942
177
698
820
420
740
166
983
F-Tes t
41
21
2
4
960
077
170
794
522
567
671
220
040
983
809
592
158
240
457
760
422
565
042
659
1 664
678
-819
66
1 747
1 821
387
1 591
-201
-1 733
1 613
-2 150
1 537
7 297
2 244
-214
-38
-223
334
-1 777
119
318
-666
-322
-3
-110
915
-62
-338
-539
-256
-689
-112
2 731
708
165
-46
58
108
-213
450
271
3 618
5 113
1 901
488
870
460
3 353
1 953
-3 425
-3 720
-2 561
-57
-950
-3 558
-172
-5 865
-1 295
-2 414
310
583
-610
950
-451
-126
623
-695
-1 564
-649
3 629
1
2
1
4
1
1
2
18
3
11
11
31
-6
964
190
051
519
123
003
217
330
930
-5 279
-1 580
673
110
715
316
161
-2 906
1 327
-7 668
-98
-728
720
-272
130 512
39 633
737
387
351
887
647
647
704
3 243
479
237
874
575
5 786
115
558
-543
1 425
-6 000
-3 602
-1 900
-5 346
-4 052
-3 763
-2 184
-4 454
-5 670
-7 332
-4 654
-3 146
-4 951
247
-133
-533
486
610
-786
-1 666
15
-2 619
-2 851
-1 673
-2 883
-1 241
-1 884
-1 809
289
151 555
34 259
-173
765
680
-3 009
125 189
60 625
5 077
-10 484
2 785
-5 750
104
178
339
000
325
299
945
967
157
989
176
715
707
755
26*
Knowledge of offic ial languages :
Englis h only
Frenc h only
Both E nglis h and Frenc h
Neither E nglis h nor Frenc h
147
23
44
1
123
074
377
265
8*
124
21
38
1
59*
Home Language
Englis h s ingle res pons e
Frenc h s ingle res pons e
Englis h and Frenc h
Aboriginal languages
German
Italian
Spanis h
Portugues e
Polis h
Chines e
Aus tro-A s iatic languages
Arabic
Punjabi
Other Indo-Iranian languages
Other non-offic ial languages
Other non-offic ial languages
(Atlantic and T erritories only)
148 968
47 354
751
610
511
1 233
849
940
829
3 578
711
490
1 064
888
6 897
166
61*
30*
Nativity:
Native born
Foreign born
174 772
41 067
-277
1 177
1 018
-4 332
Full/Part time work:
Full time
Part time
184 580
31 259
3 910
-23 087
1 224
-7 229
-4
4
-5
1
9
2
-10
12
7
8
8
12
-17
-11
2
4
-2
2
5
13*
312*
374*
3046*
Indus try of work:
Agric ulture & primary
Manufac turing
Cons truc tion
Trans portation & s torage
Communic ation & utility
Wholes ale trade
Retail trade
Financ e/ins uranc e/real es tate
Bus ines s s ervic es
Governement s ervic es
Educ ational s ervic es
Health/s oc ial s ervic es
Ac c ommodation/food & beverage s ervic es
Other s ervic es
16
40
20
13
7
13
23
8
14
15
10
7
11
13
146
243
165
405
965
618
985
307
230
010
494
451
301
519
665
030
972
595
763
344
684
123
313
257
472
669
767
276
046
340
098
928
833
532
-6 551
3 871
-380
2 606
-2 384
6 328
-8 529
-6 865
15721*
5
16
2
3
4
6
25
13
11
11
18
32
16
17
749
565
745
332
604
097
965
515
864
105
379
240
547
107
-5 155
876
-1 690
2 299
9 333
2 301
-7 219
5 244
2 732
7 524
7 792
3 560
-10 701
-7 318
10
30
10
2
2
18
7
1
31
33
9
21
3
814
543
389
559
821
109
882
832
459
994
993
306
441
672
22
11
12
1
4
-2
3
-2
-4
515
204
948
496
888
712
076
578
380
-194
-8 209
-5 367
-10 381
-7 501
68
22
25
69
972
452
164
226
-3 133
-14
-98
3 162
2
3
6
1
-2
1
3
1
-3
-3
591*
Oc c upation:
Senior managers
Middle & other managers
Profes s ionals
Semi-profes s ionals & tec hnic ians
Supervis ors : c leric al/s ales s ervic es
Supervis ors : c rafts /trades
Adminis trative & s enior c leric al pers onnel
Skilled s ales & s ervic e pers onnel
Skilled c rafts & trades workers
Cleric al pers onnel
Intermediate s ales & s ervic e pers onnel
Semi-s killed manual workers
Other s ales & s ervic e pers onnel
Other manual workers
3
21
27
12
2
11
3
10
28
12
15
36
18
12
151
063
372
866
346
791
340
673
354
670
603
378
135
097
Cens us Metropolitan Area (CMA )
Not CMA
CMA les s than 500,000
CMA 5000,000 to les s than 1 million
CMA 1 million and over
84
24
28
77
520
904
690
725
38 466
14 496
17 080
242
3 645
-112
6 980
293
-688
-7 471
-7 193
-6 114
-17 857
-13 074
29
9
11
-1
029
294
257
080
184
-4 311
-126
1 482
-1 018
-7 755
-3 235
-6 209
-4 142
-5 612
437*
15
6
8
1
1
-4
564
736
650
187
122
862
-930
-1 028
-2 696
-3 123
-3 209
-5 085
-2 296
-4 595
1424*
-3
1
1
2
322
486
016
761
-181
1 017
194
-201
1490*
-186
-2
-493
365
15*
Years of s c hooling
Work experienc e:
Work experienc e s quared:
15*
792
963*
689
1603*
1104
7417*
510
4169*
-17
4675*
-8
2424*
Number of weeks worked:
444 14384*
325 23814*
Years s inc e landing in Canada:
193
373*
133
415*
Per c ent immigrant in CMA
171
388*
120
506*
-20
0,069
-136
8*
0,40
1660*
0,49
2047*
Per c ent unemployed in CMA
R2
Sourc e:
Calc ulated from S tatis tic s Canada, 1996 Cens us of Canada, P ublic Us e Mic rodata File on Individuals .
26
Spanish
Portuguese
Polish
Chinese
Austro-Asiatic languages
Arabic
Punjabi
Other Indo-Iranian languages
Other non-official languages
Other non-official languages
(Atlantic and Territories only)
849
940
829
3,578
711
490
1,064
888
6,897
166
8,968
-4,330
4,913
-6,856
-7,496
-11,741
-8,939
-7,443
-6,926
-5,788
-3,612
-1,611
-3,242
-5,702
-4,206
-7,351
-1,784
-4,660
-3,737
-791
647
647
704
3,243
479
237
874
575
5,786
115
-5,346
-4,052
-3,763
-2,184
-4,454
-5,670
-7,332
-4,654
-3,146
-4,951
-1,666
15
-2,619
-2,851
-1,673
-2,883
-1,241
-1,884
-1,809
289
30*
Nativity:
Native born
Foreign born
174,772
41,067
-277
1,177
1,018
-4,332
13*
151,555
34,259
-173
765
680
-3,009
312*
Full/Part time work:
Full time
Part time
184,580
31,259
3,910
-23,087
1,224
-7,229
374*
125,189
60,625
5,077
-10,484
2,785
-5,750
3046*
Industry of work:
Agriculture & primary
Manufacturing
Construction
Transportation & storage
Communication & utility
Wholesale trade
Retail trade
Finance/insurance/real estate
Business services
Governement services
Educational services
Health/social services
Accommodation/food & beverage services
Other services
16,146
40,243
20,165
13,405
7,965
13,618
23,985
8,307
14,230
15,010
10,494
7,451
11,301
13,519
-4,665
4,030
-5,972
1,595
9,763
2,344
-10,684
12,123
7,313
8,257
8,472
12,669
-17,767
-11,276
2,046
4,340
-2,098
2,928
5,833
532
-6,551
3,871
-380
2,606
-2,384
6,328
-8,529
-6,865
15721*
5,749
16,565
2,745
3,332
4,604
6,097
25,965
13,515
11,864
11,105
18,379
32,240
16,547
17,107
-5,155
876
-1,690
2,299
9,333
2,301
-7,219
5,244
2,732
7,524
7,792
3,560
-10,701
-7,318
104
2,178
339
3,000
6,325
1,299
-2,945
1,967
157
3,989
1,176
715
-3,707
-3,755
591*
Occupation:
Senior managers
Middle & other managers
Professionals
Semi-professionals & technicians
Supervisors: clerical/sales services
Supervisors: crafts/trades
Administrative & senior clerical personnel
Skilled sales & service personnel
Skilled crafts & trades workers
Clerical personnel
Intermediate sales & service personnel
Semi-skilled manual workers
Other sales & service personnel
Other manual workers
3,151
21,063
27,372
12,866
2,346
11,791
3,340
10,673
28,354
12,670
15,603
36,378
18,135
12,097
38,466
14,496
17,080
242
3,645
-112
6,980
293
-688
-7,471
-7,193
-6,114
-17,857
-13,074
29,029
9,294
11,257
-1,080
184
-4,311
-126
1,482
-1,018
-7,755
-3,235
-6,209
-4,142
-5,612
437*
814
10,543
30,389
10,559
2,821
2,109
18,882
7,832
1,459
31,994
33,993
9,306
21,441
3,672
22,515
11,204
12,948
1,496
4,888
-2,712
3,076
-2,578
-4,380
-194
-8,209
-5,367
-10,381
-7,501
15,564
6,736
8,650
1,187
1,122
-4,862
-930
-1,028
-2,696
-3,123
-3,209
-5,085
-2,296
-4,595
1424*
Census Metropolitan Area (CMA)
Not CMA
CMA less than 500,000
CMA 5000,000 to less than 1 million
CMA 1 million and over
84,520
24,904
28,690
77,725
-3,322
1,486
1,016
2,761
-181
1,017
194
-201
1490*
68,972
22,452
25,164
69,226
15*
-3,133
-14
-98
3,162
-186
-2
-493
365
15*
27
Years of schooling
792
963*
689
1603*
Work experience:
1104
7417*
510
4169*
Work experience squared:
-17
4675*
-8
2424*
Number of weeks worked:
444 14384*
325 23814*
Years since landing in Canada:
193
373*
133
415*
Per cent immigrant in CMA
171
388*
120
506*
Per cent unemployed in CMA
-20
0.069
-136
8*
0.40
1660*
0.49
2047*
R2
Source:
Calculated from Statistics Canada, 1996 Census of Canada, Public Use Microdata File on Individuals.