Presentation is loading. Please wait.

Presentation is loading. Please wait.

1 The Use of Census Data in the Analysis of Ethnic Inequalities: The Canadian Experience, 1996-2006 Nikolaos I. Liodakis Department of Sociology Wilfrid.

Similar presentations


Presentation on theme: "1 The Use of Census Data in the Analysis of Ethnic Inequalities: The Canadian Experience, 1996-2006 Nikolaos I. Liodakis Department of Sociology Wilfrid."— Presentation transcript:

1 1 The Use of Census Data in the Analysis of Ethnic Inequalities: The Canadian Experience, Nikolaos I. Liodakis Department of Sociology Wilfrid Laurier University Waterloo, ON, Canada

2 2 Social Inequality in Canada: The Theoretical and Research Contexts  Ethnic perspective dominant in the analysis of social inequality in Canada since Porter (The Vertical Mosaic, 1965)  Immigration and ethnic affiliation important factors in the process of social class formation in Canada  The Canadian ethnic mosaic is vertical (Charter vs. entrance groups, etc.)  Ethnicity, associated with class, implied blocked mobility  Despite acknowledging their internal stratification (1965: 72-73), Porter treated ethnic groups as homogeneous entities  The gender and nativity dimensions of social inequality among groups have been adequately examined, but there exists, still, a relative silence on social class(es)

3 3 Research on Social Inequality in Canada  Ethnic perspective: a dominant research tradition; enjoys discursive hegemony; it is the dominant narrative of social inequality in Canada  Ethnic perspective treats ethnic and “visibility” groups as homogeneous entities  This conceals important class, gender and nativity (and other) divisions and variations within groups  Visibility Thesis: colour has replaced ethnicity in the structure of social inequality in Canada  “Race”: The fundamental basis of social inequality in Canada (e.g., Gabaluzi 2007, Canada's Economic Apartheid)

4 4 Inter-sectionalist Theorizing  Mono-causal, mono-dimensional approaches inadequate for analyzing social relations; complex character of social inequality  Integrationist / inter-sectionalist approaches: class, gender and “race”/ethnicity fundamental axes of social organization; important in the matrix of domination (but not dominant perspective, Stasiulis,1999)  Must understand the simulteneity, interactivity of class, gender, “race”/ethnicity  Although analytically distinct: inter-locking, mutually- determining, reinforcing social relations  Any two sets of social relations are always present in, permeate, inform and (re-)define the third

5 5 Bringing Classes Back In  Conspicuously absent from quantitative studies of social inequality in Canada, especially from analyses of ethnic earnings’ differentials  Canadian social formation: not only patriarchal, racist; also capitalist  What is the picture of social inequality that emerges if we begin from a different point of departure?  Re-introduce classes, retain gender and ethnicity  A holistic, more comprehensive, and arguably more accurate picture of social inequality in Canada?

6 6 Findings  Ethnic groups are not homogeneous entities  There exist class, gender and nativity earnings structures  The class and gender earnings differentials within ethnic groups are greater than the differentials among ethnic groups  Class and gender are persistent bases of social inequality in Canada  Human capital and labour market/production “variables” affect more earnings differentials than ascriptive “variables”, with the exception of gender

7 7 Ontology, Epistemology and Methodogical Limitations Data-gathering is theory-driven; Censuses rely upon dominant, well-entrenched paradigms; tend to privilege the ethnic perspective; undermine other perspectives (e.g., class) Running out of single-origin groups (“the categories are emptying themselves out”)  Racialization of analysis of social inequalities; State-driven “scholarship”? Language (construction of “unreal” social reality): some ethnic/“visibility” groups: nominal-statistical categories without social referents; Stats Can constructs: Caribbeans, Balkans, Southern Europeans, South Asians, Latin Americans, etc. Problematic epistemic relationships? (Harré’s “taxonomic collectives”)

8 8 Ontology, Epistemology and Methodogical Limitations Several problems: 1.By relying on the visible minority indicator alone, we conceal the important and sizable economic inequalities that exist within the category (e.g., earnings of Chinese- origin respondents vs. those of Filipino-origin) 2.We cover the complexity of social inequality by reducing it to a two-tier hierarchy (visible/non-visible categories). We homogenize both the “Self” and the “Other” 3.By overemphasizing the ethnic/visibility dimension of inequality, we obfuscate its class and gender dimensions

9 9 1. No question on respondents’ own subjective ethnic/cultural identity; we ask about their ancestry instead. This has created the multiple origins categories that are increasing in size (a problem in “counting” and reporting “results”). 2. A racist definition of “visible minorities” (Synnott and Howes 1996: a spurious category) “not white in colour” “not Caucasian in race” uncritical use of geography 3.Defining ethnicity through ancestry  we know nothing about the economic inequalities among self-identified “ethnics”; we know everything about offspring of ancestors Problems with “ethnic” questions in Censuses

10 10 Ontology and Implications We do not interrogate the categories. We reproduce the language of the oppressor (Goldberg). Social scientists paint a picture of inequality that does not exist, or exists only as a statistical reality. This image informs and legitimizes the images reproduced by mass media, but also the stereotypes in the minds of non-social scientists, and thus, their social praxis (Miles and Torres) It (mis)directs public policy makers and social action. We need a new, anti-racist meta-language; a new emancipatory vocabulary that transcends the racial categories. Any suggestions?

11 11 Proposed Solution(s) A. Ask respondents about their own subjective ethnic/cultural identity; retain the questions of ancestry for data comparability reasons The 2002 Stats Canada Ethnic Diversity Survey did ask about respondents’ self-identification of ethnicity, but the question sequence is questionable (it followed a number of questions about their ancestry; skewed results?) Although it was clearly stated in the Survey that the information gathered might be used in conjunction with the 2001 question on ethnic ancestry to enhance the information provided for the Survey, inexplicably, the self-identification question was not used in the 2006 Census.

12 12 Problematic Issues 1.If we ask about respondents’ own subjective ethnic/cultural identity, we will get smaller numbers in some ethnic groups (those who have been longer in Canada). 2.“The category Canadian will increase in size even more” (So? Why not? See Howard-Hassmann) 3.Negative implications for the “image” of Canada as a multicultural society? 4.Implications for the notion of the “Canadian nation(s)”? 5.Political pressures: there may be additional critiques against multiculturalism, from the right, and yet another call for dismantling the policy all together (for the wrong reasons)

13 13 Proposed Solution(s) B. No “solution” to the visibility issue in the foreseeable future. Any suggestions? How do we, or should we collect “racial” data, useful for combating inequality, discrimination and racism, without asking racist questions? Post-structuralists may propose the use of strategic essentialism, à là Derrida (see Thobani 2007). We do and will continue to reproduce racist language in the near future.

14 14 Circumventing the Issue Caveat: the following “pseudo-solution” may not apply in other contexts, although it will certainly have implications: 1.Collect ethnicity data in Censuses by asking respondents to self-report their subjective ethnic identity; retain the ancestry and visibility questions (but what we do with “multiples”?) 2.Researchers then could disaggregate the category “visible minority” to its “constituent” parts (disentangle the self- identified ethnic categories contained in the visibility category) This will provide rich data on the economic inequalities within the visibility category. Arguably, a more comprehensive and accurate picture of economic inequality. A positive implication for social policy, especially if we include class and gender issues.

15 15 Ethnic groups are not homogeneous, monolithic entities. They differ in their class, gender and nativity compositions. Evidence of Ethnic Heterogeneity

16 16 The Sex Composition of Groups ETHNIC GROUP% of M+/-% of M% of F+/-% of F Italian South Asian British Portuguese Greek French Jewish Chinese Caribbean Filipino SAMPLE

17 17 Evidence of Ethnic Heterogeneity Ethnic groups are not homogeneous, monolithic entities. They differ in their class, gender and nativity compositions.  Sex: Filipino- and Caribbean-descent respondents have a significantly higher percentage of females

18 18 ETHNIC GROUP% of FB+/-% for FB% of NB+/-% for NB Filipino South Asian Caribbean Chinese Portuguese Greek Italian Jewish British French SAMPLE The Nativity Composition of Groups

19 19 Evidence of Ethnic Heterogeneity Ethnic groups are not homogeneous, monolithic entities. They differ in their class, gender and nativity compositions.  Sex: Filipino- and Caribbean-descent respondents have a significantly higher percentage of females  Nativity: Filipino-, South Asian-, Caribbean-, Chinese-, Portuguese- and Greek-descent respondents have a significantly higher percentage of foreign-born

20 20 The Class Structure of the Sample Number of People Classes Employers (E) 17,067 Petty Bourgeoisie (PB) 24,013 Managers and Supervisors (M&S) 32,742 Semi-autonomous Workers (SAW) 57,924 Proletariat (P) 169,449 N %

21 21 The Class Composition of Groups (%) ETHNIC GROUPPSAWM&SPBE British (31,986) Caribbean (3,460) Chinese (8,763) Filipino (2,811) French (30,498) Greek (1,784) Italian (9,028) Jewish (2,118) Portuguese (2,936) S. Asian (6,038) SAMPLE (301,195)

22 22 The Class Structure of Men and Women in the Sample Classes Percentage Men Women P SAWM&S PBE

23 23 The Class Structure of the Sample by Gender and Nativity Classes Percentage FB Men NB Men FB Women NB Women PSAWM&SPBE

24 24 The Class Structure of Chinese-descent Respondents Foreign-born and Native-born Men and Women Classes Percentage All FB Men Ch. FB Men All NB Men Ch. NB Men All FB Women Ch. FB Women All NB Women Ch. NB Women PSAWM&SPBE

25 25 The Class Structure of Greek-descent Respondents Foreign-born and Native-born Men and Women Classes Percentage All FB Men Gr. FB Men All NB Men Gr. NB Men All FB Women Gr. FB Women All NB Women Gr. NB Women PSAWM&SPBE

26 26 Heterogeneity Within Ethnic groups  Class: only Jewish-descent respondents have an atypical class structure  If ethnic groups are conceived as units, no clear “ethnic class” pattern emerges  When all three dimensions are examined within each ethnic group, no clear pattern emerges.  Gender is introduced: females are over-represented in the P and SAW; under-represented in all other classes  Nativity is introduced: NB females are under-represented in the P and E. NB men are over-represented in the P and in M&S

27 27 Earnings Differentials 1.There exist class, gender and nativity earnings structures. 2.Males make more than females in all classes 3.NB males make more than the FB. NB females make more than FB expect in the PB

28 28 N301,195 Mean30, , Mode30, Std. Deviation24, Range254, Minimum-50, Maximum204, Earnings of the Sample Median

29 29 Sample Mean of Earnings by Class CLASSNMeanMedianSD±% Proletariat169,44924, , , Semi-autonomous Workers 57,92438, , , Managers & Supervisors 32,74245, , , Petty Bourgeoisie24,01319, , , Employers17,06737, , , Sample301,19530, , ,521.12

30 30 Sample Mean of Earnings by Sex SEXNMeanMedianSD±% of Mean Males160,96136, , , Females140,23423, , , Sample301,19530, , ,521.12

31 31 Sample Mean of Earnings by Nativity PLACE OF BIRTH NMeanMedianSD±% of Mean Foreign-born66,10828, , , Native-born235,08730, , , Sample301,19530, , ,521.12

32 32 Earnings Differentials Among and Within Ethnic Groups If ethnic groups are conceived as units, then, there is an ethnic rank order of earnings

33 33 ETHNIC GROUP NMeanMedianSD±% of Mean Jewish2,11843, , , British31,98633, , , Italian9,02831, , , French30,49829, , , Portuguese2,93626, , , South-Asian6,03825, , , Chinese8,76325, , , Greek1,78424, , , Caribbean3,46024, , , Filipino2,81122, , , Sample301,19530, , , Earnings by Ethnic Group

34 34 Examples of Earnings Differentials Within Ethnic Groups Jewish-descent Respondents: Male, Employers, Native-born$84,876 - Females, PB, Foreign-born$15,946 68,930 South Asian-descent Respondents: Males, M&S, Native-born$59,833 - Females, PB, Foreign-born$14,304 45,529 Filipino-descent Respondents: Males, Employers, Foreign-born$39,426 - Males, PB, Native-born$09,415 30,011

35 35 Earnings Differentials Among and Within Ethnic Groups If ethnic groups are conceived as units, then, there is an ethnic rank order of earnings If we examine the class, gender and nativity dimensions of earnings within ethnic groups, the overall sample patterns hold Class and gender earnings differentials are greater than ethnic differentials

36 36 Bivariate Regressions: Gross Effects on log Earnings Variable RAdj. R 2 % “ Explained” Class and Sex (interaction) Weeks Worked (1995) Class Full-time Industry Sex Years of Schooling Age Ethnicity Visibility Place of Birth0.022  0.00  0.00 Language(s)0.007  0.00  0.00

37 37 Multiple Regression Models on log Earnings Variables ModelAdj. R 2 Schooling Full-Time Weeks Worked Industry Age Sex Class Ethnicity Visibility 9No improvement Place of Birth10No improvement Official Language(s)11No improvement Class and Sex (interaction)

38 38 What “variables” account for inequalities in earnings? More: Labour market/production: Full-time, weeks worked, industry, classes of P, SAW, M&S Human Capital: Years of Education Ascriptive: Gender, Age

39 39 What “variables” account for inequalities in earnings? More: Labour market/production: Full-time, weeks worked, industry, classes of P, SAW, M&S Human Capital: Years of Education Ascriptive: Gender, Age Less: Labour market/production: Classes of PB and E Human Capital: Language(s) Ascriptive: Ethnicity, Visibility, Place of Birth

40 40 Findings  Ethnic groups are not homogeneous entities  There exist class, gender and nativity earnings structures  The class and gender earnings differentials within are greater than the differentials among ethnic groups  Class and gender are persistent bases of social inequality in Canada  Human capital and labour market/production “variables” affect more earnings differentials than ascriptive “variables”, with the exception of gender

41 41 Relative Silence on Class(es)?  In most qualitative studies: focus on immigrant women of “colour”; actualities of life, multiple jeopardies Small occupational groups proxies for working class (domestic labourers, nurses) Nativity dimension (foreign-born); Gender dimension (women) Conflate “race” and/or gender with class? “Race”, gender, and class essentialism (Jhappan, 1996) Relative silence on classes  In most quantitative studies: focus on income/earnings; gender and nativity dimensions within ethnic/“visibility” groups, but silence on classes

42 42 Female Employers by Ethnic Group ETHNIC GROUP% of F E+/-% Jewish Greek Chinese Italian South Asian British French Portuguese Caribbean Filipino SAMPLE3.4-

43 43 Semi-autonomous Workers by Ethnic Group ETHNIC GROUP% of SAW+/-% Jewish French Chinese British Caribbean South Asian Filipino Italian Greek Portuguese SAMPLE19.2-

44 44 Earnings Differentials within Semi-autonomous Workers CLASSSEXPLACE OF BIRTH NMeanSD S-A Workers MalesForeign-born6,52344, , Native-born20,65645, , Total27,17945, , FemalesForeign-born5,68932, , Native-born25,05632, , Total30,74532, , TotalForeign-born12,21239, , Native-born45,71238, , Class Total57,92438, ,642.01

45 45 PLACE OF BIRTH NMeanMedianSD±% Foreign-born7,95024, , , Mean FB66,10828, , , Native-born81334, , , Mean NB23,508730, , , Earnings of Chinese-descent Respondents Foreign-born and Native-born

46 46 THESISMETHODSEMPHASIS Vertical MosaicQuantitative: European ethnic National data, groups gross effects Blocked Mobility Occupation No Gender or and Income Nativity dimensions Occupation a proxy for Class 1960s

47 47 THESISMETHODSEMPHASIS Fading Quantitative: European Vertical Mosaic?National data, and some non- gross/net effectsEuropean ethnic groups Earnings Occupation and Convergence Income/Earnings Gender and and Nativity Mobility dimensions Relative Silence on Class 1970s-1980s

48 48 THESISMETHODSEMPHASIS New Mosaic:Quantitative: Mostly “Race”, “colour” has National data, “Visible” minority replaced gross/net effectsgroups Ethnicity Occupation and Earnings Visibility Qualitative: Intersections of Thesis Small focus groups Gender, “Race”/ (immigrant women of Ethnicity, Nativity, No Mobility? “colour”) Class(but not the dominant Life experiences paradigm) Relative Silence on Class(es) 1990s - Present


Download ppt "1 The Use of Census Data in the Analysis of Ethnic Inequalities: The Canadian Experience, 1996-2006 Nikolaos I. Liodakis Department of Sociology Wilfrid."

Similar presentations


Ads by Google