Alvin Lim (SID: 547298)

Tutor: Botond Vitos

MULT30018 Applied Research Methods

26 October 2012

They Stole our Jobs: The Effect of Labour Market Competition

on the Acceptance of Ethnic Diversity in Australia

Introduction

Australia is an ethnically diverse migrant nation with a melting pot of cultures. Yet, ra-

cial tensions have persisted, most recently with attacks known as curry bashings which

have targeted foreigners and non-White immigrants (D'Costa 2010). Numerous studies

have shown that racism in countries with significant migrant populations is closely linked to

economic relations in the labour market, such as in Europe (Okkerse 2008). Yet in Austra-

lia, there is a ‘dearth of empirical evidence’ (Dunn et al. 2004, p. 1) on the nature and ex-

tent of racism in this context.

In this study, I examined the relationship between age, sex, education, equity

preference in labour markets, immigration status, income, aversions (towards

indigenous people and people of different races, religion, language or nation-

ality), and finally self-identified levels of an individual’s acceptance of ethnic

diversity.

The regression model tested statistically significant and although causality was not es-

tablished, the findings reveal insights that could help future research and have normative

implications on policymaking.

Literature Review

The killing of a Chinese university researcher in 2009 and the 2010 race-related fatal

stabbing of 21-year-old Indian student Nitin Garg in the colloquially labelled ‘curry bash-

ings’ are but recent spikes in Australia’s racial tension-riddled past (D'Costa 2010). These

outward expressions of hate have been theorised as subjective violence by Slovenian phi-

losopher Slavoj Žižek. Žižek (2008) theorises a distinction of two types of violence - sub-

jective (visible) and systemic (invisible).

Subjective violence refers to apparent forms of violence such as civil unrest. Symbolic

violence, also visible, exists in hate-speech, incitement and racism. Žižek argues that there

is an objective violence, a sinister, behind-the-scenes violence that exists as a causal

mechanism behind this subjective, visible violence.

Racism is not only reflected in personal attitudes and behaviours, it can be expressed

in the values, presumptions, structures and processes of social, economic, cultural and

political institutions (Healey 2003, pp. 10-1). This research will explore how the ‘curry

bashings’ - subjective violence - be symptomatic of a bigger, objective violence that could

stem from competition in the labour market.

Gregson (2007) argued that racism is commonly a part of a competitive struggle within

classes, and that this class rivalry is often exploited by employers as a tool to manufacture

distrust between migrant workers and White workers so they would not unionise for ‘im-

proved wages and conditions’ (Gregson 2007, p. 92).

In Australia, social science research has found strong correlations between labour

market competition and racism throughout the country’s history. Markus (1985) found that

mob violence and racist stereotyping against Chinese immigrants during Australiaʼs gold

rush in the 1850s was due to an cultural identifying mechanism: that they were the largest

non-European group on the diggings, ʻdistinguished by appearance and behaviourʼ (Mar-

kus 1985, p. 87). An individual who shuns ethnic diversity is likely to reproduce these

negative stereotypes and construct immigrants and indigenous peoples as the Other

(Vasta & Castles 1996, pp. 76-7) and confines them to unemployment or employment in

jobs below their capability.

In cases where the marginalised parties already have advantageous positions over

local Australians, jealousy over earnings differentials may arise. In 2002, an Australian Re-

search Council-funded study that measured attitudes towards racism in New South Wales

and Queensland uncovered that the race backlash in western Sydney ‘appeared to be mo-

tivated by economics’ (Megalogenis 2003, p. 28).

Other determinants that could influence attitudes towards racism are education, as

better-educated individuals are more likely to welcome migration policy for economic

benefit (D'Costa 2010). Males should assert lower levels of acceptance towards ethnic di-

versity as they are statistically the main perpetrators of the reported violence towards for-

eigners in Australia, and have the most direct contact with unskilled migrant labour where

most friction occurs (D'Costa 2010; Gregson 2007).

Phizacklea & Miles (1980) found, in North America, that immigrant workers’ class con-

sciousness as outsiders also adds to their desire to integrate with the local community. The

West Indian migrants were aware of their inequitable positions compared to their white

counterparts, yet desired co-existence in a ‘pragmatic acceptance of capitalism’ (Phizack-

lea & Miles 1980, pp. 228-9). Therefore, it is probable that immigration status could influ-

ence acceptance levels of ethnic diversity.

Methodology

The data used in this research is from the World Values Survey (WVS), conducted in

2005 in Australia with a survey population of 1,421. The participants were Australian resi-

dents, of whom 45% were male and 55% female, with age range 18-95 years.

I ran tests for correlations on the independent variables with the dependent variable

and each other. Following that, I ran a linear OLS multiple regression on the independent

variables that tested statistically significant.

My dependent variable is the individual’s acceptance of ethnic diversity associated

with the question ‘Turning to the question of ethnic diversity, with which of the following

views do you agree?’ ranked on a 10-point Likert-type scale. The acceptance levels range

from 1 (ethnic diversity erodes a country’s unity) and 10 (ethnic diversity enriches life).

The independent variables are:

I. Jobs equity preference - associated with Q9b ʻWhen jobs are scarce, employers

should give priority to Australian people over immigrantsʼ. There are three codings: 1

(Agree), 2 (Neither), and 3 (Disagree). I recoded the variable so that 1 corresponds to

‘agree’, 2 to ʻdisagreeʼ and removed ʻneitherʼ by declaring it a missing value. I found it

necessary to do so to eliminate the problem of sample bias. Alternatively, I could have

retained ‘Neither’ as the middle category of a rating scale from 1 to 3, but decided

against it for two reasons: a) Respondents who did not know which option to pick

could have went with ‘neither’ and not necessarily because it was the middle category;

and b) removing ‘Neither’ reduces the sample size by 300 to N=1,094, a still-

acceptable sample size for the purposes of social science research.

II. Age - associated with Q91 ʻThis means you are how many years old?ʼ Age values

range from 18 to 95 and the numbers correspond to the year of age.

III. Sex - associated with Q89 ʻWhat is your sex?ʼ I reversed the coding of this vari-

able so that 0 corresponds to ʻfemaleʼ, and 1 to ʻmaleʼ.

IV. Income - associated with Q107 ‘What is your gross household income, before tax

or other deductions, from all sources?’ Values range from 1 (less than $18,000 per

annum) to 10 (more than $115,000 per annum).

V. Education - associated with Q92 ‘What is the highest educational level that you

have attained?’ The responses range from 1 (inadequately completed elementary

education) to 8 (completed a bachelors or postgraduate degree).

VI. Aversions - associated with Q8 ‘On this list are various groups of people. Please

tick any that you would not like to have as neighbours, with 11 variables in total. I

combined a selection of five variables b) ‘People of a different race’; d) ‘Immigrants/

foreign workers’; f) ‘People of a different religion’; i) ‘People who speak a different lan-

guage’; j) ‘Aboriginal people’ into a (0...5) scaled variable. This way, a respondent with

no aversions would score 0, a respondent who indicated two aversions would score 2,

and so on. This was to avoid collinearity in the regression as these variables are

closely related.

Analysis: Correlation (see Table 1)

• There was a significant, positive relationship between jobs equity preference and ac-

ceptance of ethnic diversity, r = 0.387, p < 0.01, indicating that disagreement that jobs

should be kept only for Australians during hard times, led to greater acceptance of ethnic

diversity.

• There was a significant, negative relationship between acceptance of ethnic diversity

and aversion to a different language, race, religion, foreigners, indigenous people and

religion. The results, r = -0.328, p < 0.01, indicate that those who checked more aversion

categories were less accepting of ethnic diversity.

• Immigration status (r = 0.001, p = 0.965) had no correlation to acceptance of ethnic

diversity.

• Sex (r = -0.107, p < 0.01) and age (r = -0.108, p < 0.01) were weakly negatively cor-

related to acceptance of ethnic diversity.

• There was a significant, positive relationship (r = 0.197, p < 0.01) between accep-

tance of ethnic diversity and education.

• Scale of incomes (r = 0.110, p < 0.01) and education (r = 0.197, p < 0.01) were

weakly positively correlated to acceptance of ethnic diversity.

• There was a significant, negative relationship between jobs equity preference and

the aversion variable (r = -0.275, p < 0.01), indicating that those who agreed that jobs

should be kept only for Australians doing hard times were likely to indicate more aver-

sions.

Tabl

e 1:

Analysis: Regression (Tables 2 - 4)

Taking the correlation test results into consideration, the final regression model, less

the independent variable not significantly correlated (immigration status) was:

ETDIVERSITY = β0+ β1JOBEQUITY + β2AVERS + β3MALE + β4INCOME +

β5EDUC + β6AGE + ɛ

• 914 of the respondents answered all the relevant questions and were included in the

regression.

• Adjusted R2 = 0.219, p < 0.05, indicating that the model is statistically significant and

that the independent variables explain 22.5% of the variance in the dependent variable.

Table 2:

Table 3:

• Income (p = 0.207) and highest educational level obtained (p = 0.107) and age (p =

0.464) were no longer found to significantly impact acceptance of ethnic diversity when

controlling for other factors.

• Jobs equity preference (B = 1.542) was positively associated with ethnic diversity

while aversions (B = -0.678) and sex (B = -0.559) were negatively associated with ethnic

diversity.

• It can be interpreted from the standardised beta coefficient that jobs equity prefer-

ence (β = 0.295) had the largest effect on the dependent variable, followed by aversions

(β = -0.243) and sex (β = -0.107).

Table 4:

Discussion

Some of the possible determinants examined in the literature (immigration status, age,

income and education) were found not to significantly impact an individual’s acceptance of

ethnic diversity in Australia when controlling for other variables. The number of people who

responded to all variables (df= 914) was also short of 1,000, marginally less than ideal for

social science research. Furthermore, there are potential problems with the jobs equity

preference variable, as mentioned earlier. While this research sought to reduce the likeli-

hood of measurement error by recoding the variable, an even-numbered Likert scale

would have been a more appropriate for the purpose of this research. Therefore, I would

recommend that these results be treated with caution.

This does not mean that the research has not met its objectives. In line with the initial

hypothesis, key determinants that help explain the acceptance of ethnic diversity in Austra-

lia were found. They are: an individual’s preference for jobs equity, aversions to people of

a different language, race as well as foreigners and indigenous people, and sex.

These findings confirm the initial expectations discussed in the literature review of this

paper:

I. Individuals who are more accepting of ethnic diversity are less likely to agree that

jobs should be kept only for Australians, and therefore more accepting of equity in la-

bour markets.

II. Individuals who have more aversions (or prejudices) against those of a different

culture, religion or birthplace are also less likely to embrace ethnic diversity. These

aversions have potentially large implications. Vasta & Castles (1996) found that when

such cultural differences are ‘viewed through the ideologies’ of racism... these cultural

skills are reinterpreted... as ‘poor communication skills’, ‘high training costs’, or ‘unreli-

ability’ (Vasta & Castles 1996, p. 76).

III. Gender was found to be significantly associated with an individual’s acceptance of

ethnic diversity, which is consistent with the hypothesis that males are the main perpe-

trators of reported racial violence. Males are also more likely to encounter their cultur-

ally different counterparts in low wage, blue-collar jobs where, in 1991, indigenous

people were twice as likely to be employed (Vasta & Castles 1996, p. 83) and where

close proximity of the working environment emphasises violence (Neal & Rettig 1963).

Fostering social cohesion that transcends racial lines is important in Australia where

globalisation and generational change have brought together over 150 different ethnicities

plus indigenous communities; 90 different languages and hundreds more indigenous

tongues; and over a hundred religions (Aboriginal & Action 1998, p. 79).

Vasta & Castles (1996) found that ideologies of racism are produced and reproduced

in the economy and society. Social divisions in Australian society are reinforced this way,

and the inferior labour market position of immigrant or indigenous men and women serves

to help reproduce negative stereotypes of the Other. This could also affect the bottom line

of business and productivity, since the economic potential of the victims of racisms re-

mains unfulfilled (Vasta & Castles 1996, p. 77).

The consequences of a nation divided on cultural lines are serious in a shrinking

world. As such, understanding the relationships between racism, society and economy is

an important task - one that may be above the scope of the WVS survey employed in this

study. Nevertheless, some headway may have been made with the results from this re-

search in understanding labour market impacts on ethnic diversity. To better understand

the nuances, I would recommend conducting further mixed-methods research where a

combination of focus groups, surveys and interviews could be used to uncover other pos-

sible determinants that would help guide policymakers and researchers in the future.

Bibliography

1. Aboriginal, Ff & Action, IR 1998, Bringing Australia together: the structure and experi-

ence of racism in Australia, Foundation for Aboriginal and Islander Research Action.

2. D'Costa, B 2010, FEATURE ARTICLE: Curry bashing? A racist Australian underbelly

and the education industry, Australian National University, February 6, 2010,

<http://asiapacific.anu.edu.au/blogs/southasiamasala/2010/02/06/feature-article-cur

ry-bashing-a-racist-australian-underbelly-and-the-education-industry/>.

3. Dunn, KM, Forrest, J, Burnley, I & McDonald, A 2004, 'Constructing racism in Australia',

Australian journal of social issues, vol. 39, no. 4, pp. 409-30.

4. Gregson, S 2007, 'War, Racism and Industrial Relations in an Australian Mining Town,

1916–1935', Economic and Labour Relations Review, The, vol. 18, no. 1, p. 79.

5. Healey, J 2003, Racism in Australia, The Spinney Press.

6. Markus, A 1985, 'Comment: Explaining the Treatment of Non-European Immigrants in

Nineteenth Century Australia', Labour History, no. 48, pp. 86-91.

7. Megalogenis, G 2003, 'Home of intolerance', in J Healey (ed.), Racism in Australia, The

Spinney Press, Sydney, p. 28.

8. Neal, AG & Rettig, S 1963, 'Dimensions of alienation among manual and non-manual

workers', American Sociological Review, pp. 599-608.

9. Okkerse, L 2008, 'How to Measure Labour Market Effects of Immigration: A Review',

Journal of Economic Surveys, vol. 22, no. 1, pp. 1-30.

10. Phizacklea, A & Miles, R 1980, Labour and Racism, Routledge & Kegan Paul.

11. Vasta, E & Castles, S 1996, The teeth are smiling: The persistence of racism in multi-

cultural Australia, Allen & Unwin.

Final Assessment