No Thanks We re Full... Attitudes Toward Immigration

8/3/2019 No Thanks We re Full... Attitudes Toward Immigration

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302 IMRVolume 42 Number 2 (Summer 2008):302329

2008 by the Center for Migration Studies of New York. All rights reserved.DOI: 10.1111/j.1747-7379.2008.00126.x

Blackwell Publishing LtdOxford, UKIMREInternational Migration Review0197-91831747-7379 2008 by the Center for Migration Studies of New York. All rights reservedXXXOriginal Articles , fi

No Thanks, Were Full: Individual

Characteristics, National Context, andChanging Attitudes Toward Immigration1

Rima WilkesNeil GuppyLily FarrisUniversity of British Columbia

In this paper we examine how individual-level characteristics and nationalcontext affect attitudes toward immigration. Although many previousstudies have compared attitudes toward immigration across countries,little attention has been paid to how attitudes may be affected by changes

within a country over time. We take advantage of seventeen national Cana-dian Gallup surveys to consider how differences in national economic con-ditions and changing immigration flows affect attitudes and changes inattitudes between 1975 and 2000. While the state of the national economyaffects attitudes this is not the case for the rate of immigration. Rather thanaffecting some groups more than others the state of the economy has a

relatively uniform effect across groups. Our results also show that far from beinga continuum, being anti-immigration and being pro-immigration are qual-itatively different. Interest, ideology, and the national economy affect anti-immigration sentiments, but only ideology affects pro-immigration sentiments.

INTRODUCTION

Several years ago Canadas national newspaper The Globe and Mail held a

contest asking readers to define a Canadian. One of the winning entries was:A Canadian is someone who, upon arriving on the shores of Canada, turnsaround to the person behind him and says, No thanks, were full. This jokesuggests that Canadians, like citizens of other countries, by and large do not favorimmigration. Yet studies of public opinion in Canada, and elsewhere, indicatethat while anti-immigration attitudes may be de facto for some, this is not thecase across the board. Explaining variation in levels of support for immigrationhas been a topic of considerable interest to scholars and policy makers alike.

1Funding for the research presented in this paper has been provided by a grant from RIIM(Research on Immigration and Integration in the Metropolis). Special thanks to threeanonymous reviewers and to Sylvia Fuller, Martin Puterman, Dan Hiebert, Eric Sayre, and SeanLauer for their helpful advice and comments.


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In this paper we examine how individual characteristics and nationalcontext affect individuals attitudes toward immigration. Since most studies

focus on individuals within single countries there is a limited understanding ofhow national context affects attitudes. Those studies that do consider nationalcontext use a cross-sectional research design that allows for comparison acrosscountries (e.g., rich versus poor). However, the role that changes in conditions

within countries over time, such as improvements to the economy, might play,is absent from this work. Here we hold country constant (Canada) and allownational conditions (e.g., the state of the economy, immigration rate) to vary.This enables us to assess (1) whether key hypotheses developed to explain cross-

national variation in attitudes also apply to over time differences; and (2) howthe effect of individual characteristics might vary with national conditions.

ATTITUDES TOWARD IMMIGRATION

Theory

Implicit in most theoretical models about attitudes toward immigration is theidea that anti-immigration attitudes are a form of prejudice because theyevaluate people not as individuals but based on their group membership.There is considerable theoretical debate on the extent to which this prejudicestems from economic factors vs. noneconomic factors or, as stated by ORourkeand Sinnott (2006:857) interests as opposed to ideology. Interest-based (orrational choice) arguments typically focus on the link between the labor marketand anti-immigration attitudes. Because immigrants are often recruited tomeet labor market shortages, immigration often leads to competition withthe native-born (Olzak, 1992). Native-born people fear that immigrants willeither take over their jobs or depress their wages. Others emphasize that it is

not necessary that this competition be real, only that it be perceived (Raijman,Semyonov, and Schmidt, 2003; Semyonovet al., 2004).

Several scholars have noted that the threat posed by immigration isusually unequally distributed in the receiving society. In the case of the U.S.,the low-skilled should oppose immigration because much immigration tothe U.S. is by low-skilled people (Scheve and Slaughter, 2001). This effectshould be magnified when low-skilled individuals live in immigrant gatewaycommunities (Scheve and Slaughter, 2001).2 Mayda (2006) extends these

2Scheve and Slaughter derived these hypotheses by applying economic theory about therelationship between immigration and wages (the Heckscher-Ohlin [H-O] trade, factor-proportions-analysis [FPA], and area analysis [AA] models to attitudes. The first hypothesis


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ideas to explain cross-national variation in the relationship between labormarket skill and attitudes. She posits that the low-skilled will only be more likely

to oppose immigration in countries where immigrants are disproportionatelylow-skilled (which tends to be the case in countries with high GDP). Whenimmigrants are high-skilled (countries with low GDP), then those who arehigh-skilled will be most likely to oppose immigration.

Ideology-based explanations of attitudes focus on beliefs. Anti-immigrationviews reflect a larger set of beliefs about the native-born being superior topeople who are culturally and/or racially different. From this perspective, thedesire to curb immigration is part of a larger tendency toward racism and

xenophobia (see, e.g., Gutierrez, 1995; Dustmann and Preston, 2004). Otherexplanations that emphasize the role of ideology offer a somewhat more benignview of what it means to be anti-immigration. Being anti-immigration couldrepresent an isolationist political view that has little association with any senseof superiority toward immigrants per se.3

Whether interests or ideology generate attitudes has different publicpolicy implications. As Simmons and Keohane (1992) note in their study ofCanadian immigration policy makers, government representatives/workers seekto promote immigration as there is basic agreement (at least among those noton the extreme right) that at the state level, immigration is largely beneficial.However, policy makers are also acutely aware that the public is not alwayson side and, for this reason, seek to minimize the potential conflict relatedto immigration (Simmons and Keohane, 1992). If anti-immigration sentimentstems from economic issues then governments can respond with economicpolicies that minimize the negative effect (or perceived negative effect) ofimmigration (ORourke and Sinnott, 2006). However, if anti-immigrationattitudes stem from ideology then other strategies such as public information

campaigns may be necessary.

Empirical Evidence

Individual Characteristics. Several studies have examined whether there is anempirical relationship between individual economic interest and attitudestoward immigration. Among the most often used indicators of economic

is derived from the H-O and FPA models and the second hypothesis (immigrant gateway) isderived from the AA models. Scheve and Slaughters empirical results only support the firsthypothesis.3Simon and Lynch (1999), though not discounting the role of racism, review this argument.


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interest are occupational skill, union membership,4 and subjective feelingsabout the economy. Scheve and Slaughter (2001) find that among the employed,

those at the bottom of the job hierarchy (the less skilled) and union membershave a stronger aversion to immigration than the high-skilled and nonunionmembers. Tucci (2005) also finds that blue-collar workers and civil servants areless accepting of immigration than other white-collar workers. Gang, Rivera-Batiz, and Yun (2001) compare two groups distinguished by whether theyengage in labor force competition with immigrants and find that those whocompete hold more anti-immigrant attitudes. Results from other studies alsosuggest that a persons feelings about where they stand economically are

more important than their actual position. Hernes and Knudsen (1992)and Tucci (2005) find that feelings of economic deprivation are related toanti-immigration attitudes. Citrin et al. (1997), Chandler and Tsai (2001), andPantoja (2006) all find that being pessimistic about the state of the nationaleconomy increases anti-immigrant attitudes. Although the above studiesshow an effect of economic interest, a number of studies find no effect for

workers occupation (Hernes and Knudsen, 1992; Citrin et al., 1997), unionmembership (Citrin et al., 1997; Pantoja, 2006), or personal views on thestate of the economy.

In contrast to explanations that focus on material self-interest, explana-tions rooted in ideology focus on an individuals political orientation. Somecase studies show that political conservatives want less immigration (Espen-shade and Hempstead, 1996; Citrin et al., 1997; Chandler and Tsai, 2001;Scheve and Slaughter, 2001)5 and that people on the left want more immigra-tion (Fortin and Loewen, 2004).6 Patriotism increases anti-immigrationattitudes (Mayda, 2006; ORourke and Sinnott, 2006), though this finding isnot uniform (see, e.g., Heath and Tilly, 2005). Cosmopolitan Americans, that

is, those who have lived abroad and who reject the idea that the world wouldbe a better place if people from other countries were more like Americans, havealso been found to have more positive attitudes toward immigrants (Haubert

4The empirical studies we reviewed do not have a strong theoretical focus on unions. However,unions, as representatives of organized labor, have, at least historically, sought to controlthe supply of labor by restricting immigration (Quinlan, 1979). This is the likely reason

why, where possible, most studies do include union membership as a predictor of attitudestoward immigration.5Although Citrin et al. find that while ideological identification (from liberal vs. conservative)has an effect, party identification (Democrat vs. Republican) has no effect.6However, Fortin and Loewin find that people on the right do not have views that are statisticallydifferent from those who are more moderate.


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and Fussell, 2006:497). Dustmann and Preston (2004) find that racism is akey factor driving negative attitudes, especially for those with low skills and

education. In contrast people who hold egalitarian and humanitarian valuesare more likely to support increasing immigration (Pantoja, 2006).

In addition several other factors affect attitudes. Women (Palmer, 1996)and older people are less supportive of immigration (Gang, Rivera-Batiz, and

Yun, 2001). In the case of women this has been linked to their more tenuouslabor market positions, though most studies we review provide little in the wayof explanation for the effect of gender (but seeORourke and Sinnott, 2006).Hispanics tend to be more supportive of immigration (Citrin et al., 1997) as

do immigrants themselves (Haubert and Fussell, 2006), both likely due to asense of shared experience and affinity. Finally, almost every study finds thatincreases in education (net of other factors) are related to greater support forimmigration (Gang, Rivera-Batiz, and Yun, 2001; Tucci, 2005; Haubert andFussell, 2006; Pantoja, 2006). However, the meaning scholars attribute to theeffect of education varies. Some scholars view education as a marker for labormarket competitiveness (Mayda, 2006).7 Others (Dustmann and Preston,2004) suggest that education indicates the ideology (racism) of the less educatedand the interest concerns (labor market competition) of the more educated.

Context. The above discussion about the effect of interest and ideologicalcharacteristics focused on the individual level. However, a few studies havealso considered the link between context and individual attitudes. To date thesehave largely defined context in economic rather than ideological terms.8

Facchini and Mayda (2006), Mayda (2006), and ORourke and Sinnott(2006) find that the state of a countrys national economy (GDP) andimmigrant-to-native skill ratio modify the effect of individual characteristics

on attitudes.9 For example, ORourke and Sinnott (2006) find that for thosein the labor force, being high-skilled has more of an effect in rich countriesand in countries with more equal wealth distribution than it does in poor

7Mayda drew this conclusion because her data show that education has no effect for those notin the labor force.8The lack of information on ideological context and attitudes is a limitation to the above(and to our own) study. For example, Semyonov, Raijman, and Gorodzeiski (2006) have shown

that the ideological political climate in European countries is associated with individualanti-foreigner sentiment (see alsoWilkes, Guppy and Farris 2007).9Because of the modeling techniques used in these three studies no main effects of the country-level contexts were provided (seeFacchini and Mayda, 2006:20 for discussion).


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countries and countries with more inequality. Mayda (2006) also finds thatthe effect of being high-skilled (either in terms of occupation or high

education) on pro-immigration sentiments increases with country-level GDPand the immigrantnative skill ratio.10 Finally, Facchini and Maydas (2006)results show that an increase in the relative skill ratio of immigrants to nativesdecreases the effect of income on attitudes. That is, while higher income peopletend to favor immigration, this effect is smaller when immigration is unskilled.In contrast, Card, Dustmann, and Preston (2005) show little effect of acountrys percent foreign-born, GDP, and unemployment rates on individualattitudes. Scheve and Slaughter (2001) also find little direct effect of context

(in this case the percent foreign-born in different locations in the U.S.) or as amoderator of a low-skilled effect.While the above studies provide important empirical tests of the link

between context and attitudes toward immigration, the time element is absent.Time is important. With time we can consider how changes in the contextwithina country affect attitudes. That is, time allows for a consideration ofchanges in context. For example, one country could typically always be betteroff than another but there can still be volatility in the economy from year toyear. Few if any studies have considered this scenario. We illustrate this pointin Table 1, which presents a summary of existing empirical studies 11 thatexamine attitudes toward immigration policy and whether and to what extentthey consider time.

As shown in the third and fourth columns of this table, only fivestudies (Palmer, 1996; Citrin et al., 1997; Gang, Rivera-Batiz, and Yun, 2001;Scheve and Slaughter, 2001; Dustmann and Preston, 2004) include measuresthat vary across time. Only four of these (Palmer, 1996; Citrin et al., 1997;Gang, Rivera-Batiz, and Yun, 2001) attempt to explain the relationship

between time and attitudes; yet even these studies are limited. Citrin et al.(1997) and Gang, Rivera-Batiz, and Yun (2001) both make the importantcontribution of looking at changes in the role that individual characteristics

10Increases in the skill ratio between natives and foreign-born (that is, the more skilled the native-born are compared to immigrants) increase the likelihood that the native-born will supportimmigration.11We only include those studies that have a dependent variable that asks about increasing ordecreasing immigration levels and that use multivariate analysis to look at the factors associated

with this. Thus some other important studies on attitudes that use other methods (Diamond,1998; Simon and Lynch, 1999) are not included on this list.


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TABLE 1

SUMMARY OF HOWCONTEXT IS OPERATIONALIZED

Authors Location Year Data Collected Time

Hernes and Knudsen (1992) Norway 1988 n.a.Espenshade and Hempstead (1996) US 1993 n.a.Palmer (1996) Canada 19891992 YesCitrin et al. (1997) US 1992, 1994 SomeScheve and Slaugther (2001) US 1992, 1994, 1996 ModestChandler and Tsai (2001) US 1994 n.a.Dustmann and Preston (2004) UK 19831990 Not mentionedFortin and Loewen (2004) Canada 2000 n.a.Heath and Tilley (2005) UK 2003 n.a.

Mayda (2006) Multiplea 1995, 19951997 n.a.Gang et al. (2001) Europe 1988, 1997 Yes Tucci (2005) Germany 1998, 2000 n.a.Card, Dustmann, and Preston (2005) Europeb 2002 n.a.Pantoja (2006) US 1996 n.a.ORourke and Sinnott (2006) Multiplec 1995 n.a.Facchini and Mayda (2006) Multiple 1995 n.a.

Notes: aISSP survey countries include Australia, West Germany, East Germany, Great Britain, the USA, Austria, Hungary, Italy, Ireland, thSlovenia, Poland, Bulgaria, Russia, New Zealand, Canada, the Philippines, Japan, Spain, Latvia, and Slovakia.bEurobarometer survey countries include Austria, Belgium, Denmark, Finland, France, Germany, Ireland, Italy, Luxembourg, thecAustria, Belgium, Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Ireland, Israel, Italy, Luxembourg, thSpain, Sweden, Switzerland, Turkey, and the UK.


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play over time.12 However, because they only include two time points, andbecause of the methods they use (both studies are based on analyses of each year

separately), they cannot assess whether changes in context over time impactattitudes. Conversely, while Palmer (1996) examines context by comparingpooled data over multiple years, his study does not include the individual occu-pational or political characteristics that are so key in the literature, nor does heexamine alternative explanations for the effect of context. In order to addressthis gap in terms of our understanding of the role of changes in national contextover time, we take advantage of a unique data set that has attitudinal data at17 different time points between 1975 and 2000. The structure of this data set

enables us to consider the effect of individual-level characteristics, to consider theeffect of the variations in national context, and to consider the possibility thatcontext affects the role that individual characteristics play (interaction effect).

Hypotheses

We generate and test hypotheses about interest versus ideology at theindividual level and about interest at the contextual level. At the individuallevel, support in favor of an interest-based explanation would occur if we findthat occupational skill affects attitudes. Although most previous researchsuggests that it is the low-skilled who tend to be more opposed to immigration,the Canadian case may not fit the model because the Canadian state haseffectively recruited highly skilled immigrants.13 On the one hand, this wouldsuggest that the highly skilled would be more likely to oppose immigration. Onthe other hand, many highly skilled immigrants in Canada have the problemof credentials recognition and end up in lower-level jobs than they are qualifiedfor (Reitz, 2001), suggesting competition in this latter domain. For this reason

12They distinguish between characteristics and coefficient effects. A characteristics effect refersto changes in the characteristics of a population over time, such as more educated people in apopulation generating more pro-immigration attitudes, and a coefficient effect refers to the effectof a particular characteristic on attitudes changing over time, such as education having a largeror smaller effect over time. Gang et al. find that coefficient effects have a stronger impact thancharacteristics effects. For example, in 1997 education played a weaker role in reducinganti-immigrant attitudes than it did in 1988.13The majority of immigrants to Canada are admitted through the economic class, where anindividuals contribution to the economy is critical (approximately 130,000140,000 annual

entrants). Entry depends upon a point system, whereby prospective new Canadians areawarded scores based mainly upon their education, language skills, occupational training andexperience, and age. Others are admitted through the family and refugee categories, thoughof course many of those admitted through these latter categories are also highly skilled.


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it is less clear whether the skilled or the unskilled will hold less favorableattitudes toward immigration (compared to those not in the labor force). We

therefore expect that skill will matter but do not specify which group. We alsoexpect that if attitudes are caused by interests, then if they are in the labor force,the following groups will hold less favorable attitudes toward immigration:older workers, women, the less-educated, and union members. For those notin the labor force these group distinctions will have no effect ( see, e.g., Mayda,2006). If the evidence runs in favor of an ideology-based explanation for attitudestoward immigration then we expect to find that political orientation affectsattitudes (the politically conservative will be less favorable toward immigration)

and that labor force status (in the labor force versus not in the labor force) willnot be consequential. We also expect that factors such as age, gender, andeducation will remain significant even when we control for labor force status.

The above hypotheses are all about the effect of individual-level charac-teristics. As stated previously we also assess the role of context. In particular

we focus on the role of the economy and the rate of immigration. These canoperate in a number of ways. First, they can have an independent effect onattitudes. Given the findings of previous research we expect to find that attitudestoward immigration become more positive when the economy is good and thatattitudes become more negative during economic downturns. Economicdownturns, especially when coupled with rising immigration, are also expectedto generate prejudice because they increase competition between minority andmajority group members (see e.g., Olzak, 1992; Myers, 1997). We also expectto find that the higher the immigration rate, the less the support forimmigration. Second, these contextual conditions can modify the effect ofindividual-level characteristics. For example, if we find that changes in theeconomy and/or the immigration rate increase the effect that being in the

labor force has on attitudes (due to increased competition) then we would havesupport for an interest-based argument.

Data

Data for this paper come from multiple data sets collected by the Galluppolling organization in 17 separate surveys spanning a 25-year interval from1975 to 2000. These surveys are ideal because they contained an identical

question on immigration policy as well as the important independent variablesfor our study (seebelow). Samples of approximately 1,000 people, representativeof the noninstitutionalized Canadian population, over the age of 17, weresurveyed each time. We merged these surveys to create a pooled data set with


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a final sample size of 14,346 (after cases with missing data and those who werestudents14 were omitted). While the immigration question had exactly the

same wording and almost exactly the same response categories from year toyear, this was not the case for some of our independent variables. Although themajor categories for the latter did not change from year to year,15 in some casesmore detailed information had to be collapsed to ensure continuity over time.

MEASURES

Attitudes toward Immigration

Much of the literature on attitudes toward immigration policy relies on surveyquestions that ask respondents if they would like to see levels of immigrationincreased, decreased, or stabilized (e.g., Espenshade and Hempstead, 1996;Citrin et al., 1997; Chandler and Tsai, 2001; Dustmann and Preston, 2004;Pantoja, 2006). The question on immigration that we used asked respondents:If it were your job to plan an immigration policy for Canada at this time,

would you be inclined to increase immigration, decrease immigration, or keepthe number of immigrants at about the current level? The responses werecoded as increase, decrease, same level, and dont know. We coded the dontknow (about 45 percent in most years) as missing. Although the responsecategories of our question are similar to those used elsewhere (e.g., Espenshadeand Hempstead, 1996; Tucci, 2005; Mayda, 2006) it should be noted that the

wording of our question is slightly different in that it asks the respondentsviews on immigration policy as a planner as opposed to as an individual.16

Figure I graphs the responses to these questions at five-year intervalsbetween 1975 and 2005.17 This figure shows that in recent years Canadianshave become more supportive of increasing immigration levels. This figure

also shows that there is reasonable stability among the Canadian public in thepercentage of respondents feeling that immigration levels should remain the

14We follow Card, Dustmann, and Preston (2005) and omit students due to the uncertaintyabout their final educational and occupational attainments.15Typically an explicit dont know category was included but on a few occasions this category

was not explicitly mentioned to respondents.16Though it might be expected that, as a planner, an individuals relative labor market positionis irrelevant, the results of our paper (seebelow) show that the individual characteristics that are

associated with attitudes in our study largely mirror those found in other studies that use slightlydifferent questions.17Although we were able to obtain 19752005 data for attitudes, our subsequent multivariateanalyses are limited to 19752000 due to missing data on key variables for 2005.


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same. Finally, we also see that whereas in the 1970s and 1980s sentiment fordecreasing immigration ran at least twice as high as support for increasedimmigration, by 2005 these positions were virtually deadlocked (with a majority

wanting levels to remain the same).

Individual Characteristics

Our primary measures of economic position are occupational skill andbelonging to a union household. The original Gallup surveys provided a rangeof occupational categories which we then coded as belonging to one of tencategories that were consistent across years.18 We then coded those respondents

whose occupations were professional and business categories as being higher-skilled and those whose occupations were in sales, clerical, skilled labor,and unskilled labor as lower-skilled. We coded homemakers, retired, andunemployed as not in the labor force. Respondents were coded as being in a union

household if they and/or their spouse were a union member. The ideologicalvariables are a series of dummy variables indicating whether a respondentstated that they would vote for (at the time of the survey) Conservative,Liberal, New Democratic, or Other.19 During some of the years under

18The ten categories that were consistent across all time periods were professional, business, sales,clerical, skilled labor, unskilled labor, homemakers, retired, unemployed, and students. In someyears there were other categories that we had to merge into one of the above categories. Forexample, in some years there was an additional category: farmworkers. We coded these cases into

the unskilled labor category.19The Other category includes those who would vote Bloc Quebecois (this could not be includedseparately as it was not available for all years), those who would vote for other parties, those who

were unsure, as well as those who did not plan to vote.

Figure I. Canadian Views on Immigration Levels, 19752005


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consideration two major political parties were established in Canada: the rightwing Reform Party (est. 1987), which emerged in the western provinces, and

the separatist Bloc Quebecois (est. 1990), which emerged in Quebec. Werecoded voting for the Reform Party as Conservative and voting for the Blocas voting for other parties.20 Education is coded into four categories indicatingthe highest level completed: elementary school or less, high school, college/trades, and university.21

We also included various demographic characteristics including gender,age, and first language (English, French, other language). Although nomeasure of the respondents immigrant/native-born status was available, we

believe that the majority of those who speak other languages as a first lan-guage are likely immigrants.22 With the exception of age all other variables aredummy-coded.

Table 2 presents the percentage of respondents who want levels ofimmigration to decrease, stay the same, or increase, for each of the variablesincluded in our study. Education level shows the strongest association withindividual attitudes; people with university educations are twice as likely asthose with only elementary education to want more immigration (21% vs.9%). Conversely, people with only elementary or high school education areamong those wanting less immigration (about 49% each). Among those

wanting to see more immigration, the highest percentage is found with peoplewhose first language is neither English nor French.

National Context

At the national level we included measures of the economic context and theimmigration rate. The economic context is measured by the yearly unemployment

20Our use of voting intention to measure political orientation differs from previous studies thatmeasure political orientation using a left-right scale (no such scale measure was in the Gallupdata sets). However, a number of recent studies of the link between political orientationand party support as applied to European societies suggest a strong link with attitudes towardimmigration/immigrants (e.g., Carter, 2005). Also recall that in some years our measure ofConservative party support also includes those who intended to vote for the Reform Party, whichdid have a highly visible anti-immigration platform. Nevertheless, we acknowledge that this linkhas yet to be established empirically within the Canadian context and our results shouldtherefore be interpreted with this caveat in mind.21In Canada college refers to community colleges that offer 2-year degrees. University in Canadarefers to institutions offering 4-year degrees.22With some slippage for immigrants who spoke English and French first and for Aboriginalpeople who may have learned an Aboriginal language first.


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rates and GDP. The GDP data come from Heston, Summers, and Aten (2002)and the Canadian unemployment rates were obtained through the CanadianSocioeconomic Information Management Database (CANSIM, 2008). Theimmigration rate is calculated as the rate of new permanent residents per 1,000

Canadians (seeVeugelers and Klassen, 1994). The data for this measure wereobtained from Statistics Canada (2005).

Table 3 presents the annual contextual measures, the changes in the con-textual measures from the previous year, as well as, for each year available, theimmigration attitude scores aggregated to the national level. Of note is the factthat in 1982 and 1991 there were economic recessions as demonstrated by thehuge rise in unemployment rates (increased by 3.4% between 1981 and 1982and increased by 2.1% between 1990 and 1991) and declines in GDP

(declined by $1,094 per capita between 1981 and 1982 and declined by $883per capita between 1990 and 1991). Furthermore, these recessions seem tocoincide with very sharp change in the levels of wanting immigration todecrease (more than 10% change).

TABLE 2PERCENTAGEOF EACH GROUP WHO WANT GIVEN LEVELSOF IMMIGRATION, 19752000

Less Same More NGender

Male 42.36 43.07 14.57 7,068Female 43.8 46 10.2 7,278

LanguageEnglish 46.72 42.14 11.14 8,883French 40.92 48.32 10.76 3,812Other languages 28.59 48.88 22.53 1,651

Education (Highest Level Completed)Elementary school 48.53 42.79 8.69 1,865High school 48.58 42.47 8.95 6,035College/trades 41.94 46.25 11.82 3,224

University 30.81 47.73 21.46 3,210Occupational Characteristics

Union household 44.25 44.56 11.19 4,219Nonunion household 42.61 44.55 12.84 10,127Higher skill 36.61 46.69 16.7 3,761Lower skill 46.36 43.33 10.51 5,569In labor force 42.43 44.68 12.88 9,330Not in labor force 44.32 44.32 11.36 5,016

Vote TodayConservative/Reform 47.9 40.57 11.53 3,002Liberal 38.28 47.64 14.08 4,305New Democratic Party 44.49 41.23 14.28 1,870

Other politics 44.38 45.04 10.58 4,727Total 43.09 44.56 12.35 14,346


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TABLE 3ATTITUDES TOWARD IMMIGRATION OVERTIME, 19752005, AND YEARLYCONTEXTUAL MEASURES

Year

Immigration Levels Should Be:

CanadianPopulation

Immigrantsper Year

Immigration

Rate per 1,000Canadians

Change in

ImmigrationRate

UnemploymeRateLess More Same N

1974 22,808,446 218,465 9.58 5.31975 42.92 10.79 46.29 980 23,142,275 187,881 8.12 1.46 6.91976 23,449,793 149,429 6.37 1.75 7.11977 23,726,345 114,914 4.84 1.53 81978 23,963,967 86,313 3.60 1.24 8.41979 24,202,205 112,096 4.63 1.03 7.51980 43.65 9.15 47.2 991 24,514,278 143,117 5.84 1.21 7.51981 24,820,382 128,618 5.18 0.66 7.61982 56.41 6.76 36.82 1034 25,117,424 121,147 4.82 0.36 11

1983 25,366,965 89,157 3.51

1.31 121984 25,607,555 88,239 3.45 0.07 11.31985 44.88 14.22 40.9 974 25,842,590 84,302 3.26 0.18 10.61986 26,100,587 99,219 3.80 0.54 9.71987 43.54 12.18 44.27 974 26,449,888 152,098 5.75 1.95 8.81988 41.97 14.76 43.26 1003 26,798,303 161,929 6.04 0.29 7.81989 36.10 14.17 49.72 958 27,286,239 192,001 7.04 0.99 7.61990 34.17 18.16 47.67 1001 27,700,856 214,230 7.73 0.70 8.21991 47.44 13.84 38.72 1001 28,030,864 230,781 8.23 0.50 10.31992 47.53 12.98 39.49 992 28,376,550 252,842 8.91 0.68 11.21993 47.00 10.68 42.32 955 28,703,142 255,819 8.91 0.00 11.41994 29,035,981 223,875 7.71 1.20 10.4

1995 45.87 8.89 45.25 969 29,353,854 212,504 7.24

0.47 9.61996 43.16 9.8 47.04 935 29,671,892 225,773 7.61 0.37 9.71997 43.88 10.56 45.56 952 29,987,214 216,038 7.20 0.40 9.21998 35.46 12.38 52.16 958 30,247,949 174,195 5.76 1.45 8.41999 30.85 16.61 52.54 976 30,493,433 189,957 6.23 0.47 7.62000 34.03 18.04 47.93 978 30,750,087 227,459 7.40 1.17 6.8

Note: GDP adjusted 1996, constant prices, Laspeyres.


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Methods of Analysis

First we consider the role of individual characteristics on individual attitudesfor each year separately. Our primary dependent variable has three categories(decrease, stay the same, and increase). The convention in the literature is totreat these as ordered and then use the ordered probit model (see alsoEspenshade and Hempstead, 1996; Tucci, 2005; Mayda, 2006). However, thismodel assumes that the logits are equal across categories of the dependentvariable. For example, this would mean that the size and significance level ofthe logits for union household (and all other variables) are the same whether

one wants less, the same, or more immigration (called the proportionalodds assumption). In order to make this assumption, the score test for theproportional odds assumption has to be nonsignificant (see alsoFortin andLoewen, 2004; Fong and Ooka, 2006). However, our initial tests indicatedthat the score test was statistically significant, indicating the inappropriatenessof the ordered probit model. For this reason we use binary logistic modelsfor each contrast. Although the convention is to present two out of the threecomparisons, given the results from the proportional odds test, we include allthree.

Second, we consider the role of individual characteristics and nationalcontext over time. This required merging the series of cross-sectional samplesinto a single data set. It also required taking into account the possibility ofcorrelated error between individuals within a particular year. For these reasons

when we analyze the merged data set we use GEE (generalized estimatingequations) models that consider three possible contrasts (less vs. more, more vs.same, and less vs. same), with year treated as a repeated measure. These equa-tions were estimated using SAS Proc Genmod with repeated statements. All

equations were weighted (standardized by Gallup to match national genderand age distributions) using the weight variable provided in each of the yearlydata sets (except 1975).

Third, in the final part of our analysis we use time series regressionmodels to look at the effect of changes in the national-level conditions (GDP,unemployment, and immigration rate) on changes in attitudes. For theseanalyses we constructed three continuous dependent variables: the change inthe percentage who think levels should be decreased, the change in the

percentage who think levels should be increased, and the change in thepercentage who think they should stay the same. The national-level conditions

were then regressed on these attitudinal measures. These equations wereestimated using the Autoregressive Times Series Module in SPSS.


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FINDINGS

In Table 4 we present the results from logistic models for the associationbetween individual characteristics and attitudes. For each year we show threemodels of the association between the individual characteristics and the logodds of wanting immigration levels to be less (as opposed to more), more(as opposed to the same), and less (as opposed to the same). We describe theresults for 1975 as an example of yearly effect, and then make some generalobservations about the remaining years. First, men and those who have anonmajority first language are less likely to want to restrict immigration than

are women or those with English/French as a first language. These models alsoshow that as people age they are more likely to want to restrict immigration.Education also has a strong association with the less vs. more and more vs. samecategories. Those with elementary school are most likely to want to restrictimmigration. The voting intention measures show only that those who say they

would vote Conservative are less supportive of immigration compared toLiberals but the results for 1975 show little difference between New Democratsand those who have Other political intentions. Finally, with respect tooccupation the results for 1975 show that union household members are moreanti-immigration than nonunion household members but that occupationalskill level has little effect.

We conclude our discussion of this table by making several observationsabout patterns across years. First, if a characteristic is significant in a given yearthe results show that it is in the same direction as in other years.23 For example,

when it is statistically significant, lower levels of education are always associatedwith wanting less immigration. This indicates that we can be very confidentabout the relationships between individual characteristics and attitudes.

Second, most characteristics do not show a consistently significant associationfor every year. Thus the strength of these associations varies across years.

Table 5 presents the results from the GEE models predicting the associ-ation between individual and contextual characteristics and attitudes for allyears combined. The first three models contain only the individual-level charac-teristics, the second three add the national context, and the third three addinteraction terms between skill level and context. The results for the individualcharacteristics models show that both interests and ideology affect attitudes.

23The only exceptions are union membership, which has a negative effect in 1980 for the less vs.same contrast and a positive effect in 1987, and male gender, which has a positive effect for thiscontrast in 1992.


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TABLE 4LOGISTIC REGRESSION MODELSFORINDIVIDUALATTITUDESTOWARD IMMIGRATION

1975 1980 1982Less vs.More

More vs.Same

Less vs.Same

Less vs.More

More vs.Same

Less vs.Same

Less vs.More

More vs.Same

Intercept 1.74* 1.67* 0.06 0.76 0.84 0.10 1.43* 1.51*Demographic

Male 0.67* 0.55* 0.04 0.57 0.22 0.30 0.01 0.24Age 0.02* 0.01 0.01* 0.01 0.00 0.01 0.01 0.00Non English/French language 1.02* 0.23 0.84* 1.35* 0.44 1.04* 0.89* 0.65

Education (vs. University)Elementary school 1.88* 1.12* 0.57* 1.10* 0.72 0.11 1.13 0.94High school 1.15* 0.85* 0.29 1.64* 0.98* 0.50 0.62 0.53College/trades 1.50* 0.94* 0.21 1.26* 1.01* 0.20 0.67 0.72

Vote Today (vs. Liberal)Conservative/Reform 0.93* 0.35 0.45* 0.70* 0.03 0.68* 0.06 0.53

New Democratic Party 0.77

0.33 0.23 0.63

0.42 0.21 0.11 0.41Other politics 0.27 0.04 0.05 0.22 0.01 0.15 0.27 0.36

Occupation (vs. Not in Labor Force)Higher skill 0.78 0.43 0.11 0.57 0.67 0.26 0.48 0.40Lower skill 0.06 0.15 0.10 0.33 0.12 0.35 0.12 0.13

Union Household 0.87* 0.65* 0.09 0.17 0.14 0.39* 0.30 0.25Log Likelihood 206 229 539 181 198 502 175 155N 477 511 796 457 477 772 561 379

1987 1988 1989

Less vs.More

More vs.Same

Less vs.Same

Less vs.More

More vs.Same

Less vs.Same

Less vs.More

More vs.Same

Intercept 1.92* 1.85* 0.01 0.70 1.15* 0.29 0.27 0.22Demographic

Male

0.98* 1.04*

0.01

0.49* 0.49*

0.07

0.31 0.40Age 0.02* 0.01 0.01* 0.01 0.01 0.00 0.01 0.00Non English/French language 0.92* 0.46 0.60* 1.79* 0.66* 0.88* 2.27* 1.09*

Education (vs. University)Elementary school 2.03* 1.23* 0.86* 2.06* 1.13* 0.55 1.67* 1.40*High school 1.60* 1.11* 0.51* 1.51* 0.86* 0.54* 1.53* 1.22*College/trades 0.81* 0.61 0.11 0.84* 0.65* 0.16 1.03* 0.94*


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Vote Today (vs. Liberal)Conservative/Reform 0.27 0.11 0.17 0.35 0.17 0.22 0.64 0.63*New Democratic Party 0.01 0.17 0.07 0.12 0.14 0.17 0.35 0.05Other politics 0.39 0.41 0.11 0.17 0.12 0.01 0.55 0.40

Occupation (vs. Not in Labor Force)Higher skill 0.74 0.43 0.11 0.44 0.46 0.11 0.19 0.25Lower skill 0.33 0.40 0.16 0.68* 0.45 0.21 0.03 0.08

Union Household 0.47 0.03 0.43* 0.22 0.11 0.26 0.79* 0.64*Log Likelihood 208 219 499 228 249 477 218 270N 486 483 759 491 496 741 441 563

1991 1992 1993

Less vs.More

More vs.Same

Less vs.Same

Less vs.More

More vs.Same

Less vs.Same

Less vs.More

More vs.Same

Intercept 1.26*

0.97 0.12 0.61

1.58*

1.10* 1.95*

2.52*Demographic

Male 0.48* 0.69* 0.08 0.10 0.54* 0.36* 0.92* 0.95*Age 0.02* 0.00 0.02* 0.00 0.01 0.01 0.02 0.02*Non English/French language 1.04* 0.48 0.51* 0.91* 0.72* 0.35 0.68 0.30

Education (vs. University)Elementary school 2.99* 2.19* 0.90* 2.33* 1.92* 0.47 2.08* 1.12High school 1.27* 0.61* 0.69* 1.29* 0.64* 0.72* 0.97* 0.47College/trades 0.56 0.19 0.40 1.06* 0.46 0.57* 0.42 0.02

Vote Today (vs. Liberal)Conservative/Reform 0.07 0.48 0.70* 0.31 0.32 0.64* 1.25* 0.55New Democratic Party 0.14 0.80* 0.67* 0.09 0.15 0.21 2.35* 1.10*Other politics 0.32 0.11 0.41* 0.14 0.09 0.15 0.18 0.06

Occupation (vs. Not in Labor Force)

Higher skill 0.15

0.59

0.41

0.17 0.29 0.19 0.10 0.00Lower skill 0.59 0.79* 0.21 0.11 0.07 0.01 0.12 0.05

Union Household 0.10 0.01 0.13 0.06 0.18 0.01 0.33 0.14Log Likelihood 256 251 519 237 223 504 191 198N 564 487 791 537 448 767 474 424

1987 1988 1989

Less vs.More

More vs.Same

Less vs.Same

Less vs.More

More vs.Same

Less vs.Same

Less vs.More

More vs.Same

TABLE 4(CONTINUED)LOGISTIC REGRESSION MODELSFORINDIVIDUAL ATTITUDESTOWARD IMMIGRATION


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1996 1997 1998

Less vs.More

More vs.Same

Less vs.Same

Less vs.More

More vs.Same

Less vs.Same

Less vs.More

More vs.Same

Less vs.Same

Less vs.More

Intercept 0.72 2.17* 1.64* 0.98 2.12* 1.29* 0.13 1.15 0.59 0.22Demographic

Male 0.58 0.35 0.02 0.18 0.11 0.09 0.01 0.22 0.23 0.13Age 0.01 0.00 0.02* 0.00 0.01 0.01 0.01 0.00 0.00 0.00Non English/French language 1.03* 0.58 0.25 0.95* 0.57 0.09 0.92* 0.72* 0.24 1.66*

Education (vs. University)

Elementary school 0.55

0.07 0.27 2.14*

1.84* 0.13 1.18

0.67 0.41 1.34*High school 1.23* 0.44 0.53* 1.29* 0.81* 0.42 0.86* 0.39 0.40 1.16*College/trades 1.12* 0.74* 0.21 1.22* 0.93* 0.23 0.94* 0.63 0.24 0.58*

Vote Today (vs. Liberal)Conservative/Reform 0.52 0.02 0.60* 0.06 0.21 0.39 0.13 0.29 0.38 0.86*New Democratic Party 1.01 1.08* 0.49 0.83 0.06 0.64 1.24* 0.73 0.43 0.51Other politics 0.48 0.07 0.52* 0.14 0.07 0.54* 0.21 0.42 0.22 0.40

Occupation (vs. Not in Labor Force)Higher skill 0.35 0.68 0.29 0.51 0.39 0.18 0.20 0.10 0.14 0.18Lower skill 0.11 0.29 0.27 0.28 0.64 0.60* 0.19 0.16 0.17 0.18

Union Household 0.51 0.10 0.22 0.34 0.05 0.47* 0.12 0.37 0.15 0.28Log Likelihood 167 180 468 182 202 465 196 229 456 226N 424 429 711 442 442 728 380 493 687 390

Note: *p < .05.

TABLE 4(CONTINUED)LOGISTIC REGRESSION MODELSFORINDIVIDUAL ATTITUDESTOWARD IMMIGRATION


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TABLE 5GEES MODELING INDIVIDUALAND CONTEXTUAL EFFECTSON ATTITUDESTOWARD IMMIGRATI

Individual Individual and Context

Less vs.

More

More vs.

Same

Less vs.

Same

Less vs.

More

More vs.

Same

Less vs

SameIntercept 0.76* 1.17* 0.43* 0.56 1.38* 1.0Demographic

Male 0.39* 0.41* 0.01 0.40* 0.41* 0.0Age 0.01* 0.00 0.00 0.01* 0.00 0.0Non English/French language 1.16* 0.58* 0.56* 1.19* 0.58* 0.

Education Completed (vs. University)Elementary school 1.46* 0.87* 0.55* 1.49* 0.87* 0.5High school 1.20* 0.72* 0.49* 1.23* 0.71* 0.4College/trades 0.78* 0.52* 0.25* 0.80* 0.52* 0.2

Vote Today (vs. Liberal)Conservative/Reform 0.41* 0.05 0.39* 0.42* 0.04 0.3

New Democratic Party 0.07 0.17 0.28* 0.06 0.18 0.2Other politics 0.26* 0.12 0.20* 0.27* 0.12 0.2

Occupation (vs. Not in Labor Force)Higher skill 0.08 0.02 0.08 0.07 0.02 0.0Lower skill 0.15* 0.11 0.07 0.16* 0.11 0.0

Union Household 0.18* 0.14* 0.04 0.19* 0.14* 0.0National Context

Unemployment rate 0.15* 0.02 0.GDP 0.04* 0.01 0.0Immigration rate (per 1,000 Cads) 0.03 0.01 0.0

Individual * Context InteractionsHigh skill * unemployment rate

Low skill * unemployment rateLog Likelihood 3,790 4,057 8,487 3,744 4,055 8,421N 7,989 8,198 12,629 7,989 8,198 12,629

Note: *p < .05.


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322 I M R

Working in lower-skilled occupations, belonging to a union household, andhaving non-Liberal voting intentions increase anti-immigration sentiment.

However, with the exception of belonging to a union household the absenceof these characteristics has little effect on pro-immigration sentiment. In thenext models, which add the economic and immigration contextual variables,

we can see that the state of the economy has a significant effect on attitudes.Increases in the unemployment rate increased the log odds of wanting lessimmigration. Conversely, higher GDP is associated with a decrease in the logodds of wanting less immigration. The immigration rate has no effect. It is alsonotable that the state of the economy has little effect on the more vs. same cat-

egories. This leads us to conclude that while poor economic times are associ-ated with wanting less immigration, good economic times do not de facto leadto wanting levels to increase. In the final three columns we add the interactionsbetween skill level and context. In these models we consider the interactionbetween higher- and lower-skilled occupations and the unemployment rate.Neither of these is statistically significant. We also ran additional models(results not shown) that replaced the unemployment rate with GDP and theimmigration rate. Again we found no evidence that the effect of skill level onattitudes depended on the state of the economy.

Table 6 contains the models for the effect of individual and context(without the interactions), broken down by labor force status. The first threemodels are for those who work in high-skilled occupations, the second threemodels are for those who work in lower-skilled occupations, and the final threeare for those who are not in the labor force. We make several points based uponthis table. First, contrary to findings elsewhere, education does affect attitudesfor those who are not in the labor force. Second, the effect of the economy isrelatively similar across occupation groups, mirroring the findings in the pre-

vious table that showed no significant interaction between labor force statusand the unemployment rate. Thus economic downturns do lead to changes inattitudes but these changes occur across the board rather than for specificgroups. Third, the results from this table provide some evidence as to what doesdistinguish these three groups and that is the role of ideology in the form ofvoting intentions. For the people who work in lower-skilled occupations,intending to vote Conservative/Reform and intending to vote Other have astronger effect on attitudes than they do on the attitudes of the people who

work in higher-skilled occupations and those who are not in the labor force.Also of note is that the meaning of voting NDP on attitudes varies by skill level.For the high-skilled voting NDP is associated with increased support for immi-gration whereas for the people who work in lower-skilled occupations and


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TABLE 6GEES CONTROLLINGFORLABORFORCE STATUS, 19752000

In Labor Force

High Skill Medium/Low Skill

Less vs.More

More vs.Same

Less vs.Same

Less vs.More

More vs.Same

Less vsSame

Intercept 0.61 1.65 1.19* 0.73 1.39* 0.7Demographic

Male 0.37* 0.37* 0.04 0.37* 0.37* 0.0Age 0.01* 0.01* 0.00 0.00 0.00 0.0Non English/French language 1.01* 0.40* 0.52* 1.34* 0.57* 0.7

Education Completed (vs. University)

Elementary school 1.78*

0.98* 0.66* 0.97*

0.41* 0.5High school 1.24* 0.77* 0.47* 1.06* 0.73* 0.3College/trades 0.88* 0.57* 0.33* 0.66* 0.56* 0.1

Vote Today (vs. Liberal)Conservative/Reform 0.31 0.09 0.44* 0.46* 0.06 0.3New Democratic Party 0.53* 0.53* 0.07 0.32 0.01 0.3Other politics 0.27* 0.06 0.21* 0.41* 0.26 0.2

OccupationUnion Household 0.22* 0.14 0.07 0.27* 0.22* 0.0National Context

Unemployment rate 0.18* 0.02 0.13* 0.14* 0.01 0.1GDP 0.03 0.01 0.04* 0.05* 0.03* 0.0

Immigration rate (per 1,000 Cads)

0.07 0.06 0.02 0.01

0.03 0.0Log Likelihood 1,065 1,268 2,013 1,408 1,449 3,421N 2,005 2,384 3,133 3,156 2,987 4,995

Note: *p < .05.


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those not in the labor force it is associated with decreased support forimmigration. This finding mirrors the point made elsewhere that peoplehave very different reasons for voting NDP; for those in the higher statusgroups voting NDP is associated with left-leaning postmaterialist values

whereas for those in lower status groups it is associated with protectingworking-class interests.

Next we examine the effect of national context on changes in attitudesover time. In Table 7 we present the results of three time series modelspredicting the change in the percent who think immigration levels shouldbe decreased, the change in the percent who think immigration levelsshould be increased, and the change in the percent who think levels shouldstay the same. Due to the high correlation between the change in theunemployment rate and the change in GDP we estimated models for each ofthese separately. These models show that changes in the economy (either

positive or negative) affect the change in the percent who want less or the samebut have no effect on the percent who think immigration levels should beincreased. As in the previous models a change in the immigration rate has noeffect on attitudes.

CONCLUSION

The joke we mentioned at the outset of this paper No Thanks, Were Full

suggests that new immigrants are as likely as native-born Canadians to wantless immigration. Our empirical analyses show that this joke has no basis inreality. People with a nonmajority first language hold much more positiveattitudes about immigration than do members of the majority group. This

TABLE 7AUTOREGRESSIVE TIME SERIES MODELS PREDICTING CHANGESIN ATTITUDES, 19752000

Change in % Change in % Change in %Want LessImmigration

Want MoreImmigration

Want SameImmigration

Constant 1.19 1.02 0.64 1.06 0.63 0.93AR1 0.38 0.39 0.11 0.18 0.41 0.30

Annual change in GDP 0.01* 0.00 0.00*Annual change in

unemployment rate 3.93* 1.12 2.89*Annual change in immigration

rate (per 1,000 Cads) 0.96 0.31 0.49 0.21 0.76 0.27LL 43.58 46.09 37.52 37.14 38.91 42.77

Note: N = 16, *p < .05.


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N T, W F 325

aside, the results of our study lead us to make two general points about thedeterminants of attitudes toward immigration.

First, one of the original contributions of this paper was to examine theeffect of context on attitudes. We argued that because most studies are basedon cross-sectional data they have been unable to fully examine the role thatcontext plays over time. In the research presented in this paper we were able totake advantage of a unique data set with information on attitudes in Canadabetween 1975 and 2000. To date, no study has been able to document attitudestoward immigration over such an extended time period, and examine contex-tual shifts, while also controlling for the individual factors that may affect these

attitudes. Our results show that some aspects of national context, in particularthe state of the economy (as indicated by both the annual unemployment rateand GDP), have a significant effect on attitudes. This effect of the economy didnot vary across groups rather it was an effect that was consistent acrossthe board. In contrast, we found little effect of annual variation in the rate ofimmigration. How to make sense of this finding? One interpretation is that theeffects of economic downturns are spread equally among groups. However,given that the immigration rate had no effect we believe the answer maybe more in line with Chavezs (2001) claim that during economic downturnsmedia coverage of immigration increases. Nevertheless, further research isclearly needed to delineate if this is the case.

Our second contribution was to compare the effects of variables designedto measure whether attitudes are caused by interests or whether attitudes arecaused by ideology. At first glance the results from our study do not allow usto make a conclusive statement in favor of one or the other set of factors. Forexample, at the outset we hypothesized that if attitudes were a reflection ofinterest then education would have no effect for those not in the labor force.

Yet there was a strong educational effect for this group. While this mightsuggest that we should favor an ideological explanation some of the measuresof interest, such as holding a lower-skilled occupation also mattered. Wecould have therefore concluded that they both matter (see alsoEspenshade andHempstead, 1996; Mayda, 2006).

However, a slightly different and clearer picture emerges once the fact thatmany of the variables did not have a uniform effect across contrasts of the dependantvariable (less vs. more, more vs. same, and less vs. same) is considered. For example,

while certain measures of occupation and voting preferences can distinguishthe less vs. same and less vs. more categories, they do not matter for the morevs. same contrast. That is, many of our findings suggest that rather than acontinuum, support and opposition are qualitatively different. We found this


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difference due to the fact that in contrast to most previous studies that treatthese attitudinal categories as a continuum (from decreased, stay the same,

increased), we treated these as distinct and separate categories (see alsoFortinand Loewen, 2004). We suggest that the less vs. more and less vs. same reflectanti-immigration sentiment whereas the more vs. same contrast reflectspro-immigration sentiment.

Thought of in this way we can then consider the possibility that thefactors that affect anti-immigration sentiment might differ from the factorsthat affect pro-immigration sentiment. Education, voting intention,occupation, and the national economy all distinguished the category wanting

less immigration from the other two categories. Our results therefore show thatinterest, ideology, and national economic context all affect anti-immigrationsentiment. On the other hand, while education and to some extent belongingto a union household affected the more vs. same categories, this was largelynot the case for voting intention, occupational skill level, or any of thenational contextual factors. Thus in the case of pro-immigration sentiment, weconcur with Haubert and Fussells (2006) recent point that its basis is largelyideological.

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No Thanks We re Full... Attitudes Toward Immigration