Order ID | 53563633773 |
Type | Essay |
Writer Level | Masters |
Style | APA |
Sources/References | 4 |
Perfect Number of Pages to Order | 5-10 Pages |
Effects of Recent Immigration from Those of Ethnicity
I had always suspected there was a problem; but then I got my proof. I sent in two copies of my CV, one with my actual (very ethnic sounding) name and the other with the most typical kiwi name I could think of, Sarah Smith. Sarah Smith got short-listed almost every time, but I never got a call using my own name.
I had provided a reference for a former student to public sector organisation. I got a call from the chair of the search committee after they had interviewed him, yelling at me because I hadn’t told them that he was “black.” His name was very British, and they were shocked when he walked in and didn’t look the way that they expected. They yelled at me for wasting their time, even though the candidate was much better qualified than the person that they ended up hiring.
While these anecdotes were collected in New Zealand, such stories are often dismissed as “one-offs”; surely they couldn’t represent anything else in a modern knowledge economy, with low unemployment and a tight labour market. And how could it happen in a nation that prides itself on a “level playing field” and that has one of the world’s most inclusive pieces of non-discrimination legislation?1
New Zealand has an increasingly diverse workforce, yet both the popular and academic press suggest persistent employment discrimination in New Zealand, particularly for ethnic minorities and immigrants.2 For minority applicants trying to “get a foot in the door,” the impersonality of resume or application based screening provides little opportunity for oversight or appeal. This makes the initial short- listing process particularly important, as bias in short-listing eliminates all subsequent opportunity for employment. This research investigates the effect of ethnicity on initial short-listing of job applicants, with particular attention to the cues for ethnicity that appear on the CV, including name and migration status.
Ellen Portch, Reagan, 2005, pencil on paper. Elam School of Fine Arts.
How do age, race, ethnicity and gender affect employment opportunties? Research identified differential “ethnic penalties” for Chinese and Indian applicants. Implications for practice and future research are discussed.
A rose by any other name: The effect of ethnicity and name on access to employment
by Marie Gee Wilson, Priyanka Gahlout, Lucia Liu and Suchitra Mouly
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Employment discrimination on the basis of ethnicity Employment discrimination occurs when job-irrelevant factors or characteristics (such as sex, age, ethnicity, or marital status) are taken into consideration while making an employment decision, violating the basic standard of fairness in employment.3 While discrimination may occur on a variety of job-irrelevant factors, in the face of increasing labor mobility across national borders, race and ethnicity have received increased attention.4
While North American studies have traditionally focused on issue of race, studies conducted in both the UK and U.S have indicated that Asian and other ethnic minority applicants remain disadvantaged when compared to non-minority “whites”5 in terms of job opportunities.6 This disadvantage manifests itself in terms of higher unemployment, under-representation in professions and lower earnings. Supporting this line of argument, Carmichael and Woods7 have argued that ethnic minorities pay an “ethnic penalty” in the competition for jobs, although the penalty varies considerably between minority groups.
In UK-based research,8 Asian applicants were the most disadvantaged when compared to British nationals, with other ethnic groups experiencing different levels of “ethnic penalty” across job seniority, salary levels, type of firm (multinational or local firm) and location. These are just two studies within a decades long research tradition that strongly support that, under most conditions, an “ethnic penalty” exists for job applicants from ethnic minorities. With the recent focus on Asian migration, government research has highlighted patterns that are similar to the UK results for ethnic Chinese and Indian New Zealanders.9 For employers, the influx of candidates from throughout Asia (including those of Indian and Chinese ethnicity) influences the mix of candidates who apply for jobs. Given the existing UK, US and New Zealand research, we might expect that:
Hypothesis 1. Ethnic Asian applicants of equal quality will be less likely to be shortlisted for employment than European/Pakeha applicants.
Impact of ethnic names on employment screening Many ethnic groups have names that are distinct and identifiable. Both the first name and last name can reveal the ethnicity of the person and activate stereotypes.10 Bertrand and Mullainathan11 sent 5,000 hypothetical resumes in response to a variety of advertisements in two major newspapers in the US. Names on the (otherwise identical) resumes were selected to sound either distinctively Anglo-
Saxon (e.g., Brendan Baker) or African-American (e.g., Jamal Jones). The study revealed that the fictitious job seekers with “white” names were 50 percent more likely to get calls for interviews. This study suggests widespread discrimination in the workplace against job applicants whose names were merely perceived as “sounding black.” In three studies in the UK, responses to Asian, West Indian and Anglo–Saxon names in written job applications resulted in significant influences on the selection decision, with different degrees of employment discrimination experienced by different ethnic groups.12 There are a number of reasons that names may prompt or increase discriminatory effects; ethnic names may signal a lack of assimilation, trigger more pronounced stereotypes, or may cause psychological discomfort because of pronunciation difficulties. Regardless of the rationale, name remains one of the most powerful signals of ethnicity in initial job screening. Based on the results of prior research, we might expect that having an ethnic name would increase the “ethnic penalty” for job applicants. Hypothesis 2. Ethnicity of name will increase the “ethnic penalty” in employment shortlisting.
Employment discrimination on the basis of immigrant status For many ethnic minorities, it is difficult to separate the effects of recent immigration from those of ethnicity in determining labor market biases. Refugee communities, and recent large-scale migrations, have introduced ethnically distinct populations to many countries for the first time, and in others there is a long-term pattern of migration. There is increasing evidence that immigration status may result in significant employment discrimination, even after language difficulties and other human capital factors have been adjusted for.13 As in studies of ethnicity, Asian immigrants appear to face even larger employment hurdles than other groups.14
Empirical studies of employment discrimination often confound or combine ethnicity and immigration status, with ethnicity signaled through country of origin cues such as employment history, educational history and immigration status. For example, it is difficult to separate employment effects for a recent Indian migrant; what difficulties arise from personal skills and career transitions, and what arises from Indian ethnicity, and what arises from immigration – with difficulties in recognition of qualifications and prior experience, and no or few local references? Conversely, the effects of immigrant status are usually studied for identified groups of ethnic migrants. In UK studies of levels of ethnic penalty, there is some indication that Anglo-
Dr Marie Wilson is Senior Fellow in the Graduate School of Business. Dr Suchitra Mouly is Associate Professor in The University of Auckland Business School. Yemei “Lucia” Liu and Priyanka Gahlout are graduates of the Masters in Commerce programme, under the supervision of Drs Wilson and Mouly.
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Saxon immigrants from ethnically similar countries (e.g., Australia, New Zealand, Canada) experienced far less ethnic penalty than West Indians, Asians and other non-Anglo- Saxon groups.15 Canadian studies find similar differentiation between immigrant status, ethnicity and race.16 This would suggest that immigration status and ethnicity may interact in potential employment discrimination. This is a particularly important distinction in countries where recent migrants may compete for jobs alongside their ethnic “cousins” who are third-, fourth-, or fifth- generation “locals”. To tease these effects apart, we will rely on the findings of research in the UK, Australia and the USA, which suggest that: Hypothesis 3. Immigrant status will increase the “ethnic penalty” in shortlisting of ethnic candidates.
Method This research was conducted in three linked studies. The first study evaluated the impact of ethnicity with name. The second study evaluated the impact of ethnicity and immigration. The third stage evaluated the impact of having many or few ethnic resumes in the selection pool. All three studies used a structured survey instrument that simulated organisational short-listing. The survey asked respondents to evaluate a new web-based selection system. They were asked to evaluate the system by viewing a current selection portfolio produced by the system; and evaluating and short-listing applicants. It is important to note that the survey was structured as the evaluation of the “beta” version of new standardized employment software, so the participants were focused on the information presented by the web- based system, rather than feeling that the attention was focused on their short-listing behavior, per se. Participation in the web- based short-listing survey was offered at the break for students in HRM classes who had just heard a lecture on the impact of new technology on recruiting and selection. A subsequent study de- brief was held in the same classes, several weeks later, in the context of either legal or diversity topics, acknowledging both the study’s intent, and its outcomes.
The instrument “portfolio” included a very detailed, three-page job description and an equally detailed person
specification for an entry level human resources position in a well-known public sector organisation, followed by a set of matched-quality one-page resumes. The resumes were presented in alphabetical order by applicant name. Each resume included the name and contact details of the applicant, details of a bachelors degree in an HR related field (required by the person specification), 16-19 months of HR experience in a well-known multi-national company (only 12 months were required by the person specification), a listing of computer competencies (all candidates were competent in the software required by job, plus one additional software package), and statements of fluency in English and one other language (to result in equal qualifications for immigrant applicants, and to counter any assumptions about lack of language competency). At the bottom of each resume, space – and two rating scales – were provided for the reviewer to rate the applicant on their suitability for the position. Participants spent 20-40 minutes carefully reading the job description and person specification, and making notes, before rating each candidate and compiling a final shortlist. Different classes received different versions of the survey, depending on the hypotheses being tested. A summary of the research design is presented in Table 1.
The first study assessed the employment effects of ethnicity and name. Eighteen resumes were created; six European/
Pakeha resumes, six Chinese and six Indian resumes. Cues for ethnicity included country where the degree was gained (only the two highest ranked Universities in each country
Table 1: Summary of three research designs
Study What is changed What is measured Design
1 Ethnicity of applicant, ethnicity of name
Rating of suitability? Presence of ethnic candidates in shortlist?
18 resumes – 6 each Pakeha/European, Chinese and Indian applicant; half of Chinese and Indian applicants had anglicised names, e.g. Bobby Sharma, Rose Wong
2 Ethnicity of applicant, immigration status (local or foreign education and experience)
Rating of suitability? Presence of ethnic candidates in shortlist?
12 resumes – 3 local Pakeha resumes; 3 European/Pakeha immigrants; 3 local Chinese; 3 immigrant chinese
3 Ethnicity of applicant, Ethnicity of labour pool
Presence of ethnic applicants in shortlist
10 resumes, with 2, 4, 6 or 8 Chinese resumes and the remainder Pakeha/ European. No applicants are immigrants.
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were used); country where HR experience was gained (with well-known international companies such as Coca-Cola, Hilton Hotels, and KPMG); and distinctly ethnic names (e.g. Laxmi Prasad, Liao Xu). Half of the ethnic applicants (three of six Indian applicants; three of six Chinese applicants) received anglicized first names, with easily pronounced surnames (e.g. Bobby Sharma, Polly Wong).
Each resume included two rating scales for reviewers to rate the candidates as they reviewed their resume: suitability for the job (7 point Likert scale; 1= unsuitable for the job; 7= very suitable for the job) and likelihood of short-listing the candidate (7 point Likert scale; 1= definitely not; 7= definitely).17 The last page of the survey asked for a final three person short-list, in addition to demographic data and feedback on the software being trialed (consistent with the survey design).
In the second study, the focus was on ethnicity and immigration status. The instructions, job description and selection ratings were identical with the first study. Distinctly ethnic names were used to identify six Asian (Chinese) and six Anglo-Saxon/European applicants (e.g. Xiao Ximen and Sarah Smith). Half of the ethnic (Asian) candidates and half of the Anglo-Saxon applicants had local education and experience. The immigrant Asian applicants had equivalent experience in Asia (again at top Universities and with well- known international companies), while immigrant Anglo- Saxon candidates came from Canada and the UK (from top Universities and with work experience at well-known international companies).
The design in these first two studies parallels real-world selection practices where employers typically evaluate more than one candidate, using limited information, typically, a short resume.18 The respondents read and annotated the job description and resumes, made numerous suggestions on the design of the forms and process, and took up to 40 minutes to complete the short-listing process.
There is, however, one point on which the structure of the surveys is distinctly dissimilar to actual selection screening; ethnic “minority” candidates are not minorities in the applicant pools presented to respondents in the first two studies in this research. This reflects the requirements of a balanced research design, but results in two-thirds of the applicant pool in the first study, and one-half the applicant pool in the second study, being members of groups that are far rarer in the working population.
Accordingly, the third study provides a check on this effect, by providing evaluators with ten quality-matched non- immigrant resumes, of which two, four, six or eight resumes are from Asian applicants. The instructions, job description and selection ratings were identical with those in the first and second studies, but the nature of the selection portfolio was changed. Distinctly Asian or Pakeha/European names were used to signal ethnicity, and all applicants were “local” non- immigrants. The portfolios varied only in the prevalence of
Asian candidates within a pool of ten resumes.
Results The survey was administered to practicing managers enrolled in HRM courses as part of an Executive MBA, and to senior undergraduates enrolled in HRM courses. Study one was completed by 102 managers and 98 undergraduate students; study two was completed by 98 managers, and study three was completed by 60 managers. The sample demographics indicate these groups are heterogeneous in terms of ethnicity, gender, and managerial experience, and statistically similar to the metropolitan population of working age. For study one, where younger undergraduates were included, all measures were assessed for statistical similarity between managerial and student groups. For all measures reported, the students in the first study displayed no rating differences from the older and more experienced managers.
Study one For the first and second hypothesis, we were assessing the impact on short-listing of ethnicity of the applicant (European, Chinese, or Indian); ethnicity of name (anglicized name or non-anglicized); and immigration status (education and experience in New Zealand, UK/Canada or China). The dependent variables in all three studies are suitability for the position, as well as the profile of the final three candidates shortlisted. A 3x2x3 multivariate analysis of variance (MANOVA), with repeated measures, was performed to test hypotheses one and two.19
Effect of ethnicity on selection outcomes The MANOVA shows a significant interaction effect for ethnicity of applicant by ethnicity of name (F(8,618)=3.158, p<.05), supporting hypothesis one and two. The analysis of variance (ANOVA) shows a significant main effect for ethnicity (F(2,155)=23.112, p<.01). The results of the multivariate and univariate analyses are presented in Table 2.
Differences in mean ratings for suitability for the position between Indian and European/Pakeha candidates were significant (t(162)=-6.814, p<.01), as they were between Chinese and European/Pakeha candidates, (t (162) = -8.440, p<.01) and between Chinese and Indian candidates, (t(162)=- 4.500, p<.01). As Figure 1 demonstrates, while the difference
Effects / Variables (within subject)
Multivariate F Univariate F
Ethnicity 6.988** 23.112** Name 5.820** 18.749** Ethnicity x Name 16.334** 13.709**
Table 2: MANOVA: Ethnicity and name effects on ratings of suitability
a rose by any other name: The effect of ethnicity and name on access to employment
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between ratings for Pakeha and Chinese candidates were large (Cohen’s d =.82), the differences between the two ethnic subgroups were small (Cohen’s d =.25)
To summarise, the findings indicate a significant effect for ethnicity. This ethnic penalty is greater if ethnic candidates have traditional, non-anglicized names. Pair-wise comparison between groups demonstrate that having an anglicized name reduces the ‘ethnic penalty’ for candidates from India and China, across all rating conditions (all p<.01), although the ratings of both Indian and Chinese applicants remains lower than European/Pakeha candidates, even when Asian candidates anglicize their names. The interaction effect between ethnicity of the applicant and name accounted for 31% of the variance in the mean ratings. Thus, hypotheses one and two are supported.
The final shortlist In addition to the rated suitability and likelihood of shortlisting, we also examined actual shortlisting choices. After rating all candidates, respondents were asked to construct a short list of three candidates. The applicant pool presented to each respondent was evenly divided among candidates from each ethnic group: European/Pakeha, Indian and Chinese. Given that all had equivalent experience and qualifications, we might expect that these proportions would be reflected across the final shortlists: 1/3, 1/3, 1/3. However, the cumulative short-lists included far fewer ethnic candidates than would be expected based on the percentage in the applicant pool (as shown in Table 3). Compared to the applicant pool, twice as many European/Pakehas were selected, and half as many Chinese and Indian candidates. The under-representation of ethnic applicants in the final short-list was statistically significant (Pearson χ22 (2, 196) =194.236, p<.001).
Study two This second study repeated the format of the first study, with separate cues for ethnicity and immigrant status, to attempt
to separate out these two effects. Ethnically Asian and Pakeha/European applicants, signalled by distinctly ethnic names and language fluencies were equally represented in the pool. Half of each ethnic group were “locals” and the other half recent migrants, as signalled by job experience and education in a foreign country and indications in their resumes that they were “permanent residents” rather than citizens.
Interaction of ethnicity and immigrant status The MANOVA demonstrates a significant two–way interaction effect for ethnicity of applicant by immigrant status, (Λ)=.988, (F(3,98)=29.107, η
2=.07, p<.01). This supports hypothesis three. The ANOVA shows a significant main effect for ethnicity on assessed suitability for the position (F(2,98)=39.8, η
2=.08, p<.01), consistent with the impact of ethnicity demonstrated in study one, and confirming hypothesis three. The multivariate and univariate analyses are presented in Table 4.
Non-immigrant, European/Pakeha candidates were rated highest and Asian migrants lowest. Immigrants were rated lower than comparable non-migrants, t(97)=5.45, p<.001, and Asian migrants were rated lower than all other groups, all t(97) >7.75, all p<.001. The statistical impact of migration in this case is small (Cohen’s d = .19); this reflects a negative impact for Asian migrants and a paradoxical positive impact for Anglo-Saxon (UK and Canadian) migrants.
To summarise, the findings indicate a significant main effect for ethnicity, interacting with immigration status. As Figure 2 demonstrates, on rated suitability for the position, ethnic migrants received the lowest average ratings. These results are even more pronounced in examining the final short-lists which were generated by respondents. Given equal quality of resumes and equal numbers in each of the four categories, we would expect equal numbers to appear on the final short-lists. However, no Asian migrants were short-listed by respondents, and the pattern of under- representation is highly significant (Pearson χ2(3, 98)=143.36, p<.0001), see Table 5.
Table 3: Ethnic representation in final shortlist
Euro/Pakeha Indian Chinese
Final short-list 63.70% 18.50% 17.80
Figure 1: Perceived suitability of candidates, by ethnicity and name
Effects / Variables Multivariate F Univariate F
Within- subject Factors
Ethnicity 22.863** 39.886**
Immigrant 0.835NS 1.647NS
Ethnicity x Immigrant 29.107** 58.337**
Table 4: MANOVA: Ethnicity and immigration effects on rated suitability
Final short-list Pakeha/Anglo-Saxon Asian
Non-immigrant 59.2% 18.3% Immigrant 22.5% 0%
Table 5: Ethnicity and immigration status in final short-list
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The results of study two confirm the discrimination on the basis of ethnicity found in study one, and confirm that this interacts with immigration status, confirming hypothesis three. Across studies one and two, all hypotheses are supported.
Study three Study three assessed the impact of over-representation of “minority” resumes in the applicant pools of studies one and two, by presenting portfolios reflecting different degrees of ethnic representation in the applicant pools. Although minority applicants are less than 25% of the population, in the first two studies ethnic candidates made up at last half of the applicant pools. This may increase the probability of ethnic candidate selection and under-estimate discriminatory effects. The 60 managers who were respondents in the third study were presented with ten equivalent resumes, of which two, four, six or eight candidates were Asian applicants, and the remainder European/Pakeha applicants. All candidates were non-immigrants. The results are presented in Table 6, and reflect that all observed selection rates are well below expected values if there were no ethnic bias present. Further, rates of selection are significantly depressed when pool representation approaches normal population levels, that is, at rates below 25% of the applicant pool. The pattern of bias against ethnic candidate is highly significant (Pearson χ2(3, 60)=18.78, p<.001).
It is particularly significant to note that in the pool with 80% Asian applicants, to reach a short list of three, raters would have to select at least one Asian applicant. All but a handful selected this minimum number and two raters picked only the two European/Pakeha applicants and left their shortlists incomplete.
Discussion The focus of this study was to investigate the effect of ethnicity of applicants in the short-listing phase of selection. Multiple cues are linked to ethnicity, and all of those investigated seem to have a cumulative, and negative, effect on the selection outcomes of applicants. These findings are consistent with the previous literature on influence of ethnicity on selection decisions,20 and in differing levels of “ethnic penalty” for different ethnic minority groups.21 In particular, this research reinforces previous findings that Asian (particularly Chinese) applicants are particularly disadvantaged in Anglo- Saxon/European work settings.22
The lower perceived suitability of ethnic applicants may be explained by the concept of ethnic stereotyping, which involves uses of (negative) ethnic schemas by members of majority groups to judge members of ethnic minorities.23 Given that all applicants in the pool actually possessed more than the stated qualifications and experience for the job, average ratings for ethnic applicants that indicate that they are “not suitable” suggest that the raters’ bias is ethnic– schema driven rather than driven by objective differences in job or applicant characteristics.
However, the employment screening by Asian raters was not biased per se; Asian raters, overall, rated equivalent Asian and European/Pakeha applicants similarly, while both Pakeha and Maori raters exacted significant ethnic penalties for ethnicity, as well as for ethnicity of name, and immigration status.24 This is less consistent with a similarity bias per se, and more suggestive of a contact hypothesis.25 The contact hypothesis suggests that frequent positive contact between groups will minimize the stereotyping. The Asian rater’s lack of bias may result from their existence in a business and social environment where they have frequent contact with both members of their own ethnic community as well as majority European/Pakeha communities. This should reduce their stereotypes of members of the other group and result in similar ratings. The Pakeha and Maori raters are less likely to have experienced significant stereotype-reducing interactions with members of minority communities, and continue to exhibit far greater schema-driven biases than their Asian counterparts.
Conclusion The first scholarly article demonstrating employment discrimination was published more than three decades ago. Our study shows that, despite significant socio-legal and demographic changes in the ensuing thirty-plus years, employment discrimination persists. The “ethnic penalty” appears to differentially impact ethnic groups, with those of Chinese ethnicity being most disadvantaged in this study, as in prior research. Across ethnic groupings, additional penalties appear to apply to those who are immigrants, with foreign qualifications and experience, and/or “foreign- sounding names”. This is problematic for New Zealand’s quest
Figure 2: Ratings of suitability, ethnicity and immigrant status
Table 6: Ethnic candidate selection by pool representation
No. of Applicants 2 4 6 8 Expected selection (%) 20.0 40.0 60.0 80.0 Candidates selected – actual (%) 4.44 13.3 33.33 37.8
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to have a “brain exchange”, with foreign talent replacing kiwis who leave. It also may prevent companies who are actively seeking talent from finding it in their applicant pools.
The review of the literature indicates that the implications for rejection of job application can be wide-ranging. At an individual level, biases in selection reduce the probability of receiving a job offer and provide lower returns to job search. At a macro level, this also indicates that employers are unable to tap and capitalize on the valuable talent that ethnic minorities bring to the labour market.
Implications for practice For both managers and HR specialists, this research should serve as a reminder that employment discrimination may be a continuing problem, both from a social perspective, as well as from an employment perspective. No employer can afford to overlook talent; an inability to see skills and abilities across ethnic boundaries is business blindness. And as the workforce becomes more diverse, issues of relative discrimination and opportunities for injustice may increase. How can this potential problem be addressed? Aside from increased awareness and continued training to combat stereotyping and employment bias, the findings of this research suggest that ethnically diverse selection panels may moderate some discriminatory effects, and ensuring that recruiters and selectors have interaction and contact with a broad cross-section of the labour market may also help.
At a more fundamental level, these results suggest that there is a substantial legal risk for companies, demonstrated by both anecdotes and the research results. Not hiring on the basis of ethnicity or migration status is not just bad business, it is clearly illegal under the Human Rights Act (1993). Companies that cannot overcome such biases will struggle to recruit and retain quality staff, and may face legal challenges.
For job-seekers, it suggests that their suspicions/ reservations regarding reasons for rejection may be well- founded. Increased awareness of stereotypes associated with the ethnic cues in resumes may cause some to re-think how they present themselves in a job search, to increase their chances of “getting a foot in the door”.
References 1. (1993). The Human Rights Act. Wellington, New
Zealand.
Glass, H. and Choy, W.K. (2001). Brain Drain or Brain Exchange (No.). Wellington: New Zealand Government.; Ward, C. and Masgoret, A.-M. (2004). New Zealanders’ attitudes toward immigrants and immigration. Paper presented at the New Directions, New Settlers, New Challenges – Building and Enhancing Communities End-users
Seminar, Wellington, New Zealand.
Swift, E.W. (1992). Glass Ceilings and Equity. The Public Manager, 21(4), 34-36.
Weeks, K.P. (2002). Levels of prejudice and motivation as explanation for race discrimination in selection interviews.
Rather than skin color or race, this research focuses on ethnic groupings. While acknowledging that there are many Asian and European ethnicities, we have adopted the meta-terms, Pakeha/European and Asian, Chinese and Indian, to refer to large ethnic groupings. The term European is used to indicate those of European self-identity, primarily of Anglo-Saxon heritage; Pakeha refers to light-skinned Europeans in New Zealand. Chinese is used as an encompassing terms for the multiple ethnicities in the PRC and related economic zones, and Indian for all those ethnic groupings in the Indian sub-continent. We have used the term Asian to include all peoples from the Indian subcontinent and continental Asia, plus Japan, Sri Lanka, Indonesia and Malaysia.
Shire, D. (1997). Real level of black unemployment is double the official figure. Working Brief, (84), 5-6.
Carmichael, F. and Woods, R. (2000). Ethnic penalties in unemployment and occupational attainment: Evidence for Britain. International Review of Applied Economics, 14(1), 71-81.
Firth, M. (1981). Racial discrimination in the British labour market. Industrial and Labour Relations Review, 34, 265-272.
Glass, H. and Choy, W.K. (2001)., Ward, C. and Masgoret, A.-M. (2004)., see endnote 2.
Bart, B.D., Hass, M.E., Philbrick, J.H., Sparks, M.R., and Williams, C. (1997). What’s in a name? Women in Management Review, 12(8), 299-307.
Bertrand, M. and Mullainthan, S. (2003). Are Emily and Greg more employable than Lakisha and Jamal? A field experiment on labor market discrimination. Working paper series, University of Massachusetts, 03-22.
Brown, C. and Gay, P. (1985). Racial Discrimination: 17 years after the Act . London: Policy Studies Institute; Hoque, K. and Noon, M. (1998). Racial discrimination in speculative applications: New optimism six years on. Human Resource Management Journal, 9(3), 71-82.; Hubbuck, J. and Carter, S. (1980). Half a chance? A
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Report on job discrimination against young Blacks in Nottingham. London: Commission for Racial Equality.
Jasso, G. and Rosenzweig, M. (1995). Do immigrants screened for skills do better than family reunification migrants? International Migration Review, 29(1), 85-111.
Blackaby, D., Leslie, D., Murphy, P., and Leary, N.O. (1999). Unemployment among Britain’s ethnic minorities. The Manchester School, 67(1), 1-20.
Jowell, R. and Prescott-Clarke, P. (1970). Racial discrimination and white collar workers in Britain. Race, 11, 397-417.; see endnote 8.
Swidinsky, R. and Swidinsky, M. (2002). The relative earnings of visible minorities in Canada: New evidence from the 1996 Census. Relations Industrielles, 57(4), 630-629.
The two Likert scales were highly inter-correlated (r=.92) and demonstrate identical patterns of significance. For the sake of clarity of presentation, the second measure is not presented here.
Bendick, J.M., Jackson, C., Reinoso, V., and Hodges, L. (1991). Discrimination against Latino job applicants: A controlled experiment. Human Resource Management, 30, 469-84.; Stewart, L.D. and Perlow, R. (2001). Applicants race, job status and racial attitude as predictors of employment discrimination. Journal of Business and Psychology, 16(2), 259-275.
Given multiple independent variables, the F-test used for significance in the MANOVAs reported here is a special case of Wilk’s U.
Jowell, R. and Prescott-Clarke, P. (1970), see endnote 15; Firth, M. (1981). Firth, M. (1981), see endnote 8.
Modood, T. (1997). Ethnic minorities in Britain (No.). London: Policy Studies Institute.; Carmichael, F. and Woods, R. (2000). Carmichael, F. and Woods, R. (2000), see endnote 7.
Hoque, K. and Noon, M. (1998). Racial discrimination in speculative applications: New optimism six years on. Human Resource Management Journal, 9(3), 71-82.; Ward, C. and Masgoret, A.-M. (2004). New Zealanders’ attitudes toward immigrants and immigration. Paper presented at the New Directions, New Settlers, New Challenges – Building and Enhancing Communities End-users Seminar, Wellington, New Zealand.
Nkomo, S.M. (1992). The emperor has no clothes: rewriting race in organizations. Academy of Management Review, 17, 487-513.
t (156) = 1.435, p<. 05 and t (156) = 1.602, p<. 01, respectively.
Nkomo, S.M. (1992), see endnote 23.
Ellen Portch, Gorbachev, 2005, pencil on paper. Elam School of Fine Arts
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