The Impact of the Structure of Ethnic Diversity in the Workplace

Enchautegui-de-Jesus, Noem`i, Diane Hughes, Kristen E. Johnston and Hyun Joo Oh. 2006. "Well-being in the Context of Workplace Ethnic Diversity." Journal of Community Psychology 34(2): 211-223.

In this study, the authors examine how ethnic diversity in the workplace affects the overall mental and psychological well-being of workers of color. As well as looking at the individual effects, this study looks at the topic of ethnic diversity in the workplace as important because
it reflects society's changing face of the American blue-collar worker.

This article defines diversity as "the representation of different social categories often based on gender, race, or ethnicity, in an organization"(212). Based on this definition, the authors examine two important concepts on ethnic diversity, which they base the study's hypotheses. One end of the cultural spectrum is tokenism, which is "a segregated work environment in which the minority group comprises less than 15% of the working group"(212). The other end of the spectrum is the concept of ethnic minority concentration, which is when a workplace has workers that are concentrated to one ethnic group.

The purpose of this study was to first, examine the psychological functioning, life-satisfaction, job satisfaction, and over all well-being of workers of color. Second, the authors wanted to test the differences between workplaces that had workers of color with a high ethnic proportion. The overallhyopothese was that a workplace that had a proportion of above tokien level of diversity and lower ethnic minority concentration, would create a better working environment, and in turn, a happier worker.

The researchers collected their data fron The Survey of Minority (MIDUS), which is a survey based on a stratified sample of men and women, ages 25 and older. The survey sampled African Americans and Dominicans in New York City, Mexicans in Chicago,andPuertio Ricans in both cities. Respondents were asked questions on their highest level of school completed, median income, years at job, and job position. Also asked was the ethnic composition of their workplace, whichethnicity's were dominant or sparse, and the worker's overall feeling of being a worker
of color in a low-wage job. Most respondents had only graduated from high school and their median income was $25,000-$29,999. 57% of respondents were immigrants.
Results of this study found that people who worked in a more balanced environment (no high or low levels of co-ethnic workers) reported a more positive level of job satisfaction than workers in a tokien or ethnic minority concentration environments.

The authors of this article felt that the topic of workers of color must be
looked at because people of color are overrepresented in low-paying,low-status jobs. Also, because the growing numbers of workers of color in America are changing the face of the U.S. labor force. The questioning of ethnic composition in the workplace is important for creating a positive environment for all workers and for understanding of the impact of the structure of workplace.

Future Research: As the authors suggest, there needs to be further research on this topic that expands to the topic of the ethnicity of employees at different levels, types of jobs, the working environment, and the quality of working relationships in low-wage, low-status jobs.

Preference Theory: Sex Segregation

Hakim, Catherine. 2006. “Women, careers, and work-life preferences.” British Journal of Guidance & Counselling. 34:279-294.

Trying to find some sort of theoretical background as to why there is occupational segregation, I came across an article identifying how the US and Britain have tried to solve the problem of gender discrimination/segregation in the workplace. Although there has been an increase of women working in the labor market, and family-friendly policies have been set in place to somehow offset the gender inequalities, Catherine Hakim (2006) from the department of Sociology in the London School of Economics, and other sociological theorists agree that neither one of these “make any major positive difference to gender equality in the labour market, as indicated by levels of occupational segregation, the pay gap and the glass ceiling”. On the Contrary, they exacerbate these problems” (281).

The fact is, although women might be able to join the work force, if they want to have children and a family, they cannot work the long irregular hours, travel for work, or be full time. That is, part-time jobs that would pay the same wages as full time jobs are a rarity in the US and Britain. On the other hand, many men who are married and have children have the “luxury” of mentally and physically working for 24 hours a day, because their wives are at home with the children (Harkim 2006). Therefore, even if there are more women in the work force, they are working in low-income part time positions. An example of this type of low-paying job would be a school teacher.

In addition employers and other employees feel it is unfair for women to get child leave, while the rest of the workers are working overtime to do the work left by the mothers who are on leave. Here, the employers are angry because they are forced to pay extra to the overtime workers, and the other employees are jealous because they do not get any paid leave (Harkim 2006).

Harkim examines two types of occupational segregations 1-Horizontal and 2-Vertical. The former means segregation by choice of job, for example, men might choose to be carpenters while women might choose to be school teachers. The latter means segregation when men monopolize the dominant job positions. With that said, Harkim writes that macro-level studies cannot tell anything about the social processes at the micro-level. “It is wrong to assume that a low percentage of women in higher-grade jobs is necessarily due to sex discrimination alone” (285). She suggests examining the women with dominant positions—most are childless, or have only one child, and these women express so-called “masculine” characteristics, thereby perpetuating dominant male ideals.

To express another reason why there is sex segregation, Harkim suggests “Preference theory” predicts the polarization of work-lifestyles. “Preference theory specifies the historical context in which core values become important predictors of behaviour” (286). Harkim’s table of preferences shows approximately 20% of women are “home-centered” (stay-at-home moms), 60% of women are “adaptive” (try to balance work and home life), and 20% of women are “work-centered” (work-a-holics, mostly childless) (288). From this spectrum, Harkim claims that men remain dominant and sex segregation continues because only a minority of women are work-centered. Since part-time jobs are rare, in relation to sustaining a family while working, women choose jobs like teachers, or seasonal/ temporary occupations.

The implications of this are that increased women in the labor market does not matter, equality policies are misdirected because they overlook people with other life goals. Furthermore the wage gap and glass ceilings persist because high paying part-time work rarely exists. Finally, so-called equity policies create a jealous atmosphere for those who do not get gender neutral policies for paid leave.

As for the future, Harkim suggests gender-neutral policies, like the ones in the Netherlands, where anyone has the right to ask for part-time hours, rather than part-time wages. Also, mothers should not be the only ones with paid leave; other workers should get longer paid vacations or paid leave for their personal reasons.

Future Research:

Would this phenomenon be similar for migrant women, or even migrant men? Is sex segregation or racial segregation a cause of differing life goals? What cities, racial-ethnic groups are affected most?

Overrepresentation of Immigrant Workers in San Francisco Hotel Industry

Wells, Mariam J. 2000. “Unionization and Immigrant Incorporation in San Francisco.” Social Problems. 47:241-265.

This study explores the changing demographics of San Francisco hotel workers from 1970-1990. The author's focus is on the impact an increase of immigrant workers has on the ability to unionize. She does so using the success of the hotel workers union, H.E.R.E (now called U.N.I.T.E H.E.R.E), as a case study. Occupations such as cooks, dishwashers, bussers, and room cleaners are more than ¾ immigrant - the largest groups being Chinese, Filipino, Central American, and Mexican. Positions such as receptionist are predominantly white and held by citizens. “Front of the house” positions are generally paid more than “back of the house” positions. White men hold the most privileged positions, while women of color hold the least. In the hotel industry in San Francisco From 1970-1990, minority, immigrant, and non-citizen population has risen, while non-Hispanic, white and citizen population has plunged. White and Black groups are underrepresented while minority groups are over represented in the San Francisco hotel industry. For example, Filipino’s comprise 5.4% of the city’s population, but make up 13.7% of the industry population. The article includes a chart comparing the city population and industry population of all ethnic groups. Historically, hotel workers have predominantly been less white & comprised of more minorities compared to the rest of the population, but this change has increased. Wells concludes that the workers are clustered in such a way because of 3 factors: employer recruitment practices, immigrant reliance on social networks to find jobs, and native workers preference for non-menial positions.

The article demonstrates a growing trend of a predominantly immigrant low wage workforce in San Francisco’s service sector. It would be interesting to see how the trend continues from 1990-2000.

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1970 – San Francisco’s population 5% foreign born
1990 – 34% foreign born

• Majority of increase is Asian-Pacific Islanders (56% of foreign born residents) and Hispanic (21% of foreign born residents)
• Asian Pacific Islander group: 2/3 are Chinese and 1/5 is Filipino
• Hispanic group: 38% are Central American, 40% are Mexican
  

Occupations (1970)

• Managers: 93.8 White, 6.3% Black, 0% API, 0% Hispanic, 0% Other
• Receptionists: 100% White
• Room Cleaners: 20.6% White, 47.1% Black, 11.8% API, 20.6% Hispanic, 0% Other

Occupations (1990)

• Managers: 67.4% White, 0.8% Black, 16.8% API, 10.7% Hispanic, 4.3% Other
• Receptionists: 76.5% White, 0% Black, 0 API, 23.5% Hispanic, 0% Other
• Room Cleaners: 5.8% White, 8.3% Black, 51.8% API, 33.6% Hispanic, .06% Other

Room cleaners make up about 27% of all hotel workers and contribute the largest share of immigrant workers, meaning that the largest body of San Francisco immigrants in the hotel industry are Asian Pacific Islander and Hispanic women that clean rooms. Immigrants are 77% of the cooks, 80% of food preparers, and 85% of room cleaners

Immigrant Filipinas/Immigrant Asian Indian women/non-Hispanic white women

Torres Stone, Rosalie A., Bandana Purkayastha, Terceira Ann Berdahl. 2006. “Beyond Asian American: Examining Conditions and Mechanisms of Earning Inequality for Filipina and Asian Indian Women.” Sociological Perspectives. 49:261-281.

To explore whether highly educated non-white immigrant women do as well as non-Hispanic white women in the U.S. labor market, this study examines educated women of color in the U.S. labor market using 1% of the 2000 Integrated Public Use Microdata Series census data. This study took statistics from people living in New York City, Chicago, and LosAngeles “to examine the effects of human capital, family status, and migration history on annual earning for white, Filipina, and Asian Indian women” (269).

The Dependent Variable is total logged wage and salary earning in the 1999 calendar year. The primary human capital variables were education and English language proficiency. Family status was measured by 0-not married 1-married. And number of children living in the house ranged from 0-9. Race/ethnicity was Filipina, Asian Indian, and non-Hispanic white. The researchers controlled for number of hours worked per year, age, occupation, and metropolitan area. Dummy variables included migrations cohorts (post-1990, 1980s, 1970s, pre-1970s).

After examining the earnings of immigrant Filipinas and immigrant Asian Indians women (groups with both higher levels of education than non-Hispanic white women, and who are proficient in English) compared to non-Hispanic white women, it is important to highlight the factors: migrant context and occupational racial/ethnic segregation. As income attainment has to do with social location, Stone, Purkayastha, and Berdahl (2006) found that income attainment is correlated with the reason that women migrated—as workers for labor shortages like nurses, as refugees, as wives—and the occupational context where women may be segregation by race/ethnicity. Migrant cohorts affect attainment, those migrated in the 1990s earn significantly less than natives, while those migrated before the 1980s earn more than natives.

Finding showed that these immigrant women were affected by time of migration, occupational racial-ethnic segregation, and race-ethnicity. Education and English proficiency positively affect income, as well as hours per week and aging. Negatively, for every additional child, income declined (probably because of the gender role of motherhood). There was no significant difference in earnings between Filipinas and white women after controlling for other variables. On the other hand, significant difference in earnings between Asian Indian women and white women remained after controlling for the same variables. Future research should focus on a longitudinal study and examine other Asian immigrant groups as well as Asian groups that are not immigrants.

Filipino, Native Hawaiian, Honduran, Vietnamese, Columbian, Guatemalan, Haitian, Puerto Rican in L.A., Boston, Detroit, Atlanta

Wilson, Frank D. 2003. “Ethnic niching and metropolitan labor markets.” Social Science Research. 32(3): 429-466.

Wilson discusses a study of labor market niching of 100 ethnic groups in 216 metropolitan areas in 1990. The article uses the term niche to refer to the tendency of members of certain ethnic groups to over-representatively specialize in a particular occupation. Wilson’s primary objective for the analysis is to discern in which labor market niches different ethnic groups are more likely to concentrate. Wilson also explores ethnic homogeneity in workplaces and niching. The study also seeks to determine whether patterns can be drawn from those occupational niches of individual ethnic groups across various metropolitan areas.

The study used data derived from the public use microdata sample (PUM) files for 1990, 1% and 5% samples. Ethnic groups were classified into 10 broad categories: Central America and Mexico, South America, Other Hispanic, Caribbean, Sub-Sahara Africa, N. Africa and Mid. East, Asia, North America, Northern and Western Europe, and Eastern and Southern Europe. Occupation categories included were as follows: Executive, Administrator, and Manager; Management-related; Professional; Technical; Sales; Administrative Support; Protective Services; Food Service; Health Services; Cleaning and Building; Personal Services; Farming, Forestry, Fishery; Mechanics and Repairers; Construction Trade; Extractive; Precision Production; Machine Operators, Assemblers; Transportation and Material Moving; and Laborers and Private Household.

The analysis found that most of the Hispanic groups were concentrated in service (food, health, cleaning and building) and blue-collar (machine operators and assemblers, laborers) jobs. More specific findings indicate that persons of Guatemalan, Honduran, Argentinean, Chilean, and Panamanian ethnicity were concentrated in construction trades. Administrative support jobs were over-representatively occupied by Puerto Ricans, Cubans, and other Hispanics. Persons of Caribbean ancestry were concentrated in health services, administrative support, and laborer occupational sectors. Middle Eastern and Asian groups were concentrated in professional and retail occupations. Vietnamese were over-representatively working in semiskilled blue-collar occupations. American Indians, Hawaiians, and Canadians were clustered in construction trades, and transportation and material moving. European ethnic groups were concentrated in white-collar occupations.

Wilson used Multi-city Study of Urban Inequity (MCSUI) surveys to explore the extent to which persons work in jobs at jobs that are ethnically homogeneous, and any associations between ethnic niches and ethnically homogenous workforces. The surveys were conducted in 1992-1994 in Atlanta, Boston, Detroit, and Los Angeles.

Several implications that Wilson derived from this study are that ethnic niching is a “social formation driven by the needs of ethnic groups to acquire material resources beneficial to the well-being of members” and the necessity of maintaining those members’ access to resources; that the structure of labor markets facilitate the matching of individual workers’ skills and experiences with the goods and services labor market positions; and that employers, who seek to maintain productivity goals, may recruit a certain group in order to minimize doubt of the labor supply quality.

Latinos/Occupational segregation

Zavella, Patricia. 2000. “Latinos in the USA: changing socio-economic patterns”. Social & Cultural Geography. 1:155-167.

Zavella (2000) aims to describe how Latinos and Latinas experience poverty and socio-economic inequality because of historic and geographical experiences, despite the traditional focus on the black-white paradigm. Zavella does not herself do any data collection or analysis, but does a critique on past literature and on how scholars need to move beyond the white-black racialized experience as a means to understand how occupational segregation is generationally maintained for Latinos. Describing who Latinos are is difficult because the category can include people from Guatemala, El Salvador, Cuba, Puerto Rico, Mexico, etc. (156).

The main issue is how the cycle of low-wage jobs or “brown-collar jobs” precludes Latinos from moving out of bad hours, bad work conditions, bad pay—even US laws of equal employment do not make Latinos economically mobile (158). Once Latinos are in the low-wage jobs, they become segregated into “racial-ethnic enclaves”, where Spanish is spoken, they only meet other Latinos and social networks are never formed, which are necessary for mobility. Zavella’s connected between occupational segregation and Latinos even contrasts the expected mobility of future generations because the racial-ethnic enclaves. While Blacks have similar experiences as Latinos, Zavella explains that the focus should not remain on Blacks, but also on how Latinos experience structural forces that create poverty. For example, on a geographic note, the deindustrialization, white flight, and residential segregation in Midwest and East Coast cities also affect Latino groups.

Future research:

1-I would suggest studying each Latino group on an individual basis with actual data collection or census data, because to combine Latino groups and say they experience segregation and jobs in the same way is probably a mistake.

White/Black/Latino insider referrals and ethnically homogeneous jobs in Atlanta, Boston, and LA

Elliott, James R. 2001. “Referral Hiring and Ethnically Homogeneous Jobs: How Prevalent is the Connection and for Whom?” Social Science Research. 30:401-425.

Elliot (2001) questions a fundamental understanding of why certain jobs are ethnically homogeneously concentrated. Premised with three hypotheses, Elliot posits that 1- insider job referrals play a critical role in contemporary job matching, at least in Atlanta, Boston, and Los Angeles, 2- insider referrals vary in degree depending on immigrant status, at least when looking at the general groups of Whites, Blacks and Latinos (he does not specify the groups of Whites, Blacks and Latinos in the article), and 3- those who acquire a job through insider referrals will end up in a ethnically homogeneous job.

The Data for the study came primarily from the Multi-City Survey of Urban Inequality (MCSUI), which is a random sample from the cities Atlanta, Boston, Detroit, and Los Angeles between 1992-1994. However, Detroit was excluded because job-matching questions were not asked.

In sum, Elliot found that 1/3 of new hires from 1992-1994 in Atlanta, Boston, and Los Angeles were a product of insider referrals. However, while immigrant status matters, ethnicity was the important factor when looking at the difference between native born and foreign-born. That is, in terms of ethnically homogeneous jobs entered, referrals did not significantly matter for Latinos or Whites—both entered ethnically homogeneous jobs regardless of insider referrals. Conversely, insider referrals were significant for native-born Blacks to enter ethnically homogeneous jobs, whereas, non-referrals (like answering ads, job agencies, etc.) led native-born Blacks to enter non-ethnically homogeneous jobs.

Although not written in the MCSUI, Elliot speculates that Latinos end up in ethnically homogeneous jobs regardless of insider referrals because of their language barriers. That is to say, because English is not the Latinos’ first language, job placement is relative to the ethnically homogeneous language necessities of the Latino groups.

Future Research needed:

1. Elliot writes mostly about native-born Blacks using formal means to find jobs, and minimal use of informal means. More research needs to be done on non-native-born Blacks, such as Nigerians, Ethiopians, Eritreans, etc. Perhaps this would only pertain to the bay area, but for example, if you walk into most any Fry’s Electronics, it is like management has an African exchange program going on. If you ask where the majority of the workers are from, they are, first of all, from foreign countries, and, second of all, most likely from Eastern African countries. Is it insider referrals that concentrate this type of occupation, or some other reasons?

2. While Elliot speculates that Latinos are ethnically concentrated regardless of insider referrals because of language, I would speculate this is also because a huge Latino population is undocumented—just at one place I worked, there were Brazilians, Argentineans, Nicaraguans, Mexicans, and El Salvadorians all working under false social security cards. Perhaps ethnically concentrated jobs are also caused because the employers can get away with paying lower wages to those who them know are undocumented.

3. Finally, future research could be done on the difference between insider referrals patterns for men and women in low-income jobs.