ASIAN IMAGES PORTRAYED IN THE WEB SITES OF U.S. HIGHER
EDUCATION INSTITUTIONS:
PROPORTIONALITY, STEREOTYPICAL STATUS AND POWER POSITIONS
A dissertation presented to
the faculty of
the Scripps College of Communication of Ohio University
In partial fulfillment
of the requirement for the degree
Doctor of Philosophy
Xiaopeng Wang
August 2007
This dissertation titled
ASIAN IMAGES PORTRAYED IN THE WEB SITES OF U.S. HIGHER
EDUCATION INSTITUTIONS:
PROPORTIONALITY, STEREOTYPICAL STATUS AND POWER POSITIONS
by
XIAOPENG WANG
has been approved for
the E. W. Scripps School of Journalism
and the Scripps College of Communication by
______
Anne M. Cooper
Professor of Journalism
______
Gregory J. Shepherd
Dean, Scripps College of Communication
Abstract
WANG, XIAOPENG. Ph.D. August 2007. Mass Communication
ASIAN IMAGES PORTRAYED IN THE WEB SITES OF U.S. HIGHER EDUCATION
INSTITUTIONS: PROPORTIONALITY, STEREOTYPICAL STATUS AND POWER
POSITIONS (143 pp.)
Director of Dissertation: Anne M. Cooper
This study examines the portrayals of Asians in U.S. college and university Web
sites. By analyzing the representation of Asian American and Asian students, this study
assesses the proportionality and stereotypes of Asians in an educational environment,
interprets the social implications and sheds lights on ethnic representations, visual
consumptions and the emerging higher education marketing in the Internet era.
A purposive sample of 265 U.S. colleges and universities were selected for a
quantitative content analysis, including 257 four-year-above accredited institutions
(from California, Florida, Michigan and Maine) and eight Ivy League universities. The
analysis identified 378 Asian models from 8,319 human models presented on the
homepages and admissions homepages of the sampled college and university Web sites.
The proportion of Asian images on a Web site and the portrayals of Asian models’ status
and power position were the focus of this study.
Results show that Asian American and Asian students were under-presented on
the Web compared to their proportion in the student body, disregarding the statistical
error caused by two definitions of Asians. In contrast, African Americans were
proportionately represented. Instead of being stereotypically portrayed as passive,
submissive and devoted to work, Asians appeared neutral in terms of status and power
positions. However, genders differed significantly in representing stereotypes of Asians.
Asian females appeared more active in interacting with others and more often to be the visual focus than Asian males. On the contrary, Asian males were more likely than Asian females to be appearing alone, submissive, as a background role and as an action receiver.
This study indicates that Asian Americans and Asians are of less ideological, political and social importance compared to the non-ethnic majority and other
ethnicities, whereas the improving portrayals of Asians may serve as part of the
marketing strategies to positively influence prospective students’ choices in higher
education. Social norms and ideologies influence gender images, which further
complicates the portrayals of Asians. Images of an ethnic minority mirror marketers’
utilitarian strategies and social ideologies. With the changing of markets and society,
Asian images transform accordingly.
Approved: ______
Anne M. Cooper
Professor of Journalism
To my father,
Wang, Feizhang (1938–2005).
Acknowledgements
Although this dissertation is authored by one, it is the work of many. My deepest gratitude goes first to Dr. Anne Cooper-Chen, my academic adviser, committee chair and mentor. Her scholarship, generosity and encouragement offered me the indispensable force to go through the doctoral program. From the first cheers when I walked into her office in the Scripps Hall to the last hug when I left Ohio, the mentorship and friendship made my days in Athens enjoyable and memorable.
My gratefulness is extended to my committee members, Dr. Hong Cheng, Dr.
Jane Z. Sojka and Dr. Don Flournoy for their guidance and valuable comments on this dissertation from their own expertise. I also express my sincere thanks to the E. W.
Scripps School of Journalism, where I spent an unforgettable three years of my life, and I am proud to be one of the scrippsters.
Much of the research was done on the beautiful campus of University of South
Florida St. Petersburg. The university and colleagues offered me a supportive and friendly environment, which eased the pressure and frustration I had in conducting research while I started teaching. Particularly, I could not complete this work without the help from Kate Bradshaw, who assisted me in collecting thousands of photos from hundreds of Web pages, contacting every Webmaster in the sample and testing intercoder reliability.
Last but not least, I owe special thanks to my father, Feizhang Wang, my mother,
Laiying Wang, and two sisters. Without their endless love and support, I would not have reached the highest point in my student career. Unfortunately, my father could not witness my fulfillment. He will forever be missed. vii
Table of Contents
Page
Abstract...... iii
Dedication...... v
Acknowledgements...... vi
List of Tables...... ix
List of Figures ...... xi
Chapter 1: Introduction...... 1 College Web sites and admissions ...... 1 Ethnic diversity...... 5 Asian images on campuses...... 9 Purpose of this study ...... 13 Organization of this study...... 13
Chapter 2: Related studies ...... 14 Visual consumption...... 14 Schema theory ...... 18 Schemas of Asian images ...... 21 Under- or over-representation ...... 22 Stereotyping Asians...... 26 Status ...... 28 Power position...... 30 Gender differences ...... 32 Research questions and hypotheses ...... 34
Chapter 3: Method...... 37 Sample ...... 38 Unit of analysis ...... 40 Asian population and Asian models ...... 40 Asian population ...... 40 Asian models ...... 42 Homepages ...... 44 Photographs and slide shows...... 45 viii
Procedure...... 46 Variables ...... 48 Status ...... 48 Power position...... 49 Other variables ...... 49 Intercoder reliability ...... 50 Procedure...... 50 Results ...... 51
Chapter 4: Results ...... 54 Proportionality ...... 57 Status portrayed ...... 66 Power position portrayed...... 73 Gender differences ...... 76 Summary...... 80 Other results ...... 84
Chapter 5: Discussion and conclusions ...... 89 Rationale...... 89 Theoretical framework ...... 90 Under-represented Asians ...... 92 African Americans and Asians ...... 94 Neutral Asians ...... 96 Female Asians...... 98 Future studies...... 100
REFERENCES ...... 103
APPENDIX A...... 126
APPENDIX B ...... 128
APPENDIX C ...... 130
ix
List of Tables
Table Page
Table 1: The Asian American population, 2000, Asian American buying power, 2004 and higher education institutions in California, Florida, Michigan and Maine, 2006...... 39
Table 2: Image attributes coding criteria for Asian images’ status portrayed ...... 48
Table 3: Image attributes coding criteria for Asian images’ power position portrayed....49
Table 4: The overall coder pair agreements calculated by Simple Percent Agreement and Scott’s Pi methods (in parentheses)...... 51
Table 5: The average agreements on the numbers of ethnic images, tested by Simple Percent Agreement, Scott’s Pi and Pearson’s Correlation ...... 52
Table 6: Numbers of four-year-and-above, public and private colleges and universities by Carnegie’s classification from California, Florida, Michigan and Maine and Ivy League universities in the sample, 2006...... 55
Table 7: Top national universities and best liberal arts colleges by state (ranked by U.S. News & World Report) and the number of unranked schools in the sample...... 56
Table 8: Frequencies of Asian models, total models and human photos in the sample and means on each higher education institution’s Web site by state ...... 57
Table 9: Comparisons on the representations of Asians, Asians’ buying power (BP), populations (AP) and numbers of higher education institutions (HE) in California, Florida, Michigan and Maine...... 63
Table 10: Paired correlations between a state’s proportion of Asian images (PAI)/misrepresenting Asians (MEAsian) and its buying power (BP), Asian population (AP) and numbers of higher education institutions (HE)...... 64
Table 11: Frequencies for Asian images’ status attributes in the sampled college and university Web sites ...... 67
Table 12: Frequencies and percentages of Asian models’ gaze directions by their accompanying ethnic group ...... 68
Table 13: Frequencies and percentage of Asian models’ interactions with others by accompanying groups...... 70
Table 14: Frequencies and percentage of study- and research-related settings and social settings in the sample...... 72 x
Table 15: Frequencies for Asian images’ power positions in presence of other ethnic models in the sampled college and university Web sites...... 74
Table 16: Frequencies of Asian images’ status attributes in the sampled sites by gender 78
Table 17: Frequencies for Asian images’ power positions by gender in presence with other ethnic models in the sampled college and university Web sites ...... 80
Table 18: A summary of the answers to the research questions and results of hypothesis tests ...... 81
Table 19: Comparisons between the portrayals of Asians and African Americans regarding the frequencies of models and mean number of models for each institution by state...... 85
Table 20: Comparisons between the portrayals of Asians and African Americans regarding proportionalities, predictors of the use of images and misrepresenting ethnicities by coast, by type of institution and by institutions’ rank...... 86
xi
List of Figures
Figure Page
Figure 1: The proportion of Asian images compared to the Asian population’s proportion in student bodies on the West and East coasts ...... 60
Figure 2: The proportion of Asian images compared to the Asian population’s proportion in student bodies in public and private higher education institutions...... 61
Figure 3: The proportion of Asian images compared to the Asian population’s proportion in student bodies in doctoral/research, masters and baccalaureate institutions ...... 62
Figure 4: The proportions of Asian and African American images on college and university Web sites compared to the proportions of Asian and African American students in the student body...... 84
1
Chapter 1
INTRODUCTION
“Today in marketing to students, the Web is everything, period.”
– Christopher Simpson1
Marketers gear their strategies for success in the marketplace. In college recruiting, two trends of the marketplace are remarkable and have consequently been shaping college and university admissions practices. One of the trends is that the World
Wide Web2 has become the most important information source for Internet users
(Roach, 2004); the other is that U.S. populations of people of color are growing in number and buying power faster than the non-ethnic majority (Schreiber & Lenson,
2001). In response, more and more colleges and universities have begun to use their
Web sites as a major venue to reach these increasingly diverse populations (Tedeschi,
2004).
College Web sites and admissions
Consumer behavior research suggests that buying behaviors can be better anticipated if marketers have a clearer understanding of how consumers search for information (Lindquist & Sirgy, 2003). More than a third (35%) of consumers anticipate relying on emerging news media in addition to traditional news media for information in the future (“LexisNexis Survey,” 2006). The Pew Internet and American Life Project has
1 Christopher Simpson, a marketing consultant in Williamsburg, Va. Quoted in Tedeschi (2004). 2 The Internet is a data communications network of thousands of smaller networks, through which computers of any type can interact with one another; the World Wide Web, or the Web, particularly refers to a way of presenting, linking and accessing information through the Internet (Flournoy, 2004). Many in the related literature have used these two terms interchangeably. 2 released a study showing that the Internet is the most important information source for many people facing an important decision; 45% of Internet users regard the Internet to be a crucial source in making their major decisions like buying a car, making a major financial decision and choosing a college (Horrigan & Rainie, 2006). Studies of high school students consistently report that the Internet culture generation, as marketers called Generation Y,3 relies heavily on the Web for seeking information (Blair, 2000;
Foster, 2003; Kwak, Fox & Zinkhan, 2002; Stoner, 2004; Tedeschi, 2004). As Internet
access is becoming universal, reaching 99% of Americans in 2003 (“Technology update,”
2003), U.S. high school students spend an average of more than seven hours a week
surfing on the Web (Blair, 2000). According to Noel-Levitz, James Tower and the
National Research Center for College and University Admissions survey, 49% of high
school juniors were online every day; their primary online activities included research for
school assignments, researching universities and reading news stories (“Engaging the
‘social networking’,” 2006; “Navigating toward e-recruitment,” 2006).
Although face-to-face communication and campus visits remain crucial in college applications (“Campus visit drives,” 2004), more and more students have turned to the
Internet searching for colleges and universities (Hollingsworth, 2006; “Online and on- campus,” 2006). Carnegie Communications surveyed 5,400 college-bound students about e-communication trends in 2001 and found that the Internet was considered the single most important tool in a college search (Klein, 2005). A study of Virginia high school students revealed that more than 94% of respondents rated the Internet as their primary source of information about colleges and universities (Tedeschi, 2004).
3 Generation Y, or Gen-Y, usually refers to those born roughly between 1976 to 1994 and who are characterized as sophisticated in using new technology, in multi-tasking and are optimistic economically and more diverse ethnically than any previous generation (Goman, 2006; Featherstone, 2007; Miller, 2006). 3
Among the numerous college-search resources on the Internet, individual college
Web sites are deemed to be the most valuable tool. Individual college Web sites often serve as students’ first entry point to a particular institution. According to the National
Association for College Admission Counseling’s (NACAC) survey of colleges and universities across the United States, higher education institutions’ Web sites are thought to be of great value as a first contact platform for students and schools (Hawkins
& Clinedinst, 2006). Moreover, for those who cannot afford to make a campus visit, a school’s Web site could be their only encounter with that college or university (Tedeschi,
2004). Finally, in addition to such information as admissions, academic programs and majors, visuals used on individual college Web sites enable viewers to have a general feeling for campus life, which results in a strong preference among college-bound students for going to individual college sites rather than to online information services4
to gather information (Jones, 2006; “Use of the Web,” 1998).
Several successful examples have provided further evidence that individual
college Web sites have been playing a key role in school admissions. Ohio University
credited its Web site for an increase in applications, especially out-of-state applicants
(Moseley, 2007). In 2005, Case Western Reserve University saw 50% more applicants
than in the previous year after having its Web site redesigned with the help of a
professional design company (Klein, 2005). The University of Dayton applied
personalized Web recruiting strategies in boosting the number of undergraduate
applications by 50% since 1996 and reducing the average cost of recruiting an applicant
by 17.5% (Foster, 2003).
4 Online information services refer to those integrated Web sites maintained by non-profit and for-profit organizations to provide relatively comprehensive higher education information and services, such as nces.ed.gov by the National Center for Education Statistics (NCES), located within the U.S. Department of Education and the Institute of Education Sciences and the site of Peterson’s at www.petersons.com. 4
The proliferation of the Internet has caught the attention of admissions officials and education researchers to the need for a strong online presence to reach prospective students (“Online and on-campus,” 2006). Many have recognized the Internet’s indispensable role in attracting college-bound students and delivering recruitment information (Carnevale, 2005; Gifford, Briceño-Perriott & Mianzo, 2005; Mentz &
Whiteside, 2003; Wolff & Bryant, 1999). Glossy brochures are outdated; virtual tours, personalized electronic newsletters, video magazines and interactive online admissions reflect the latest fashion in college recruiting (Blair, 2000; Foster, 2003; Tedeschi, 2004).
The 2003 Noel-Levitz National Enrollment Management Survey revealed that most colleges and universities made basic admission information and processes available through their Web sites in response to the increasing number of students using online tools in researching colleges and universities (“National enrollment,” 2003). The findings of the College Bound’s Annual Admissions Trends survey (“College Bound’s,”
2003) also indicated that 98% of colleges surveyed accepted online applications in 2003.
However, despite the general agreement on the Internet’s potential to reshape college admissions, little research has been devoted to examining the use of college Web sites in the recruiting process (Schneider, 2004). Beyond the case studies of Case
Western Reserve University (Klein, 2005), Franklin & Marshall College (Strout, 2006) and the University of Dayton (Foster, 2003), a broader overview is needed to analyze the use of Web sites in marketing to college-bound students around the nation. Moreover, researchers have placed much emphasis on exploring functional and informational aspects of the Web sites, such as detailed admission information, online applications, email newsletters, instant messaging, chat rooms, personalized Web pages, blogs and
Podcasting (“Engaging the ‘social networking’,” 2006; Hawkins & Clinedinst, 2006;
Mentz & Whiteside, 2003; “Navigating toward e-recruitment,” 2006; Poock & Bishop, 5
2006; Stoner, 2004). Few academic studies have concentrated on the use of visual elements on college and university Web sites (Schroeder, 2002). In effect, professional experiences have suggested that visuals on the Internet have much influence on students’ attitudes toward a particular college or university because they offer online visitors a glimpse of the “real” campus (Jones, 2006; Murray, 2000; Schroeder, 2002; Stoner,
2004). Online virtual tours, one of the most sophisticated new recruiting tools, provide still and moving images highlighting college life (Blair, 2000); campus pictures on college sites enable students to gain a general feeling about the campus (Jones, 2006;
“Use of the Web,” 1998).
Although an ample amount of Internet marketing literature has tapped into the many aspects of modern society (Lee, 2001), research is often dominated by an information-processing approach and lacks a comprehensive look from a visual- consumption perspective (Schroeder, 2002). Empirical evidence has shown that visual elements have a crucial impact on students’ information searches (Blair, 2000; Stoner,
2004). It is necessary and beneficial to systematically examine the use of visual elements, especially the images on college Web sites.
Ethnic diversity
A study of community college Web sites suggested that Web pages “should reflect
a ‘distinguished’ institution, and indicate success and diversity in pictures” (Poock &
Bishop, 2006, p. 692). Ethnicity is one of the widely studied and discussed diversity
issues. As a way of categorizing people, ethnicity has been considered as a means of
defining cultural identities (Downing & Husband, 2005). In relation to ethnicity, race is
a term for categorizing humans based on biological characteristics (Oommen, 1994).
However, the concept of race has been generally attached to racism, “a social evil” and 6
“politically divisive ideology” (Downing & Husband, 2005, p. 12) because race has become a constructed social category based on the belief that some races are inferior and others are superior (Oommen, 1994; Winant, 2000). Therefore, ethnicity has been frequently and positively employed in politics and social sciences (Downing & Husband,
2005). Yet, due to cultural differences and social disparity, ethnic issues such as stereotypes and discrimination still remain.
The recognition and promotion of an ethnically diverse student body in colleges and universities partially reflects U.S. demographic shifts and market trends. The proportion of U.S. ethnic minorities, including African American, Hispanic and Asian or
Pacific Islander students, increased from 15% in 1976 to 29% in 2001 (Snyder, Tan &
Hoffman, 2004). The U.S. Census Bureau estimates that ethnic minority students will account for 44% of the school-age population by 2020 and 54% by 2050, becoming the majority in U.S. classrooms (The Alliance for Equity in Higher Education [AEHE], 2000).
A rapidly growing number of undocumented immigrants may stretch the proportion of U.S. ethnic minorities even further. Population analysts estimate that the number of undocumented immigrants has jumped from 3.5 million in 2000 to 12 million in 2006, adding up to 26% percent of the total foreign-born population (Nasser, 2006;
Passel, Capps & Fix, 2004). The growth of undocumented immigrants has raised national concerns about social welfare and education for those illegal immigrants. For instance, as of 2004, an estimate of 1.6 million children under 18 were undocumented immigrants coming to the United States with their parents; another 3 million children were born in undocumented families, most of whom had little education and limited
English skills (Passel et al., 2004).
Marketers, witnessing the demographic shift reshaping the marketplace, are striving to alter their practices to manage diversity (Gilbert, Stead & Ivancevich, 1999; 7
Schreiber & Lenson, 2001; Thaler-Carter, 2001; Zahra, Ireland & Hitt, 2000). Many colleges and universities tend to recruit minority students to improve the inclusiveness of under-represented ethnic groups. In 2003, 33% of U.S. colleges and universities factored ethnicity into their admissions decisions (Marklein, 2003); 74% had included a
commitment to diversity of some form in their mission statements and had employed
specific recruitment activities to increase ethnic minority populations in their student
body (NACAC, 2003). An investigation into the recruiting of ethnic minority students as
psychology majors found that 64% of colleges and universities created recruitment
materials specifically targeted to ethnic minority students (Rogers & Molina, 2006).
More than a simple parallel of the rapidly changing demographics, recruiting
minority students reflects concerns from the public. Research found that the increasing
number of undereducated minorities would become a threat to the U.S. economy
(Astone & Nuñez-Wormack, 1990). The American Council on Education (ACE, 2004)
pointed out that 30 years after the Brown v. Board of Education Supreme Court decision, minorities, particularly African Americans and Hispanics, continued to lag behind at all levels of educational attainment. Given the present level of minority education and the growth of minority populations, the potential shortage of qualified workers would become the center of the government and industry’s attention (“Still trailing behind,”
1990).
On the other hand, a diverse student body is believed to benefit the overall educational environment and can strengthen communities. Gurin, Lehman and Lewis
(2004) reasoned that ethnically diverse environments fostered active engagement in learning and motivated students to be citizens and leaders in a democratic society; these educational benefits for learning and democracy outcomes extended to all students.
Many scholars believe that in a modern society, a heterogeneous workforce brings 8 different perspectives to work and is more likely to solve problems creatively and effectively (Crosby, Iyer, Clayton & Downing, 2003; Rogers & Molina, 2006). A diverse student body is also important for education in certain professions. For instance, Chung
(2004) noted that minority physicians were more likely to work with minority
populations, which normally had low access to health care; conversely, minority patients
were more likely to seek out minority doctors. This particular market relationship led medical schools to consider enlarging their ethnic student enrollment.
Many studies have provided sound evidence on the efficacy of the inclusiveness of diversity in recruiting materials. Chung (2004) proved that diversity’s contribution to an enriched educational experience for all students would consequently appeal to prospective students who were searching for that kind of experience. According to Rau and Hyland (2003), diversity statements in an organization’s recruitment brochures significantly affected applicants’ attitudes toward that organization, and organizations were thus advised to advertise diversity to attract applicant pools with larger representation of minorities. Kim and Gelfand (2003) arrived at a similar conclusion after comparing the effects of recruiting brochures with and without a diversity initiative.
They incorporated an individual’s level of ethnic identity to find that people with higher levels of ethnic identity would produce more positive evaluations of an organization whose recruiting brochure had a diversity initiative (Kim & Gelfand, 2003).
When studies have recommended advertising diversity in recruitment, the employment of this strategy, such as using minorities’ images, is usually a reconciliation of some philosophical and political objectives. There is a long-lasting, nationwide debate over the consideration of ethnicity in college admissions (Kane, 2003). On June 23,
2003, the U.S. Supreme Court issued a landmark ruling that universities could consider 9 an applicant’s ethnicity in school admissions.5 The court’s decision was largely driven by
the fact that selective universities would admit very few African American or Hispanic
students if their academic performances in high school were the only criterion. The
court’s ruling affects Asian Americans because an ethnicity-conscious admission policy
may reduce the chances of Asian Americans, who are more academically successful than
other minorities, by giving more chances to other minority students (Schmidt, 2003).
Recruiting ethnic minorities is frequently a compromise of affirmative action and
academic fairness.
As a result, the complex nature of the diversity issue may, to some extent, cause
higher education admissions officials to be more ethnicity conscious than ever in
recruiting. Consequently, the representation of ethnic minorities, especially Asians, on
college and university recruiting materials including the Web sites can illustrate the
trade-off of marketing, educational, philosophical and political considerations on this
matter, which is worthy of a close examination.
Asian images on campuses
Due to their growing populations, buying power and academic achievements,
Asian Americans are becoming a unique target of U.S. colleges and universities. The
appearance of Asian faces on campuses enriches the academic and cultural environment
of U.S. colleges and universities in terms of diversity. Thus, an increasing number of U.S.
colleges and universities have been marketing to Asian countries because recruiting
students from foreign countries can be a “cash cow” for higher education institutions
(“Fewer foreigners,” 2004). As a result of admissions officials’ proactive recruiting
efforts, international enrollments in U.S. colleges and universities increased 8% after five
5 Grutter v. Bollinger, 123 U.S. 2325 (2003) and Gratz v. Bollinger, 123 U.S. 2411 (2003). 10 years of decline since 9/11/2001 (“Enrollment recovering,” 2006). Given a mixed picture of Asian Americans and Asian students, the study of Asian images in college Web sites cannot avoid either of them.
Asian Americans represent a fast-growing market in the United States. Increased from 3.5 million in 1980 to 10.7 million by 2000 (Barnes & Bennett, 2002), Asian
Americans have become the fastest growing minority during the 1990s (Harris, 1999). A continued growth is projected, so that by the year of 2050 the Asian American population will be 33.4 million, or 8% of entire U.S. population (U.S. Census Bureau
[USCB], 2004). Besides their growing numbers, Asian Americans’ high education level and rising buying power have further attracted marketers, including college admissions officials. Forty-four percent of Asian Americans hold a bachelor’s degree, compared to
24% of the overall U.S. population; Asian Americans are more likely to have a household computer (65%) and Internet access (56%) than any other group (Barnes & Bennett,
2002); and they are also reported to be the heaviest everyday Internet users among all the ethnic groups including Whites (Nakamura, 2005; Spooner, 2001). The median annual household income of Asian Americans is $59,324, higher than the $50,046 U.S. average (Barnes & Bennett, 2002). The Selig Center for Economic Growth at the
University of Georgia reported that Asian Americans’ buying power rose to $254.6 billion in 2000, more than double its 1990 level (Humphreys, 2005). By 2007, Asian
Americans’ buying power is expected to increase to $454.9 billion, which reinforces the attractiveness of this minority group to colleges and universities recruiters (Vence, 2004).
Asian Americans per se are a fairly diverse ethnic group. According to Harris
(1999), Asian Americans’ immigration history can be traced back to the large group of
Chinese railroad laborers imported to the west of America in the 1800s; in the early 20th century, Japanese immigrants began to move to the United States; after World War II 11 and the Vietnam War, a growing number of Koreans, Filipinos, Vietnamese and other
Southeast Asians came to America; immigrants from South Asia added to this group
substantially. The U.S. census in 2000 showed that immigrant Asian Americans, who
included Chinese, Filipinos, Asian Indians, Vietnamese, Koreans, Japanese, Cambodians,
Hmong, Laotians, Pakistanis and Thais, had origins from more than 30 countries and
spoke more than 100 languages (“National population estimates,” 2000). Demographic
data also indicate that the education levels and household incomes vary greatly among
Asian subgroups. For instance, although 80% of total Asian Americans have completed
high school, half of Laotian Americans have less than a high school education; the
median household income of Japanese Americans reaches $70,849, whereas Hmong
Americans’ median household income is $32,384, less than half that of the Japanese
(Barnes & Bennett, 2002).
International students are another important source of diversity on college and
university campuses (Zhao, Kuh & Carini, 2005). In the 2004 to 2005 academic year,
there were 573,000 international students enrolled in the U.S. colleges and universities,
which was 4% of colleges and universities’ total enrollments, having increased from 2.8%
in 1990 (Snyder, Tan & Hoffman, 2006). According to NAFSA’s (2005) estimation,
international students and their dependents contributed $13.3 billion to the U.S.
economy during that academic year. After 9/11/2001 terrorist attacks, various reasons,
including a stricter visa policy, caused a decline in international student enrollment until
2006, when U.S. colleges and universities gradually regained foreign students at a rate of
8% (“Enrollment recovering,” 2006; Kim, 2006). The majority of international students
were from Asian countries (56.6%), followed by Europe (12.9%), Latin America (12.2%),
Africa (6.7%), the Middle East (5.6%), North America (4.8%) and Oceania (.8%)
(Institute of International Education [IIE], n.d.). 12
There is a long history of stereotyping of Asians in the U.S. society and media
(Iiyama & Kitano, 1982). Compared to African Americans and Hispanic Americans,
Asians are portrayed more positively in U.S. media (Harris, 1999). The term “model minority” is often associated with Asian Americans. The emergence of Asian Americans as the model minority became popular in the mid-1960s when New York Times
Magazine and U.S. News & World Report published two articles commenting on
Japanese Americans’ and Chinese Americans’ good behavior and economic success in the United States (Fong, 2002).
Ironically, the positive stereotype has troubled the Asian community in many ways. For instance, because Asian American and Asian students were academically more successful than other minorities, in the 1980s this ethnic group was “over-represented” at some elite universities relative to the size of its U.S. population (Takagi, 1990). Some prestigious U.S. universities, including Harvard, Yale, Princeton, Stanford, the
University of California at Berkeley and the University of California at Los Angeles, reportedly employed an “Asian quota” to limit the enrollment of Asian American students (Dong, 1995; Takagi, 1990). The U.S. Supreme Court’s landmark ruling in 2003 and affirmative action do not necessarily benefit Asian Americans and students from
Asian countries. Keeping ethnicity within consideration, colleges and universities will likely reduce the number of Asian Americans in favor of other minority students to pursue an ethnic balance on campus (Schmidt, 2003). As a result, Asian Americans, as a unique ethnic group, could be facing serious discrimination in college admissions (Fisher,
Wallace & Fenton, 2000; Schmidt, 2003; Takagi, 1990).
Whether this type of discrimination against Asian Americans and Asian students exists, and whether this discrimination is reflected in college admissions strategies, particularly regarding the use of visuals on Web sites, deserves an examination. 13
Purpose of this study
Colleges and universities have enthusiastically employed Web sites to market to minority students (Rogers & Molina, 2006), where visuals are considered fairly effective in conveying vivid and reliable messages (Blair, 2000; Stoner, 2004). Empirical evidence suggests that including a member from a minority group in an advertisement enhances the campaign’s marketing effects (Stevenson & Swayne, 1999). Using Asian images on college and university Web sites might influence the prospective Asian Americans’, Asian countries’ and other ethnic students’ evaluations of the institutions. Studying the visual
representation of ethnic minorities, especially Asian American and Asian students in the
college admission process, is a significant matter, to which previous studies rarely paid
attention. This study fills this research gap.
The focus of this study is on the portrayals of Asian American and Asian students
on U.S. college and university Web sites. By analyzing the image representation of Asian
American and Asian students, this study assesses the proportionality and stereotyping of
Asians in an educational environment, interprets the social implications behind the
screen and sheds light on ethnic representations, visual consumption and some
emerging higher education marketing issues in the Internet era.
Organization of this study
Chapter 1 outlined the research context and purpose. Chapter 2 establishes the
theoretical framework, presents related studies and proposes research questions and
hypotheses. Chapter 3 explicates the research method and procedures. Chapter 4
exhibits the findings and answers research questions and hypotheses. Chapter 5
discusses the findings and provides conclusions. 14
Chapter 2
RELATED STUDIES
Visual consumption
The Internet is a visual medium that has a role in almost every aspect of marketing strategy, practice and communication (Flournoy, 2004; Murray, 2000;
Schroeder, 2002). In addition to attracting attention and conveying messages, evidence shows that visual presentation on the Internet has a positive impact on consumers’ mood and purchase intention (Park, Lennon & Stoel, 2005). Improving online visual presentation will be helpful in creating the best environment and keeping competitive in the marketplace (Khakimdjanova & Park, 2005). Therefore, a discussion of visual consumption becomes relevant to college and university online recruiting practice.
Images intrude into everyday life (Lester, 2006). Many disciplines, including sociology, psychology, political science and communication, have studied the power and influences of visuals on people and society. Empirical research suggests that people process verbal messages and imagery information in different ways (Boush & Jones,
2006). MacInnis and Price (1987) proposed that people perceive images through a mode of processing in contrast to the discursive processing of verbal information. Paivio (1986) introduced the dual coding theory that imagery messages were encoded analogically and symbolically, whereby the number of associations increased and people’s memory was enhanced. Branthwaite (2002) offered a brief summary on the use of images in cognitive behavioral therapy, sports, medicine and healing, and their role in problem solving, inspiring creativity, controlling affective states, assisting athletes in concentration and integrating mind and body functions. 15
Research in political science indicated that photographs played an important role in political campaigns by vividly delivering candidates’ attributes of realism, credibility and truthfulness (Moriarty & Popovich, 1991; Verser & Wicks, 2006). For instance,
Graber (1988) pointed out that images were valuable in shaping attitudes due to their special ability to gain attention, convey a sense of credibility and evoke emotions. As a result, political campaigns often strategically use visuals as a powerful tool in persuading voters. In an extreme case, Candidates in the 2004 U.S. presidential campaign who relied heavily on “photo opportunities” rather than explaining substantive issues were criticized for their overusing visuals (Lester, 2006).
In marketing research, the use of images in branding (Boush & Jones, 2006; Lutz
& Lutz, 1977; Robertson, 1987), persuasion (Markham & Hynes, 1993; Mazzocco & Brock,
2006) and consumption (Schroeder, 2002) has attracted much attention from scholars and marketers. Particularly, advertising greatly relies on images (Goffman, 1979;
Schroeder, 2002). Numerous advertising studies have strived to understand the image’s role in catching attention, conveying messages and altering attitudes (Barnard, 2005;
Lester, 2006; Messaris, 1997). Visuals are believed to influence the formation of product attributes, attitudes toward the ad and the consumer information search process
(Childers, Houston & Heckler, 1985; Mitchell, 1986; Sojka & Giese, 2001). Markham and
Hynes (1993) pointed out the images’ persuasive role and emphasized that as a vivid representation of the environment stored in people’s minds, images might confer realities and thus lend credibility to arguments that were otherwise unbelievable.
Mazzocco and Brock (2006) further explained that images became more persuasive when they were more difficult for viewers to resist than verbal messages.
Schroeder (2002) called attention to the notion of “visual consumption,” a process that interacts between consuming and producing social identities. He noted that 16 visual consumption is a critical component in contemporary culture, which is awash in marketing images. When consumers are responding to signs, symbols and images in the marketplace, they are involved in a complex cognitive process (Schroeder, 1998). While most products are marketed to a specific group of consumers, people in the marketplace become aware of the associations between certain products and a certain group of consumers. Once consumers follow the associations to purchase and consume a product, their activities essentially reinforce the definition of that product and the identity associated with that product. Schroeder (2002) said that identity can entail what one imagines others seeing, including one’s physical appearance, clothing style, tattoos, car, home decoration and schools; consumer culture trades on imagery, desires, passions and identity. Schroeder and Zwick (2004) concluded that because of advertising’s representational system and signifying mechanisms, it was important to study the connections between visual culture conventions and their impact on advertising images.
In such a perceptual process of representing identity through consuming certain
products, photography is considered the most widely used and the most powerful
imagery tool of representation (Schroeder, 2000). Photography becomes a central way of
representing identity because it is in essence a process of selection, in which
photographic practices and conventions give rise to the objects, places and people
photographed in the very composition of the picture (Bourdieu, 1990; Lester, 2006;
Sontag, 1977). Photographs are “an artfully arranged manipulation” of reality, which is
able “to arouse desire, fantasy, and longing,” and to make viewers “to participate in the
world they [the pictures] portray” (Bordo, 1997, p. 122).
Goldman and Papson (1996) stressed marketing campaigns’ ideological
significance by outlining several sociological features of advertising images; they argued
that advertising images socially and culturally constructed a capital-intensive world. The 17 concept of construction of reality includes creating and representing social identities. In many advertisements that feature people, social identities are conveyed primarily through the display of a product along with people in a social context (Leiss, Kline &
Jhally, 1990).
Researchers are interested in exploring the mechanisms of images’ construction of a social identity from various perspectives. For example, by comparing visual messages to verbal messages, Branthwaite (2002) concluded that images had a more direct connection to feelings and unconscious ideas; they were more likely to be perceived unconsciously as a whole rather than in a linear, rational fashion. Sojka and
Giese (2001) discovered that people with a high need for affect preferred visual rather than verbal messages. Greenfield (2000) provided evidence from neurophysiology that people were using the same areas of the brain for vision and visual imagination. In other words, when being exposed to an image, people tend to interpret them as analogies of similar objects, things and memories (Messaris, 1998). The mixed findings from the previous research suggest that affect and cognition may work independently or together
(Epstein, Pacini, Denes-Raj & Heier, 1996; Giese & Sojka, 1998; Sojka & Giese, 2006).
From a cognitive approach, Goffman’s (1979) classic study of gender advertisements concentrated on models’ hands, eyes, facial expressions, relative sizes, positioning, head-eye aversion, finger biting and sucking to reveal the stereotypical portrayals of genders in advertising photographs. He classified photographs into different categories, such as public and private photos, to understand that advertisers used certain mental schemas or frames in photographs to recreate realities for viewers.
Goffman (1979, p. 23) states,
The magical ability of the advertiser to use a few models and props to evoke a life-
like scene of his own choosing is not primarily due to the art and technology of 18
commercial photography; it is due primarily to those institutionalized
arrangements in social life which allow strangers to glimpse the lives of persons
they pass, and to the readiness of all of us to switch at any moment from dealing
with the real world to participating in make-believe ones.
The notion of “institutionalized arrangements” embraces the concept of mental schemas that refers to the existing knowledge in people’s minds for processing news information.
Schema theory takes a cognitive approach to explain how people make sense of an image and form an attitude to the object portrayed in the image, which can be a valuable theoretical ground for the investigation of online representation of Asian American and
Asian students.
Schema theory
The early use of schema and its concept can be traced to Plato, Aristotle and Kant
(McVee, Dunsmore & Gavelek, 2005). According to Kant, schemas are organizing structures that mediate people’s perceptions of the outside world (Johnson, 1987).
Cognitive psychologists believe that schemas are data structures for representing the knowledge stored in people’s memories (Rumelhart, 1984; Taylor & Falcone, 1982).
Schemas serve a crucial role in the interactions between old knowledge and new knowledge in perception, language, thought and memory (Brewer & Nakamura, 1984).
Researchers have noticed that people’s limited capacity for dealing with information forces them to use simplified mental maps or shortcuts to process messages (Fiske &
Taylor, 1991). Individuals seldom comprehend all relevant information to make a judgment. Instead, they normally form a decision with what is most accessible in their minds, which can be called cognitive efficiency and economy (Taylor & Falcone, 1982). 19
Schema theory holds that people activate certain mental images or schemas to help them select and organize new information in a meaningful way (Axelrod, 1973;
Graber, 1988; McLeod, Kosicki & McLeod, 2002; Shah, Domke & Wackman, 2001).
Graber (1988) introduced schemas’ four major functions in the course of information processing: determining “what information will be noticed, processed and stored so that it becomes available for retrieval from memory;” helping “individuals organize and evaluate new information so that it can be fitted into their established perceptions;” making “it possible for people to go beyond the immediate information presented to them and fill in missing information, which permits them to make sense of incomplete communications;” and helping “solve problems” (Graber, 1988, p. 29).
In visual communication, theorists state that images constitute an analogical system of communication, in which the brain perceives a picture by placing it within a preexisting visual symbol (Axelrod, 1973; Graber, 1988; Messaris & Abraham, 2001;
Verser & Wicks, 2006). Schroeder (2002) explained that comprehending images relies on the personal understanding of symbols, conventions and stereotypes to establish associations between individuals’ common sense and the social context presented in the pictures. In other words, people use symbols to structure all their experience. In information processing theory, the set of symbols are schemas, which enable people to routinely perceive information (Axelrod, 1973; Entman, 1993; Gitlin, 1980; Goffman,
1974; Reese, 2001).
During the interactions between mental schemas and external information, a related framing effect is most likely to occur. Framing or frames are conceptually similar to schemas in communication research. Framing exists at two levels: individuals’ mental schemas and media frames (Entman, 1991; Scheufele, 2000). Media frames serve as working routines for media workers, allowing them to quickly identify information that 20 needs to be conveyed; individuals’ schemas are mentally stored symbols of ideas that affect receiving and perceiving information.
Entman (1993) related how frames exerted power in the process of mass communication. He noted that “frames highlight some bits of information…, thereby elevating them in salience” (p. 53). Making a piece of information more noticeable, meaningful or accessible increases the probability that audiences will make sense of the information.
D’Angelo (2002) distinguished three paradigms of framing research: cognitive, constructionist and critical. The cognitive paradigm focuses on the negotiation between the salient information in mass media and individuals’ schemas of knowledge (D’Angelo,
2002). The constructionist paradigm introduces the idea that the media develop frames by selecting and excluding certain parts of information to construct meanings and a perceived reality (Gamson & Modigliani, 1989; Hertog & McLeod, 2001). The critical paradigm accentuates ideology (Entman, 1991, 1993; Gitlin, 1979, 1980; Tuchman, 1978), reflecting values held by political and economic elites (D’Angelo, 2002).
Framing analysis can connect studies of media content to those of media effects, concerns at the individual cognition level to those at a macro level and interpretations of an individual’s perception to social and ideological contexts (Bryant & Zillmann, 2002).
To conduct an analysis of schema and frames, Gamson and Modigliani (1989) developed the notion of “media package” for measuring media frames. The media package includes a set of symbolic devices, such as metaphors, exemplars, catchphrases, depictions and visual images, which will help delineate a particular frame.
Actually, a rich body of framing research has been performed to examine various media and messages. For instance, Goffman (1979) applied frame analysis to investigate advertising and argued that advertising influenced people’s perception of women by 21 conveying a set of social cues. Women were framed as less serious and more playful than men in numerous advertisements.
Framing analysis is also widely applied to observe online content. One of the
most evident differences between new media and traditional media is the
communication symbols and how those new symbols in media content construct
meanings. This has interested media researchers (Fredin, 2001). Zillmann and
colleagues (2004), who examined the news leads in the new media environment, found
that online news coverage tended to attract audiences by framing aggravated conflicts or
the agony of suffering in news leads. Hawthorne (2004) focused on global cyber-culture
and its impact on women. She criticized the Internet as a symbolic device for exploiting
women through making them continuously accessible to mobile men (Hawthorne, 2004).
Downing and Husband (2005), who examined research on racism, ethnicity and media,
insisted that framing was useful for research in race and media “because of the visual in
‘race’ and ethnic relations, and in media” (p. 37).
Schemas of Asian images
There is a fairly long tradition in studying portrayals of Asian Americans in films,
fiction books, television, newspapers and other media (Fong, 2002; Iiyama & Kitano,
1982; Knobloch-Westerwick & Coates, 2006; Lee, 1996; Wu, 1996). From the 1840s to
the 1940s, the media portrayed Chinese, Japanese, Koreans and Filipinos as
“Mongolians,” “Yellow Peril,” “Little Brown Monkey” and “Rag heads” (Chan & Hune,
1995). In the 1950s, studies of Americans’ mental images of China and India revealed
that portrayals of Chinese and Indians were closely associated with the political
relationship between the United States and these two countries (Isaacs, 1958; Jones,
1955). According to Lee (1996), before the 1960s Asian Americans were usually 22 stereotyped in “devious, inscrutable, unassimilable, and in other overtly negative ways”
(p. 6). In the late 1960s and 1970s, the immigration of middle-class professionals from
Asia introduced a new image of Asian Americans as a model of assimilation into middle- class Americans (Davé, Nishime & Oren, 2005). In the 1980s, America’s elite media, including Time, Newsweek, Fortune, NBC and CBS news programs, framed Asian
Americans as a “model minority” in terms of their lower incidence of criminal activity and almost no juvenile delinquency, their healthier physical and mental status, their higher incomes and their students’ higher scholastic achievement than other minority students (Chen & Hawks, 1995; Cheng, 1997; Cohen, 1992; Fong, 2002; Sue, 1994;
Takaki, 1995; Varma & Siris, 1996). Wu (1996) also noted that there seemed to be a
“distinction or discrepancy between the images of the Chinese held by people on the East
Coast as opposed to Californians; intellectuals versus laborers; high-brow literature and popular fiction; and so forth” (p. 71).
In the marketing research area, studies regarding portrayals of Asian Americans emerged in the 1990s (Lee, Williams & LaFerle, 2004). A twofold conclusion was often embraced by the existing studies about Asian images: on the one hand, this ethnic group was largely under-represented; on the other hand, the portrayals that did exist were generally stereotyped (Bang & Reece, 2003; Bowen & Schmid, 1997; Fong, 2002; Frith,
Cheng & Shaw, 2004; Mastro & Stern, 2003; Taylor, Landreth & Bang, 2005; Taylor &
Lee, 1994; Taylor & Stern, 1997).
Under- or over-representation
Proportionality is useful in assessing the frequency of the representation of a group in media portrayals (Wilkes & Valencia, 1989). It compares the frequency of the minority group’s presence to the group’s level of representation in a certain population 23
(Taylor, et al., 2005). The interest in studying proportionality has a root in racial ideology and hegemony that dominant groups in a society maintain and legitimate their power over other minority groups through various means including the mass media
(Hirshman, 1993). Under-representation of ethnic minorities might lead to a perception that those minority groups, as consumers or members of society, are not worth much attention (Knobloch-Westerwick & Coates, 2006).
Empirical research shows a complex picture of the proportionality of Asians portrayed in the U.S. media. Knobloch-Westerwick and Coates (2006) summarized studies of U.S. mainstream magazines in the 1990s and discovered representation in ads with Asian Americans ranging between 1% and 10% (4.2% on average). An analysis of magazine advertisements in 1992 revealed that the presence of Asian Americans in magazine advertisements decreased from 2.5% in 1987 to 1.8% in 1992; during the same period of time, however, the portrayals of African Americans rose from 6.8% to 10.6%
(Bowen & Schmid, 1997). A cross-national study of magazine ads in 2000 and 2001 also discovered that Asian Americans were under-represented in U.S. women’s magazines; merely five out of 481 ads contained Asian models in Glamour, Vogue and Elle (Frith et al., 2004). The under-representation of Asian Americans also occurred in mainstream consumer magazines, such as Popular Mechanics, PC World, Fortune, Business Week,
Times, and U.S. News & World Report, in 2000 and 2001 (Lee & Joo, 2005).
Rather than being under-represented, Asian Americans were portrayed disproportionately high in advertisements for technology-based products, in the business press and in scientific magazines (Taylor & Lee, 1994; Taylor & Stern, 1997).
Such a conflicting finding suggests that product category or occupational settings are an important function of the presence of Asians. In other words, the representation of
Asians will be found comparatively high in some scenarios associated with the “model 24 minority” stereotype (Taylor & Lee, 1994; Taylor & Stern, 1997). Bang and Reece (2003) further confirmed this association in their study of children’s television commercials, in which they found that Asian models well represented the Asian American population except in commercials for toys, clothing and movies.
These pieces of evidence indicate that the presence of Asian Americans and people from Asian countries depends on the product category (technology related versus
general household products), media type (business and scientific media versus popular
and women’s media) and occupational settings (business versus household settings).
Given the seemingly conflicting findings, on college and university Web sites, the
proportion of the representation of Asians becomes a question:
RQ1: Will the proportion of Asian images on a college or university’s Web site
exceed the proportion of Asian American and Asian students in that institution’s
student body?
Studies further propose that factors such as geography, school type and school
ranking may to some degree alter the presence of Asians. For example, according to Wu
(1999), the suspected distinction between the images of Chinese perceived by people on
the East Coast versus Californians may propose a difference in the image usage between
colleges and universities on the East Coast versus West Coast of the United States. As a
result,
RQ2: Will the proportion of Asian images on college and university Web sites in
West Coast states differ from that of colleges in East Coast states?
The U.S. colleges and universities can be categorized into public institutions and
private institutions (U.S. Department of Education [USDE], n.d.), or Baccalaureate 25
Colleges, Masters Colleges and Universities, Doctoral/Research Universities and other categories, such as school of art, music and design and other separate health profession
schools (The Carnegie Foundation for the Advancement of Teaching [CFAT], 2006). It
will be worthwhile to observe differences of proportion of Asian images among various
types of higher education institutions. Thus,
RQ3: Do public and private colleges and universities differ in the proportions of
Asian images used on their Web sites?
RQ4: Do undergraduate instructional, masters instructional and
doctoral/research instructional colleges and universities differ in proportion of
Asian images presented on their Web sites?
Literature also shows that population shifts are not the only indicator of the
representation of minorities (Barnes & Bennett, 2002; Harris, 1999). Instead, Pietilainen
(2006) examined economic factors in the media’s daily practice, concluding that
economy played a critical role in the media’s decision-making process. In market-driven
college recruiting, Asian Americans’ economic power, defined as buying power in this
study, should be considered as another significant predictor of their presence on the
college Web sites. Therefore,
H1: There is a direct relation between the proportion of Asians’ images on college
and university Web sites and changes in Asian Americans’ buying power in those
states.
A discussion on the recruitment of Asian American students must take into
consideration the debate over affirmative action and academic fairness in U.S. higher 26 education. As researchers have noted, even though some prestigious universities denied using the so-called Asian quota, affirmative action might not necessarily benefit Asian
American students, who in fact were facing some discrimination in college admissions, especially from some elite universities (Dong, 1995; Fisher et al., 2000; Schmidt, 2003;
Takagi, 1990). Thus,
H2: The proportion of Asian images on the Web sites of lower-ranking colleges
and universities is more accurate than that of higher-ranking colleges and
universities in matching the reported proportion of Asians in student bodies.
Stereotyping Asians
Besides being under-represented and occasionally over-represented, Asian
Americans are frequently stereotyped when they appear in the U.S. media (Bang & Reece,
2003; Bowen & Schmid 1997; Frith et al., 2004; Lee & Joo, 2005; Knobloch-Westerwick
& Coates, 2006; Mastro & Stern, 2003; Taylor et al., 2005; Taylor & Lee, 1994; Taylor &
Stern, 1997; Thomas, Cheng & Cooper-Chen, 2006). Finding stereotypical Asian images
in the U.S. media is “like shooting fish in a barrel” (Brislin, 2003, p. 111). Regardless of
the diversity within the Asian American group, the U.S. media tend to stereotype the
Asian Americans as one ethnic group in general (Taylor & Stern, 1997).
A great many studies have attempted to interpret the schemas applied in
stereotyping this group. Before the 1990s, of the few characters on television dramas,
Asians were frequently portrayed as villains or stereotyped as laundry and restaurant
owners (Harris, 1999). Wu (1996) studied the portrayal of the Chinese in prime time
network television dramas and found that Chinese images were comparatively distorted
and misleading. Newspapers covering Asian immigration often used headlines like
“Asian invasion” or “containing Japan” (Funabiki, 1992, pp. 13–14). In non-Asian 27
Americans’ minds, Asian Americans were generalized as hardworking and thrifty
(Delener & Neelankavil, 1990).
In advertising, Asian models are usually portrayed as passive, submissive and devoted to work (Taylor & Stern, 1997). They are often portrayed in business suits or
used for advertising technology-based products (Taylor, Lee & Stern, 1995). Paek and
Shah (2003) analyzed U.S. magazine advertising and identified several aspects of Asian
Americans’ stereotypical images as a model minority, such as financial success, technological savvy and academic excellence. Stereotypical Asian images also influence education. Kim and Yeh (2002) stressed that stereotypes of Asians caused Asian
American students’ emotional distress and created conflicts with their peer students. Lee
(1996) found that non-Asian American students stereotyped Asian students as being
“geniuses,” “overachievers,” “nerdy,” “great in math and science,” “competitive,”
“uninterested in fun” and “4.0 GPAs.”
In terms of personality and behavioral stereotypes, Asian American students are thought to be “submissive,” “humble,” “passive,” “quiet,” “compliant,” “obedient,”
“stoic,” “devious,” “sneaky,” “sly,” “tend to hang out in groups,” “stay with their own
race,” “condescend to other races” and are “racist,” “not willing to mesh with American
culture,” “try to be like Americans,” “want to be Caucasian” and “act F.O.B.6” (Lee, 1994,
1996; Yeh, 2001). Moreover, the physical appearance and mannerism stereotypes of
Asian Americans include “short,” “slanted eyes,” “eyeglass wearing,” “poor or non-
English speaking” and “poor communicators” (Lee, 1996).
Stereotypical Asian images seem ubiquitous in the media and marketing practices.
Whether a stereotype of this ethnic group has been represented in colleges’ marketing
6 F.O.B. refers to fresh off the boat, a somewhat derogatory slang phrase applied to people of foreign nationality who have arrived in a host nation as tourists, immigrants, students, or most commonly, as work permit applicants. 28 strategies requires an assessment. The following analysis inspects stereotyping Asians from two dimensions: individual characteristics (status) and interactions with others
(power position).
Status Previous studies indicate that Asian Americans are usually portrayed as
passive and submissive (Taylor & Stern, 1997), neutral (Thomas et al., 2006), quiet,
humble and compliant (Lee, 1994, 1996; Yeh, 2001). Goffman (1979) offered in his
gender advertisement study a few visual cues that symbolized subordination: looking
away or with eyes closed (gaze); bent knee, bowed or leaning body (posture); hands at
side or at rest (hands); arm at side, resting or folded (arms). Impression management
theory has also identified several behaviors and attributes that would encourage an
active and positive impression of an individual in others’ minds (Jones & Pittman, 1982).
Among those attributes, the “status” or potency dimension is helpful to evaluate their
individual characteristics (Rosenberg & Bonoma, 1974). An individual with higher status
owns more strength and appears more active in a social occasion (Bononma & Felder,
1977). This study adopted a few of the low-status visual cues from Verser and Wicks’
(2006) summary: alone or appearing alone (interaction); showing serious or concerned
expression (expression).
Stereotypical Asian images also involve the settings where Asian models are
presented. Studies about Asian images consistently report that Asian Americans and
Asian populations are serious rather than fun loving (Yim, 1989); they are not socially
skilled (Taylor & Lee, 1994). Instead, the model minority stereotype encourages people
to see Asians according to their work ethic, hardworking, intelligent, genius-like and
overachieving (Kim & Yeh, 2002; Paek & Shah, 2003; Taylor et al., 2005; Taylor & Lee,
1994). As a result, empirical studies show that Asian models are depicted more often in
business settings and the workplace than in social settings, outdoors or at home (Frith & 29
Mueller, 2003; Taylor et al., 2005; Taylor & Lee, 1994; Taylor & Stern, 1997). Based on this logic, in a higher education context Asian American and Asian students will be more likely portrayed in study- and research-related settings, such as laboratories, libraries and classrooms (setting), performing activities regarding study and research (activities), instead of being portrayed in social settings, such as outdoors and relaxing on campuses, engaging in social activities including parties, sports and entertainment.
In the marketing and advertising literature, cultural critics have defined ads as aesthetic objects and socio-political artifacts (Schroeder & Zwick, 2004). Visual representations in marketing practice both reflect and create social norms, identity and cultures (Lippke, 1995; Stern & Schroeder, 1994). Photographs in marketing campaigns do not normally represent reality but are artificially constructed. Advertising images are manipulations of visuals to entice viewers’ fantasy (Schroeder & Zwick, 2004). Thus, how higher education marketers will pursue a balance between the existing stereotypical
Asian images and the artificial marketing manipulations remains a question. In this regard, a series of research questions are introduced:
RQ5: Will Asian images tend to be in a low status as opposed to a high status in
college and university Web sites?
RQ5a: Will Asians’ gaze directions be more likely looking away from the
camera/others, or looking directly at the camera/others?
RQ5b: Will Asians be more likely bending or leaning their bodies, or standing
tall and upright?
30
RQ5c: Will Asians’ hands and arms be more likely at their side/at rest, or
raised/gesturing/waving?
RQ5d: Will Asians be more likely alone/appearing alone or interacting with
others?
RQ5e: Will Asians more likely appear serious/concerned or cheerful/confident?
RQ5f: Will Asians more likely appear in a study- and research-related setting
rather or in social settings?
RQ5g: Will Asians more likely be engaged in study- and research-related
activities or socializing?
Power position Besides the focused investigations on individual characteristics of
Asian images represented on college Web sites, a large number of studies are devoted to the interactions between Asian Americans/Asian students and other ethnic groups, especially the White majority (Diangelo, 2006; Frith & Mueller, 2003; Taylor et al., 1995;
Taylor & Stern, 1997; Tierney, 2006). Taylor, Laudreth and Bang (2005) analyzed magazine advertisements and did not find a single ad that showed Asian models exclusively. In reality, on a diverse campus, ethnic minority students often appear in a mixed-ethnic scenario, where various ethnic students study, talk, walk and live together.
Diangelo (2006) explicated the social production of Whiteness in college classrooms where White students enjoyed more learning opportunities, more power and an elevated position in a classroom that included Asian American and Asian students, 31 while Asian American and Asian students were rather passive and positioned as White students’ audiences. After studying the portrayals of Asians in advertisements, Frith and
Mueller (2003) found that Asian Americans were usually presented in a mixed-ethnic
group as a practice of tokenism. During the interactions with others, Asian Americans
tended to have a minor background role in the image composition (Taylor & Stern, 1997),
be silent (Mastro & Stern, 2003) and enjoy less social power. People “often find that
minority groups are given minimum concessions, that is, they are in the ads but they do
not hold much power” (Frith & Mueller, 2003, p. 120). After examining Hispanic,
African American and Asian American models in Time magazine advertisements,
Thomas et al. (2006) found that Asian models were shown frequently to play neutral
roles in a mixed-ethnic group.
Goffman (1979) studied gender interactions in advertisements by comparing
models’ “relative size,” “function ranking” and “ritualization of subordination.”
Specifically, models’ relative size, especially height, in a photograph reflects social power
positions. Differences in size correlate with differences in social situation. In terms of
function ranking, the model who enjoys higher social power will perform the executive
role, while the one who possesses lower social power will be portrayed as an action’s
receiver. Ritualization of subordination suggests that certain physical positions also
symbolize social power. For instance, lowering oneself physically and in a recumbent
position provides visual cues of defense and subordination; in contrast, elevating the
body and head is a stereotypical sign of superiority (Goffman, 1979). Thus,
H3: If presented along with others in college and university Web sites, Asians are
portrayed in a less powerful position in interactions with other ethnicities.
32
According to Frith and Mueller’s (2003) tokenism theory and Goffman’s (1979) analysis of social power cues in real-life situations, a series of hypotheses can be proposed regarding stereotypically representing Asians in a lower power position during interpersonal interaction with others.
H3a: If presented along with others in college and university Web sites, Asians
are more likely positioned in background roles rather than the visual focus in a
photograph.
H3b: If presented along with others in college and university Web sites, Asians
are portrayed relatively smaller in size than others.
H3c: If presented along with others in college and university Web sites, Asians
are portrayed more often as action receivers than in executive roles.
H3d: If presented along with others in college and university Web sites, Asians
are portrayed more often in a subordinate position than others.
Gender differences Studies of stereotypes in the U.S. media, particularly motion pictures and television, have uncovered important gender differences in portraying
Asians (Chang, 1993; Fong, 2002; Lee, 1999; Marchetti, 1993; Paek & Shah, 2003). In contrast to Asian males, who are most often depicted as strangely asexual characters,
Asian females are often portrayed as extremely sexual in U.S. movies and television shows (Fong, 2002). Asian women’s sexy images, being petite, exotic and eager to serve men, can be seen in Sayonara (1957), The World of Suzie Wong (1960), Tai-Pan (1986), an episode from Wiseguy (1987–1990), M. Butterfly (1988), Miss Saigon (1990), Xiu 33
Xiu (1999), Last Samurai (2003), Memoirs of a Geisha (2005) and Miami Vice (2006).
Kim (1986) concluded these sexual stereotypes were a creation of media fantasy for
White males at the expense of the Asian males. In the 1990s and 2000s, Asian women’s images improved as they are taking a wider variety of roles on the screen (Fong, 2002).
Asian American females appear in major roles, in affluent settings and as favorable roles
(Paek & Shah, 2003). However, their stereotypical sexual power and attractiveness to
White males is deeply ingrained in Americans’ perceptions and can still frequently be seen in the U.S. media (Fong, 2002; Kim, 1986; Paek & Shah, 2003; Tierney, 2006).
Jackson, Lewandowski, Ingram and Hodge (1997) reported that Americans tended to think of men instead of women when asked to imagine stereotypes in general; they considered Asian women not much different from themselves.
On the contrary, Asian males’ roles in U.S. (but not overseas Asian) motion pictures and television shows are limited and stereotypically nerdy, incompetent and asexual (Fong, 2002). Sixteen Candles (1984), The Ballad of Little Jo (1993), Lieutenant
Sulu in the Star Trek series (1966–1969), The Last Samurai (2003) and Bulletproof
Monk (2003) are some examples of the stereotypes in the U.S. popular culture. Based on the assumption that the distinct portrayals of Asian women and men in the U.S. motion pictures and television programs have an impact on Americans’ perceptions of Asians
(Fong, 2002), the images of male Asian students and female Asian students depicted on college and university Web sites might vary as well. Thus, gender should be introduced into the investigation of Asian images on college and university Web sites as an important variable.
RQ6: Will the portrayals of Asian males and females on college and university
Web sites vary in terms of their status?
34
RQ7: Will the portrayals of Asian males and females on college and university
Web sites vary in terms of their power positions?
Research questions and hypotheses
In sum, based on the previous studies, this study raises four sets of research questions (RQs) and hypotheses (H’s) regarding the portrayals of Asians on college and university Web sites from the dimensions of proportionality, Status portrayed and power position, controlled for gender. Hypotheses are statements of the relations between variables, often “based on the best [prediction] that can be derived from more general assumptions and prior evidence” from the related literature (Stempel, Weaver & Wilhoit,
2003, p. 96). Research questions are asked if prior evidence is lacking or conflicting.
1. Proportionality:
RQ1: Will the proportion of Asian images on a college or university’s Web site
exceed the proportion of Asian American and Asian students in that institution’s
student body?
RQ2: Will the proportion of Asian images on college and university Web sites in
West Coast states differ from that of colleges in East Coast states?
RQ3: Do public and private colleges and universities differ in the proportions of
Asian images used on their Web sites?
RQ4: Do undergraduate instructional, masters instructional and
doctoral/research instructional colleges and universities differ in proportion of
Asian images presented on their Web sites?
H1: There is a direct relation between the proportion of Asians’ images on college
and university Web sites and changes in Asian Americans’ buying power in those
states. 35
H2: The proportion of Asian images on the Web sites of lower-ranking colleges
and universities is more accurate than that of higher-ranking colleges and
universities in matching the reported proportion of Asians in student bodies.
2. Status portrayed
RQ5: Will Asian images tend to be in a low status as opposed to a high status in
college and university Web sites?
RQ5a: Will Asians’ gaze directions be more likely looking away from the
camera/others, or looking directly at the camera/others?
RQ5b: Will Asians be more likely bending or leaning their bodies, or standing
tall and upright?
RQ5c: Will Asians’ hands and arms be more likely at their side/at rest, or
raised/gesturing/waving?
RQ5d: Will Asians be more likely alone/appearing alone or interacting with
others?
RQ5e: Will Asians more likely appear serious/concerned or cheerful/confident?
RQ5f: Will Asians more likely appear in a study- and research-related setting
rather or in social settings?
RQ5g: Will Asians more likely engage in study- and research-related activities or
socializing?
3. Power position portrayed
H3: If presented along with others in college and university Web sites, Asians are
portrayed in a less powerful position in interactions with other ethnicities.
H3a: If presented along with others in college and university Web sites, Asians
are more likely positioned in background roles rather than the visual focus in a
photograph. 36
H3b: If presented along with others in college and university Web sites, Asians
are portrayed relatively smaller in size than others.
H3c: If presented along with others in college and university Web sites, Asians
are portrayed more often as action receivers than in executive roles.
H3d: If presented along with others in college and university Web sites, Asians
are portrayed more often in a subordinate position than others.
4. Gender differences
RQ6: Will the portrayals of Asian males and females on college and university
Web sites vary in terms of their status?
RQ7: Will the portrayals of Asian males and females on college and university
Web sites vary in terms of their power positions? 37
Chapter 3
METHOD
Content analysis was conducted to examine the visual representations of Asians
on the U.S. college and university Web sites. Riffe, Lacy and Fico (2005) defined
quantitative content analysis as the “systematic assignment of communication content to
categories according to rules, and the analysis of the relationships involving those
categories using statistical methods” (p. 18). This research method has been widely used
in media studies for decades and has become the most basic way of discovering media’s
meaning (Bell, 2001). Downing and Husband (2005) even regarded content analysis as
the standard method of textual analysis among social scientists in media studies.
Applying a content analysis approach to investigate the portrayals of Asians is based on a
number of considerations.
Content analysis allows researchers to efficiently reduce large amounts of
information and maintain the efficacy of the data (Riffe et al., 2005). Since the Carnegie
Classification lists more than 4,000 higher education institutions in the United States
(CFAT, 2006), a quantitative content analysis is better than other research methods for systematically examining thousands of photographs on hundreds of Web sites.
Additionally, the process by which higher education institutions admit minorities involves heated, controversial debates (Kane, 2003; Schmidt, 2003). Content analysis is a “nonobtrusive, nonreactive, measurement technique” (Riffe et al., p. 30), which may avoid potential difficulties in working with higher education admissions officials. Indeed, content analysis has been successfully used in examining media images of minority groups (Bowen & Schmid, 1997; Frith et al., 2004; Hardin, Lynn, Walsdorf & Hardin, 38
2002; Mastro & Stern, 2003; Moriarty & Popovich, 1991; Taylor & Lee, 1994; Thomas et al., 2006; Verser & Wicks, 2006; Wu, 1996).
Sample
To obtain a representative sample for U.S. college and university Web sites, the first step was to identify the sampling frame. As related studies have suggested
(McMillan, 2000; Riffe et al., 2005; Weare & Lin, 2000), instead of using the indices provided by online search engines such as Yahoo! and Google, this study adopted the U.S.
Department of Education’s institution listing and classification, which contains an updated list of accredited postsecondary educational institutions and programs across the United States (USDE, n.d.).
This study employed a purposive sampling strategy by choosing all four-year- and-above, accredited colleges and universities from four geographically and demographically representative states plus eight Ivy League universities. The nature of this study determined the use of a purposive sample of U.S. colleges and universities.
First, the portrayals of Asians are assumed to relate to the distribution of Asian
American and Asian students across the states. However, the geographic distribution of
Asian populations is rather uneven. More than half of all Asian populations live in
California, New York and Hawaii; 49% of Asians live in the West, while only 12% live in
the U.S. Midwest (Barnes & Bennett, 2000). California also receives more international
students from Asian countries than any other state (IIE, n.d.). Furthermore, purposive samples are extremely useful in some cases when particular samples are of great significance for the study (Greer & Mensing, 2004; Riffe et al., 2005; Stempel et al.,
2003; Vogt, 2005). For instance, the state higher education system of California, as well 39 as some elite universities, such as Ivy League universities, attracts many Asian American and Asian students.
This study purposively selected four U.S. states varying in Asian population and geographic location (Barnes & Bennett, 2002). Specifically, as shown in Table 1, four states were chosen using the U.S. census data: California, the continental U.S. state with the largest Asian population (4.2 million, 12.3% of its total); Maine, the state with the smallest Asian population (12,000, .9%); Michigan, the state with the median Asian population in the northern U.S. mainland (208,000, 2.1%); and Florida, the state with the median Asian population in the South (333,013, 2.1%). The Asian American buying power of these states was projected to reach $180 billion in California, $ 13 billion in
Florida, $10 billion in Michigan and $.3 billion in Maine by 2009 (Humphreys, 2005).
The four states additionally represented the East Coast (Maine, New England; Florida,
Southeast), West Coast (California) and inland states (Michigan) (USDE, n.d.).
Table 1 The Asian American population, 2000, Asian American buying power, 2004 and higher education institutions in California, Florida, Michigan and Maine, 2006
California Florida Michigan Maine Asian alone or Number 4,155,685 333,013 208,329 11,827 in combination Percentage of 12.3 2.1 2.1 .9 population total population Buying power 2004 128,585,618 8,940,502 6,804,231 212,378 (thousands of 2009, projected 180,071,414 13,476,778 10,225,335 289,476 dollars) Growth from 40.0% 50.7% 50.3% 36.3% 2004 to 2009 Number of Public 33 15 15 8 institutions Private 86 56 32 12 Total 119 71 47 20 Sources: Barnes & Bennett, 2002; Humphreys, 2005; USDE, n.d.
From each of the four states, all four-year-or-above institutions accredited by
agencies recognized by the U.S. Secretary of Education were included in this study. 40
According to the U.S. Department of Education’s institution listing and classification, 119 public and private higher education institutions in California, 20 in Maine, 47 in
Michigan and 71 in Florida were chosen (USDE, n.d.).
For the purpose of comparing the selected colleges and universities with elite universities, the eight Ivy League universities, Brown University, Columbia University,
Cornell University, Dartmouth College, Harvard University, Princeton University,
University of Pennsylvania and Yale University (Berry, n.d.), were also included in this study.
Unit of analysis
The unit of analysis refers to the persons, words, images or things being studied
(Stempel et al., 2003; Vogt, 2005). To investigate the portrayals of Asians on college and university Web sites, the unit of analysis in this study was the Asian models photographed on each institution’s homepage and admissions homepage.
Asian population and Asian models
Asian population Asians represent an extremely diverse pan-ethnic group, and the definition is not consistent (Fong, 2002). The U.S. Census Bureau employs a self-report method and defines Asian Americans in a broad sense. In 2000, the term “Asian” refers to people having origins in any of the original peoples of the Far East, Southeast Asian or the Indian subcontinent; however, the 1970 census classified Indians as White and the
Vietnamese population as “other” ethnicity (Barnes & Bennett, 2002). The U.S. immigration and Naturalization Service additionally considers people from Southwest
Asian countries, including Iran, Israel and Turkey, as Asian Americans (Fong, 2002).
Moreover, the U.S. Census in 2000 regarded Asians as “people who identified entirely or 41 partially as Asian” (Barnes & Bennett, 2002, p. 3), which further complicates the definition of Asians.
To estimate the proportions of Asian students in student bodies, this study used the U.S. Department of Education’s enrollment statistics of every college and university, which defined Asians in the same way as the U.S. Census 2000 did and included 30 ethnic combinations of Asian (Institute of Education Sciences [IES], n.d., see Appendix
A). This decision was based on several considerations.
The U.S. colleges and universities vary in their means of collecting and presenting ethnic information. One of the common methods is students’ voluntary self report, according to Eddith Dashiell, assistant provost for multicultural graduate affairs at Ohio
University (E. Dashiell, 2007, personal communication, June 7, 2007). Since students’ self report is not always required, the accuracy of Asian American populations varies across campuses.
Furthermore, a preliminary search discovered that colleges and universities differed in classifying Asians. For instance, University of Southern California categorizes ethnicities as Asian/Pacific Islander, African American, Hispanic, Native American,
White, international students and unknown (University of Southern California [USC], n.d.). In contrast, University of Miami does not consider international students as an individual ethnic category, classifying ethnicities as Asian/Pacific Islander, African
American (non-Hispanic), Hispanic, Native American, White (non-Hispanic) and unknown (University of Miami [UM], 2006). In Ohio University, the Asian population includes all faculty and students who identify themselves as Asian, without separating among countries (E. Dashiell, 2007, personal communication, June 7, 2007).
Consequently, the different classifications of ethnicities, especially the ethnic student 42 from foreign countries, may lead to an inconsistent parameter for proportionality comparisons.
The researcher also attempted to contact each higher institution in the sample through phone and e-mail for ethnic enrollment information. Only about 15% of colleges and universities offered complete Asian American and Asian student enrollment data.
The remaining colleges and universities either did not response to the inquiries or the information requested was unavailable.
Therefore, due to the inconsistency in data collection and parameter definitions, this study adopted the U.S. Department of Education’s enrollment statistics. One of the advantages of using the U.S. Department of Education’s statistical standard is that it defines Asian as a person “who has origins in any of the original peoples of the Far East,
Southeast Asia, or the Indian subcontinent” (IES, n.d., ¶. 4), which matches the definition of Asians used in U.S. census. Because prior studies commonly used the U.S. census data in proportionality comparisons (Lee & Joo, 2005; Taylor et al., 2005; Taylor
& Lee, 1994; Taylor & Stern, 1997), using the U.S. Department of Education’s enrollment
statistics was not only consistent with the proportionality research tradition, but also offered a consistent population parameter in comparing two proportions—the proportion of portrayals of Asians and the proportion of Asian population on campus.
Asian models To compare images with the Asian population on a given campus, this study coded Asian models presented on college and university Web sites. Scholars have found that coding for ethnicities including Asians is methodologically problematic because ethnicity is “a cultural and political construct, not a discretely definable biological entity,” and the visual coding procedure is highly subjective (Sabo, Jansen,
Tate, Duncan & Leggett, 1996, p. 10). 43
A search of previous proportionality studies discovered that Asian Americans were usually defined as “persons whose ancestry is rooted in any Asian country other than those on the Indian subcontinent, those countries that Americans refer to as the
Middle East (e.g., Saudi Arabia) or those that are former members of the Soviet Union.
This definition includes people from Cambodia, China, Japan, Korea, Vietnam, Laos, the
Philippines, Singapore, Taiwan, Thailand, and Hong Kong” (Taylor & Lee, 1994, p. 241).
Taylor and Stern (1997) studied Asian American stereotypes on television advertising
using the definition of persons whose ancestry is rooted in any of the countries including
Cambodia, China, Japan, Korea, Vietnam, Laos, the Philippines, Taiwan, Thailand,
Malaysia and Hong Kong. This narrower classification is based on Americans’ general
perception of Asians, since the public may have different stereotypes of people from the
Southwest, the Middle East and the Indian subcontinent (Lee & Joo, 2005; Taylor et al.,
2005; Taylor & Lee, 1994; Taylor & Stern, 1997).
Instead of offering a clear definition of Asians, other prior analyses of Asian
images only reported satisfactory intercoder agreements on identifying Asians in the
coding process (Paek & Shah, 2003; Rodgers, Kenix & Thorson, 2007; Taylor et al., 1995;
Thomas et al., 2006). However, when coding ethnic visuals in televised sport programs,
Sabo et al. (1996) found the ethnicity was basically indeterminate by using the U.S.
census definitions of African American, Asian, Caucasian and Hispanic. Thus, the
narrow definition of Asians, based on people’s perception of Asians, is more reliable than
the broad definition of Asians, based on geographic boundaries, for the purpose of
coding visuals.
Because the nature of this study was to examine the proportionality and
stereotypes of Asians, the narrowed academic definition of Asians was used in coding 44
Asian images, being consistent with the research tradition.7 In other words, Asian
images include the appearance of people from Cambodia, China, Japan, Korea, Vietnam,
Laos, the Philippines, Malaysia, Indonesia, Singapore, Taiwan, Thailand and Hong Kong.
Models with the appearance of people from the Southwest, the Middle East and the
Indian subcontinent were classified as undecided.
Finally, the numbers of other ethnic models, including African American,
Hispanic and White models, were coded for comparisons.
Homepages
As the first page that Web viewers will see when entering a site, a homepage, or front page, becomes a virtual portal for the Web users (Hawkins & Clinedinst, 2006; Lee,
2001). Many empirical studies on online media and online advertising have paid particular attention to the homepage because it is the first and primary presence of a site
(Cassidy, 2005; Dumont & Frindte, 2005; Greer, 2004; Lambiase, 2003; Pashupati &
Lee, 2003; Potter, 2002; Tremayne, 2004). A pretest on colleges and universities in
Maine and Ivy League universities discovered that every institute had its own site; in addition to the homepage, every college and university had created an exclusive subsidiary site for its admissions, which usually had a hyperlink on the institution’s homepage labeled as “admissions,” “prospective students,” “attending …” or
“applying … .” Given a clear target and designated functions, the admissions homepage was assumed to be as important as the institution’s homepage. Accordingly, each
7 The tradition of proportionality research often uses the narrowed classification of Asians in coding visuals, but uses the broad definition in collecting population data (Lee & Joo, 2005; Taylor et al., 2005; Taylor & Lee, 1994; Taylor & Stern, 1997). Such a double-standard method may exaggerate the differences between the level of representation in a certain population and the percentage in image portrayals. Since this study followed the proportionality research tradition, the results of this study should be used in caution. 45 institution’s homepage and its admissions homepage were both studied in the analysis of
Asian images presented to the prospective students.
Photographs and slide shows
This study concentrated on Asian models in photographs excluding graphic illustrations, video or animated visuals. Photography is the most widely used and the most powerful imagery tool of representation (Goffman, 1979; Schroeder, 2000; van
Leeuwen & Jewitt, 2001). It is a central way of representing identity (Bourdieu, 1990;
Lester, 2006; Sontag, 1977) and can offer viewers a realistic feel for campus life (Jones,
2006; “Use of the Web,” 1998).
The photographs comprised still pictures and photo slides appearing on the homepages in this study. Still pictures are defined as imagery files displayed in
JPEG/JPG (Joint Photographic Experts Group), GIF (Graphics Interchange Format) and
PNG (Portable Network Graphics) formats since they are the three file formats currently used for displaying photographs in a Web browser (Bennett, 2004; Campbell, 2005;
Kovarik, 2002).
Even though video and animated visuals were not included in this study, the pretest found that many institutions’ Web sites employed Flash to present photograph slides. Flash refers to a multimedia-authoring program to produce interactive, animated
content for the Web (Bennett, 2004; Nielsen & Loranger, 2006), such as photograph
slide shows. Unlike video and animated visuals, still photographs and most Flash
photograph slide shows are similar in their presentations because Flash photo slides
serve as a self-playing showcase. Once viewers log onto a site offering Flash photograph
slide shows, they will see the moving photo slides in the same way they will see a still
image. However, video and animated visuals usually require viewers’ interactions, such 46 as clicking on a button to play a video clip. One of the concerns of analyzing online content is that interactions between Web content and viewers enable the audience to retrieve different content from the same site, which challenges the underlying assumptions of the traditional content analysis method (Gunter, 2003; Neuendorf,
2002). For instance, a viewer who refuses to watch a video on the Web site may perceive the site differently from those who have watched the video. Therefore, this analysis focused on mainly still photographs and Flash photograph slide shows.
Procedure
The coding involved three steps. The first step was to locate each college’s or
university’s homepage address and admissions homepage address; the second was to
download still photographs and Flash photograph slide shows; and the third was to
collect information about Asian images.
In the first step, the study used Google’s search engine (www.google.com) to locate the sampled college and university homepages since the U.S. Department of
Education’s institution listing and classification does not provide institutions’ Web sites.
The Google search engine is one of the most popular information retrieval systems on the Internet and has been frequently used in academic research (Cassidy, 2005; Singer,
2005). This study used each higher education institution’s full name plus the key word
“homepage” when performing a search at Google. For instance, the study searched
Google for “University of Florida + homepage” to locate the University of Florida’s homepage at www.ufl.edu. Then, the study followed the link offered by Google to log onto the institution’s homepage.
To locate the admissions homepage, the procedure was to look for “prospective students,” “admissions,” “apply…” or relative links that offered various admissions 47 information and further hyperlinks. For instance, on the University of Florida homepage there was a link named “admissions,” through which visitors could find the University of
Florida admissions homepage, www.ufl.edu/admissions.
In the second step, this study looked for any photograph with human models in
JEPG/JPG, GIF or PNG format and it was downloaded to a computer hard drive. To
identify the format of an image and then to save it, the researcher only needed to move
the mouse cursor over the image and use the right click of the mouse to find the property
of the image and then to choose the option of “save the file as” to download it. As
previous research and the pretest suggested, online images might change when the Web
page is refreshed (Gerstenfeld, Grant & Chiang, 2003). To ensure intercoder reliability
and the research’s validity, this study downloaded all the photographs by reloading the
Web pages until no more distinct photographs from previous views were found.
To download Flash photograph slide shows, screen snapshots were captured for
each slide and saved to the computer’s hard drive individually. To capture a screen
snapshot, the researcher could press the “PrtSrn” key on the keyboard on a PC, or used
the Grab function listed under the “Finder” menu on a Macintosh computer.
In the third step, this study counted the number of recognizable Asian models, as
well as the total number of human models in the photographs downloaded from every
Web page. A photo without Asians was not further analyzed. Variables defining
stereotypical schemas for each Asian model were recorded according to the coding sheet
(see Appendix B).
48
Variables
Status
Adapted from the previous studies and measurements (Bonoma & Felder, 1977;
Goffman, 1979; Mehrabian, 1972, 1981), the attributes coded to measure the status of
Asian images included gaze, posture, hands/arms, interaction, expression, setting and activity. One point was assigned to each attribute when the Asian image matched the schemas in the “high status” category; three points were given to any schema in the “low status” exhibited in Table 2; two points were given to inapplicable situations. For instance, if an Asian model was portrayed looking directly at the camera (see Appendix
C1), then the coder recorded “1” for this model’s gaze attribute; if this model’s hands were at rest (see Appendix C1), then the coder recorded “3” for this model’s hands/arms attribute; and if the coder could not tell the model’s expression (see Appendix C2), a “2” was recorded for the expression attribute (see Appendix C2).
Table 2 Image attributes coding criteria for Asian images’ status portrayed
Attribute High status Low status Gaze Looking directly at camera or Looking away from camera or others others Posture Standing tall and upright Bent knee, bowed, leaning body Hands/arms Gesturing, waving or rising high At side or at rest Interaction Interacting with others Alone or appearing alone Expression Cheerful, confident Serious or concerned Setting Social settings Study- and research-related Activity Socializing Study- and research-related
The researcher calculated the average of those attributes’ scores and used it as the status score for each model. The higher the status score, the more passive the model was
portrayed.
49
Power position
O’Barr (1994) suggested analyzing power positions in an ad by looking at which model was portrayed stronger, bigger or having more control over the whole image. Four sub-dimensions further defined a model’s power position in this study: visual position, relative size, function rank and subordination. A three-point scale measured each of the domains (see Table 3). For instance, when an Asian model was positioned as the visual focus in a photo (see Appendix C3), the value for visual position was coded “1;” when the
Asian model was positioned as a background role (see Appendix C2), the value for visual position was “3;” and when the Asian model shared an equal position with others, the value for visual position was “2”. The average of visual position, relative size, function rank and subordination was calculated as the score for power position. The higher the power position score, the less power and less control the model was assigned in the interaction with others.
Table 3 Image attributes coding criteria for Asian images’ power position portrayed
Attribute High power position Low power position Visual position Visual focus in photo Background role Relative size Relatively big Relatively small Function rank Executive role Submissive role, action receiver Subordination Physically elevated head/body Physically lower body
Other variables
This study collected additional information regarding Asian images on college and university Web sites. These items included types of institutions (public or private;
baccalaureate, masters or doctoral/research), the institutions’ ranks, the enrollment of
Asian American and Asian students in the institution, the total student enrollment, inclusion or exclusion of diversity in mission statement of the institution, homepage or 50 admissions page, number of photos with human models, number of models, number of
Asian models in each photo, number of other ethnic models in each photo and gender of
Asian models.
Intercoder reliability
Procedure
Three coders were trained to conduct the intercoder reliability test: a female
Caucasian graduate student, 25, the researcher’s research assistant; a female African
American undergraduate student, 52, a non-traditional student who received extra credit
for her participation; and an Asian male, 30, the researcher. They were diverse in gender,
ethnicity and age. The researcher randomly selected 40 out of 256 colleges and
universities, which was approximately 16% of the sample. Mass communication scholars
have suggested that the Internet was challenging for content analysts because its easy-to-
update and interactive features caused difficulty in ensuring Web coders to be exposed to
identical content (McMillan, 2000; Stempel & Stewart, 2000; Weare & Lin, 2000). To
solve this problem caused by the Internet’s features and to reduce coding errors, the
researcher downloaded all the visual contents, 67 human photos, from the selected 40
college and university homepages and admission pages to a computer’s hard drive. After
a debriefing and training session, each of the three coders received a CD with those 67
photos and performed coding on their own. They each recorded information about those
67 photos following the coding instructions. In addition, they also collected the factual
information about the 40 colleges and universities, such as student enrollment, from
their Web sites and other designated resources.
51
Results
The intercoder reliability test used Simple Percent Agreement (SPA) and Scott’s
Pi (Pi) tests to examine coders’ agreements on categorical variables as suggested by Riffe et al. (2005). Both tests proved the measurements and coding instruments to be valid and reliable because the overall agreements by both methods exceeded the desired .80
(Riffe et al., 2005).
Specifically, using the SPA method, the overall agreement among three coders was .884. Observed in pairs (Table 4), the Asian male and Caucasian female reached the highest agreement, .926, while the agreement between the Caucasian female and the
African American female was the lowest, .85. Of all the categorical variables, the agreements ranged from 1 to .80.
Table 4 The overall coder pair agreements calculated by Simple Percent Agreement and Scott’s Pi methods (in parentheses)
Caucasian female African American female Asian male .926 (.915) * .876 (.84) * Caucasian female - .85 (.826) * African American female - - * indicates the agreement exceeded the desired .80 and was acceptable.
Using the Pi test, the overall agreement among three coders was .86. Observed in pairs (Table 4), the Asian male and Caucasian female reached the highest agreement, .915, and the agreement between the Caucasian female and the African
American female was the lowest, .826. Of all the categorical variables, the agreements ranged from 1 to .79.
In addition to assessing the coding instruments, the intercoder reliability test also showed that people of varying genders, ethnicities and ages could mostly recognize 52
Asians and African Americans only by their appearances (Table 5). The average agreements on the number of Asian models were .933 (SPA) and .91 (Pi), followed by the
number of African Americans8, .84 (SPA) and .80 (Pi). However, coders had difficulty
differentiating Hispanic and White models only by their appearances, which led the
agreements on the number of Hispanics to drop to .367 (SPA) and .194 (Pi), and the
agreements on the number of Whites to drop to .556 (SPA) and .525 (Pi).
Table 5 The average agreements on the numbers of ethnic images, tested by Simple Percent Agreement, Scott’s Pi and Pearson’s Correlation
Simple Percent Scott’s Pi Pearson’s Agreement Correlation Number of Asians .933* .91* .988 Number of African Americans .84* .80* .993 Number of Hispanics .367 .194 .781 Number of Whites .556 .525 .998 Number of Undecided .333 .256 .689 * indicates the agreement exceeded the desired .80 and was acceptable.
Coders did not successfully recognize Hispanic models because Hispanic models’ facial appearances provided inadequate visual cues so that coders tended to confuse them with White models. Given the focus of this study, the researcher decided to concentrate on Asians and combine the categories of Hispanics and Whites as one, namely White and others, in the coding process.
Table 5 also showed the agreement on the number of undecided did not exceed the critical value .80. Coders’ confusions in identifying models from South Asia and the
Indian subcontinent reflected the coding problems raised by Sabo et al. (1996) that
8 Due to the difficulty in distinguishing African Americans from international students and scholars from African countries, this study used “African Americans” referring to both for convenience. 53 ethnicity was visually unclear if the coding categories were based on the U.S. census definitions.
After the intercoder reliability test, the researcher (author) coded all the photographs sampled. 54
Chapter 4
RESULTS
This chapter presents the results of the content analysis in two sections. The first section reports the overall description of the sample, followed by the second section that investigates the research questions and hypotheses.
This study sampled 265 U.S. colleges and universities, including 257 four-year- and-above accredited institutions (from California, Florida, Michigan and Maine) and eight Ivy League universities. As shown in Table 6, private colleges and universities (194,
73.2%) dominated the sample, and only 71 (26.8%) public higher education institutions were sampled.
According to the Carnegie Classification of Institutions of Higher Education
(CFAT, 2006), 54 (20.4%) institutions were Baccalaureate Colleges; 84 (31.7%) were
Masters Colleges and Universities; 50 (18.9%) were Doctoral/Research Universities; and 77 (29.1%) colleges and universities fell in other categories, such as School of art, music and design and other separate health profession schools. The Web sites of 116
(43.8%) colleges and universities published their mission statements with an emphasis on diversity; 131 (49.4%) colleges and universities did not note diversity in their online mission statements; and only 18 (6.8%) colleges and universities did not publish a mission statement online. 55
Table 6 Numbers of four-year-and-above, public and private colleges and universities by Carnegie’s classification from California, Florida, Michigan and Maine and Ivy League universities in the sample, 2006
Frequency Percentage Baccalaureate Masters Doctoral Others Total California Public 1 20 10 2 33 Private 19 24 14 29 86 20 44 24 31 119 44.9 Florida Public 1 4 6 4 15 Private 14 10 3 29 56 15 14 9 33 71 26.8 Michigan Public 0 8 7 0 15 Private 10 8 1 13 32 10 16 8 13 47 17.7 Maine Public 4 3 1 0 8 Private 5 7 0 0 12 9 10 1 0 20 7.5 Ivy League Public 0 0 0 0 0 Private 0 0 8 0 8 0 0 8 0 8 3.0 Total Public 6 35 24 6 71 Private 48 49 26 71 194 54 84 50 77 265 99.9* * indicates that due to rounding the total is not 100%.
According to the U.S. News & World Report’s America’s best colleges’ rankings
(2007), less than a quarter of the sampled colleges and universities, including 43 national universities (16.2%) and 15 liberal arts colleges (5.7%), were named among the top universities and best colleges in the nation compared to the remaining 207 unranked universities and colleges (78.1%) in the sample, as shown in Table 7.
The average enrollment of the sampled colleges and universities was 7,318.2 (SD
= 10,710.39); Miami Dade College (Miami, Florida) had the largest enrollment of 54,169 56 students, and California Christian College (Fresno, California) the smallest enrollment of
35. Asian American students on average accounted for 9.05% of the student body (SD =
12.27).
Table 7 Top national universities and best liberal arts colleges by state (ranked by U.S. News & World Report) and the number of unranked schools in the sample
Frequency Total % Calif. Fla. Mich. Maine Ivy League Top national universities Top schools 15 3 2 0 8 28 10.6 Tier 3 schools 2 2 3 1 0 8 3.0 Tier 4 schools 1 4 2 0 0 7 2.6 Total 18 9 7 1 8 43 16.2 Best liberal arts colleges 8 1 3 3 0 15 5.7 Unranked 93 61 37 16 0 207 78.1 Total 119 71 47 20 8 265
Every higher education institution in the sample maintained a Web site that included a homepage and an admissions homepage. Visuals, particularly human photographs, were widely used on the sampled college and university Web sites. Table 8 showed this content analysis collected 3,644 photos with a total of 8,319 human models from the sampled college and university homepages and admissions homepages. By their appearances, 378 (4.54%) models were identified as Asians. On average, each institution’s homepage and admissions homepage contained 31.19 models, 1.43 of who were Asian models (SD = 3.38). Although the number of White models was not available
due to the lack of intercoder agreements, the images of the nation’s non-ethnic majority
continued to dominate the college and university Web sites. Recall that Hispanics and
Whites were grouped as White and others in the coding process.
57
Table 8 Frequencies of Asian models, total models and human photos in the sample and means on each higher education institution’s Web site by state
Asian models Total models Total human photos f M SD f M SD f M SD California 270 2.27 4.75 4,017 33.76 48.26 1,803 15.15 19.67 Florida 45 .63 1.09 1,702 23.97 24.46 735 10.35 8.76 Michigan 41 .87 1.21 1,893 40.28 43.85 791 16.83 17.85 Maine 6 .30 .66 537 26.85 22.73 251 12.55 12.51 Ivy League 16 2.00 1.41 170 21.25 10.31 64 8 5.66 Total 378 1.43 3.38 8,319 31.39 40.13 3,644 13.75 16.36
Among the sampled 378 Asian models, genders were fairly evenly represented with 179 (47.2%) male models and 200 (52.8%) females. More than half of the Asian images (230, 60.7%) appeared on the sampled college and university homepages and the rest (149, 39.3%) appeared on their admissions homepages. About two thirds (250,
66.0%) of Asian models were portrayed in a mixed-ethnic group rather than being alone.
This study used SPSS 14.0 (Statistical Package for Social Sciences) to perform
statistical tests. Before the data analyses, a series of explore tests was run to detect
missing data and outliers. Cases with missing data were not included in the analyses. For
outliers, this study substituted the extreme values with their corresponding means plus or minus two standard deviations.
Proportionality
Under- or over-representation
RQ1 asked whether the proportion of Asian images on a college or university’s
Web site would exceed the overall Asian Americans and Asian students’ proportion of that college or university’s student body.
A paired-sample t-test, comparing the proportion of Asian images on every college site and the proportion of Asian American students on every campus, revealed 58 that Asian images was significantly under-represented compared to the actual enrollments of Asian American students (t = 4.84, d.f. = 241, p < .001). The average
Asian population was 9.05% of the total enrollment on the U.S. campuses, but the proportion of Asian images on the Web sites was merely 5.14%.
To take ethnic enrollments into consideration, this study computed the variances between the proportions of ethnic students’ enrollments and the proportions of ethnic models on Web pages as a new variable to reflect higher education institutions’ misrepresenting ethnicities (ME) on their Web sites. For example, the mean of the variances between the percentages of Asian students’ enrollments and Asian models
(MEAsian) was -3.16 (SD = 9.46), which suggested Asians were under-represented
compared to Asian students’ enrollments.
To explore the factors leading to the use of Asian images on a higher education
institution’s Web pages, a linear regression analysis was employed and found that the
total number of human photos presented on an institutions’ site and the institution’s
rank were two significant determinants, R2 = .285, adjusted R2 = .279, F (2, 262) =
52.114, p < .001. Specifically, a higher education institution would use more Asian images when it had an intention to use a greater number of human photographs on its
Web site and/or when it had a higher rank according to the U.S. News & World Report’s
America’s best colleges’ rankings (2007). In other words, if an institution did not have the desire to exhibit many human photos or it was not one of the top universities or best colleges, the use of Asian images would be limited.
Note that the rank was a categorical variable with 1 referring to top universities and 5 referring to colleges or universities with no ranks. A regression model was suggested to predict the use of Asian images below: 59
Predicted number of Asian images = .054 total number of photos - .162 rank +
1.171
Thus, the overall Asian proportion in a college or university’s student body, measured by the broad definition of “Asian,” exceeded the proportion of Asian images, measured by the narrow definition of “Asian,” on that institution’s Web site. Asians were significantly under-represented as compared to their enrollments (disregarding the statistical error caused by two definitions of Asians). Colleges and universities choose
Asian images not necessarily because of Asian American and Asian student presence on campus but for other reasons, such as the institutions’ academic rank.
West Coast vs. East Coast
RQ2 asked whether the proportion of Asian images on college and university
Web sites in West Coast states differ from that in East Coast states.
Except for Michigan, the sampled states were either on the West Coast, namely
California, or on the East Coast, namely Maine and Florida. To compare the colleges and universities from California and those from Maine and Florida, a t-test was employed to find that the proportion of Asian images on the West Coast college and university Web sites was greater than that of the East Coast colleges. In West Coast states 6.06% of models were Asians, larger than 3.61% in East Coast states, t = 2.974, d.f. = 216, p = .003.
Moreover, the two coasts also differed in their misrepresenting Asians (MEAsian).
In the West Coast state, shown in Figure 1, because of the large proportion of Asian
populations on campuses (MWest = 12.48%, MEast = 3.22%, t = 11.777, d.f. = 179.2, p
< .001), Asian images were under-represented by 7.12%, which was significantly greater than being over-represented by .031% in East Coast states, t = 5.637, d.f. = 170.9, p
< .001. 60
14% 12.48% proportion of Asian 12% images proportion of Asian 10% population 8% 6.06% 6% 3.61% 4% 3.22%
2%
0% West Coast East Coast
Figure 1: The proportion of Asian images compared to the Asian population’s proportion in student bodies on the West and East coasts
These findings suggested that even though West Coast colleges and universities studied presented more Asians than their counterparts on the East Coast, the representation in the West was still disproportionate to Asians’ percentages on those campuses.
Public vs. private
RQ3 asked whether public and private colleges and universities differ in the proportions of Asian images used on their Web sites.
A t-test showed that the frequencies of portraying Asians in public and private institutions did not differ significantly. In public schools’ Web sites, 4.17% of the models
were Asians, while 4.71% of the models in private institutions’ sites were Asians. In
Figure 2, the proportion of Asian images for public institutions was fairly comparable to
that for private institutions despite the fact that public institutions presented more 61 models (M = 40.06, SD = 58.63) than did private institutions (M = 28.32, SD = 30.36), t
= 2.12, d.f. = 262, p = .035.
Additionally, public and private institutions are also comparable in terms of misrepresenting Asians. Given their Asian populations on campus, public (-4.73%)
schools do not differ from private (-2.57%) schools for misrepresenting Asians (MEAsian) on their Web pages.
10% proportion of Asian images 9% 8.90% proportion of population 8% 7.28% 7% 6% 4.71% 5% 4.17% 4% 3% 2% 1% 0% public institutions private institutions
Figure 2: The proportion of Asian images compared to the Asian population’s proportion in student bodies in public and private higher education institutions
As a result, no significant differences were found between public and private colleges and universities regarding the proportion of Asian images and the level of misrepresenting Asians on their Web sites.
Undergraduate vs. graduate
RQ4 inquired whether undergraduate instructional, masters instructional and
doctoral/research instructional colleges and universities differ in the proportions of
Asian images presented on their Web sites. 62
ANOVA’s results showed that doctoral/research universities presented significantly fewer Asian images than baccalaureate colleges and masters colleges and universities, F (3, 261) = 3.649, p = .013 (see Figure 3).
14% proportion of Asian images 11.96% 12% proportion of population
10%
8% 5.84% 6.45% 6% 4.91% 3.62% 4% 3.19% 2%
0% doctoral masters baccalaureate
Figure 3: The proportion of Asian images compared to the Asian population’s proportion in student bodies in doctoral/research, masters and baccalaureate institutions
Although Asians were commonly under-represented on all college and university
Web sites, the disproportionate portrayals of Asians on doctoral/research universities’ sites were most substantial. The average of misrepresenting Asians in doctoral/research
universities was -6.63%, much worse than baccalaureate colleges’ -1.29% (p = .003) and worse than masters college and university -2.86% (p = .021). Yet, baccalaureate colleges did not differ from masters’ institutions significantly in their uses of Asian images.
63
Buying power
H1 predicted a direct relation between the proportion of Asians’ images on college and university Web sites and changes in a state’s Asian Americans’ buying power.
The answer to RQ1 noted that overall Asians were under-represented on college and university Web sites as compared to their enrollments (disregarding the statistical error caused by two definitions of Asians). When comparing the proportions of Asian
images (PAI) among the sampled four states, the study found that California’s colleges
and universities used a significantly larger number of Asian images on their Web sites
than Michigan, Maine and Florida, F (3, 253) = 10.145, p < .001, while the other three
states did not differ significantly.
Ironically, although California used more Asian images than any other states in
the sample, given its relatively large Asian population (AP), this state’s colleges and
universities significantly under-represented Asians on their Web sites, F (3, 250) =
18.747, p < .001 (see Table 9).
Table 9 Comparisons on the representations of Asians, Asians’ buying power (BP), populations (AP) and numbers of higher education institutions (HE) in California, Florida, Michigan and Maine
California Florida Michigan Maine PAI (%) Mean 5.81 3.08 2.90 1.19 SD 5.94 5.52 4.36 2.52 MEAsian Mean -6.82 .98 .24 -.53 SD 10.68 6.13 4.36 3.28 BP 2004, thousands of dollars 128,585,618 8,940,502 6,8940,502 212,378 BP 2009, thousands of dollars 180,071,414 13,476,778 10,225,335 289,476 BP growth, 2004–2009 (%) 40.0 50.7 50.3 36.3 AP 4,155,685 333,013 208,329 11,827 AP Percentage (%) 12.3 2.1 2.1 .9 NH 221 111 69 20
64
Based on the literature, states’ varying use of Asian images was potentially a result of a state’s Asians’ buying power (BP), buying power growth (BP Growth), Asian population (AP) and Asian population’s proportion (APP), as well as the number of higher education institutions (HE) in that state. Pearson’s correlation tests indicated that all those variables were significantly correlated in various degrees; however, none of the variables appeared to be a crucial determinant to the proportions of Asian images (PAI) or the misrepresenting Asians (MEAsian) because their paired correlations to Asian image
proportion or the misrepresenting Asians did not exceed .80, a widely accepted
threshold in testing Pearson’s correlation, seen in Table 10.
Table 10 Paired correlations between a state’s proportion of Asian images (PAI)/misrepresenting Asians (MEAsian) and its buying power (BP), Asian population (AP) and numbers of higher education institutions (HE)
PAI MEAsian BP, 2004 BP, 2009 BP Growth AP APP BP, 2004 .36 .49 BP, 2009 .36 .45 1.0 BP Growth .24 .21 .69 .69 AP .36 .45 1.0 1.0 .69 APP .36 .47 1.0 1.0 .69 .99 HE .34 .51 .95 .95 .48 .96 .96 Note: Correlations are significant at the .01 level.
To further identify the factors leading colleges and universities to use Asian images differently across states, linear regression tests were employed. Only the percentage of Asian population in a state was found to be the predictor of the uses of
Asian images on colleges Web sites, R2 = .133, adjusted R2 = .129, F (1, 214) = 32.752, p
< .001. The regression model for predicting the Asian image proportion across states was:
Predicated Asian image proportion = .361 Asian population proportion + .811 65
The actual effect size was R2 = .129, meaning that approximately 12.9% of the variances of the Asian images proportions in a state can be explained by the Asian population’s proportion in that state. Therefore, if a state has a larger proportion of
Asians, colleges and universities of that state will reflect more Asian images on their Web sites. Other variables, such as Asian Americans’ buying power, are not closely associated
with uses of Asian images. However, the Asian population’s proportion only predicts
12.9% of the variances; a large portion of the variance is affected by some unknown
causes.
On the other hand, results found a state’s Asian population impacted the degree
2 2 of misrepresenting Asians (MEAsian), R = .273, adjusted R = .268, F (1, 146) = 54.828, p
< .001. The regression model for predicting the misrepresenting Asians across states
was:
Predicated misrepresenting Asians = -1.46E-006 Asian population - .536
The actual effect size was R2 = .268, meaning that approximately 26.8% of the variance of the over-representing or under-representing Asians in a state can be explained by the state’s Asian population. Specifically, if a state has a larger Asian population, colleges and universities within that state will under-represent Asians to a greater degree on their Web sites. Therefore, according to the narrow definition of
Asians, since Asian Americans’ buying power was not a significant factor to predict the degree of misrepresenting Asians, H1 was not supported.
Low ranking vs. high ranking
H2 predicted the proportion of Asian images on the Web sites of lower-ranking
colleges and universities would be more accurate than that of higher-ranking colleges
and universities in matching the proportion of Asians in student bodies. 66
According to the U.S. News & World Report’s America’s best colleges’ rankings
(2007), 265 colleges and universities in the sample were classified into five groups (see
Table 7). ANOVA analysis found colleges and universities of various rankings differ in
using Asian images, F (4, 260) = 4.872, p = .001. In particular, the sampled 28 top universities9 and 15 best liberal arts colleges employed significantly more Asian images than those 207 unranked colleges and universities. Every top university presented approximately two Asian images on average (M = 1.94, SD = .389) and every best liberal arts college used 2.63 Asian models (SD = .665), whereas colleges and universities with no ranks normally presented only one Asian model.
Additionally, considering the enrollments of Asian American and Asian students, the study also found the degree of misrepresenting Asians varied between high-ranking institutions and low-ranking institutions. ANOVA showed that Asian images were significantly under-represented in the top universities as compared to the Tier Three
(Mean difference = -8.7, p = .008), Tier Four (Mean difference = -6.64, p = .05), the best colleges (Mean difference = -5.74, p < .03) and colleges and universities without rankings (Mean difference = -8.05, p < .001), F (4, 237) = 6.15, p < .001.
As a result, H2 was supported that the proportion of Asian images on the Web sites of lower-ranking colleges and universities would be more accurate than that of higher-ranking colleges and universities in matching the proportion of Asians in student bodies.
Status portrayed
RQ5 asked whether Asians tended to be portrayed in a low status as opposed to a
high status on college and university Web sites. This study examined Asian models’
9 Eight Ivy League universities were included in the top universities category according to the U.S. News & World Report’s America’ best colleges’ rankings (2007). 67 gazes, postures, hands and arms, interactions, expressions, settings and activities to
assess their status. Table 11 exhibits the frequencies of Asian images appearing in a high
status and low status based on the seven attributes. Accordingly, before answering RQ5,
a series of seven secondary research questions regarding seven Status attributes should be addressed first.
Table 11 Frequencies for Asian images’ status attributes in the sampled college and university Web sites
Status Frequency Gaze* Look directly at Cannot tell Look away from camera or others camera or others 228 6 143 χ2 = 199.676, d.f. = 2, p < .001
Posture Standing tall and Neutral Knee bent, bowed, leaning body upright 105 130 142 χ2 = 5.671, d.f. = 2, p = .059
Hands/arms* Gesturing hand Neutral At rest, fold at side 47 157 173 χ2 = 74.886, d.f. = 2, p < .001
Interaction* Interact with others Neutral Alone or appearing alone 76 145 156 χ2 = 29.926, d.f. = 2, p < .001
Expression* Cheerful, confident Cannot tell Concerned, serious 272 49 56 χ2 = 255.793, d.f. = 2, p < .001
Setting* Social settings Cannot tell Study and research settings 177 99 101 χ2 = 31.469, d.f. = 2, p < .001
Activities Social activities Cannot tell Study and research related 132 135 110 χ2 = 2.966, d.f. = 2, p = .227 * indicates the association is significant at .05 level.
68
Gaze
RQ5a asked whether Asians would be more likely to look away from the camera or others or look directly at the camera or others once they appeared on the Web sites.
Chi-square analysis revealed that Asian models were more likely to look directly at the camera or other models rather than looking away, χ2 = 199.676, d.f. = 2, p < .001.
To further investigate models’ gaze directions controlling for whether they appeared alone or in a mixed ethnic group, Table 12 shows that when Asian models appeared alone, they were more likely to look directly at the camera (72.09%). If Asians appeared in a group, they were more likely to look directly at others when others were also Asians (69.23%); their gaze directions did not differ significantly when they were with other ethnic models.
Table 12 Frequencies and percentages of Asian models’ gaze directions by their accompanying ethnic group
Look directly at Cannot tell Look away from Total camera or others camera or others Alone 93 (72.09%) 0 36 (27.91%) 129 With other Asians 27 (69.23%) 1 (2.56%) 11 (28.21%) 39 With other ethnics 108 (51.92%) 5 (2.40%) 95 (45.67%) 208 Total 228 6 142 χ2 = 16.718, d.f. = 4, p = .002
Thus, Asian models were more likely to look directly at the camera or others rather than looking away, especially when they were photographed alone. This finding
was inconsistent with Asians’ passive stereotypes discovered in previous studies
(Goffman, 1979). Interestingly, Asians models seemed more willing to look directly at
other Asians rather than having eye contact with people of other ethnicities.
69
Posture
RQ5b asked if Asians would be more likely portrayed bending or leaning their bodies than standing tall and upright. As shown in Table 11, the portrayals of active
(standing tall and upright), neutral and passive (knee bent, bowed or leaning body) postures seemed roughly balanced, suggested by Chi-square (χ2 = 5.671, d.f. = 2, p
= .059).
As a result, Asian models’ postures are neutrally portrayed in general. However, if
the analysis took gender into consideration, female Asians appeared more likely in a
passive posture rather than an active posture. Findings related to gender differences are
discussed in details in a later section.
Hands/arms
RQ5c asked whether Asian models’ hands and arms were more likely at side/at
rest or gesturing/waving on college and university Web sites. Table 11 showed that 173
out of 377 (45.89%) Asian models were portrayed with their hands and arms at rest,
followed by 41.65% of them being portrayed neutral (not showing their hands or arms).
Only a few Asian models (12.47%) were seen gesturing, waving or raising their hands and arms high, χ2 = 74.886, d.f. = 2, p < .001.
Thus, the answer to this question is that Asian models are portrayed more likely to rest their hands and arms than actively gesture or wave their hands and arms. Asian images are seldom represented actively for this attribute.
Interaction
RQ5d was a question about whether Asian models were more likely to be alone or appearing alone rather than interacting with others. Results in Table 11 indicated that 70 the majority of Asian models sampled were or appeared to be alone (41.38%) and were neutral, keeping a distance from others (38.46%). Merely 20.16% of Asian images appeared to be interacting with others, χ2 = 29.926, d.f. = 2, p < .001. Although frequently being presented in a mixed-ethnic group with other models, Asians still more likely appeared alone or kept a distance from others rather than closely interacting with the models they are together with, χ2 = 274.75, d.f. = 3, p < 001.
Because 66.0% of Asian models in the sample appeared in a mixed-ethnic group and 34.0% were portrayed alone, to explore the interactions of Asians in a mixed-ethnic group, Table 13 analyzed their interactions controlled for accompanying models. A Chi- square revealed that when appearing with other models, more than half of the Asian models kept a neutral distance from others; Asians would be more likely to interact with other Asians (43.59%) than other ethnic models (28.37%). However, when with other ethnic models than Asians, sometimes Asian models were portrayed to be passive and alone in a group (13.94%).
Table 13 Frequencies and percentage of Asian models’ interactions with others by accompanying groups
Interact with others Neutral Appearing alone Total With other Asians 17 (43.59%) 22 (56.41%) 0 39 With other ethnics 59 (28.37%) 120(57.69%) 29 (13.94%) 208 Total 76 142 29 χ2 = 7.921, d.f. = 2, p = .019.
Expression
RQ5e asked whether Asian models were more likely to appear serious or concerned rather than cheerful or confident. A Chi-square found that Asians on colleges
Web sites usually appeared cheerful and/or confident rather than serious or concerned, 71
χ2 = 255.80, d.f. = 2, p < 001. About three quarters of the Asian images looked cheerful or confident in the sample, comparing to 56 of them with concerned or serious expressions. This finding answered the research question that Asians were portrayed cheerful and confident for a purpose of marketing to prospective students.
Settings and activities
RQ5f and RQ5g were related as they both attempted to find out on what occasions Asians were presented on the photographs. RQ5f asked if Asian models were more likely to appear in a study- and/or research-related setting rather than in social settings. RQ5g asked whether Asians were more likely to perform study- and/or research-related activities than social activities.
A Chi-square discovered that Asians appeared more often at a social setting
(46.95%) than a study- and/or research-related setting (26.80%), χ2 = 31.469, d.f. = 2, p
< 001. Because this content analysis defined the social setting broadly as one indirectly related to studies or research including residence halls, gyms, cafeterias, outdoors and others, a closer examination on various social settings was performed. Results in Table
14 showed that Asian models appeared more frequently outdoors than in any other setting, χ2 = 384.51, d.f. = 9, p < .001. They were only captured once at the residence hall and cafeterias, but 116 times outdoors in the sampled 377 appearances.
Even though Asians appeared in a social setting, such as outdoors, they were not necessarily performing a social activity and vice versa. For instance, students can be
reading outdoors or socializing in classrooms. Consequently, an investigation of Asian
models’ activities would offer a clear answer to this question. Table 11 indicated that
despite the fact that in Asian models were seen performing study- and research-related 72 activities (132, 35.01%) more often than socialized activities (29.18%), such a distribution was statistically insignificant, χ2 = 2.966, d.f. = 2, p = .227.
As a result, Asian models are frequently presented in a social setting, especially outdoors. However, even often in a social setting, Asians do not engage in significantly more social activities than study- and research-related activities.
Table 14 Frequencies and percentage of study- and research-related settings and social settings in the sample
Frequency Percentage Study and research settings* 101 26.79% Classroom** 34 9.02% Library** 10 2.65% Labs** 37 9.81% Other study and research settings** 20 5.31%
Social settings* 177 46.95% Residence hall** 1 .27% Gym** 11 2.92% Cafeterias** 1 .27% Outdoors** 116 30.77% Other social settings** 48 12.73%
Unknown settings* 99 26.26%
Total 377 * χ2 = 31.469, d.f. = 2, p < 001 ** χ2 = 384.512, d.f. = 9, p < .001.
Summary
Collectively, Asian images tended to be neutral in terms of status based on the evaluations of their gazes, postures, hands/arms, interactions with others, expressions, settings and activities. By computing the average of each model’s status attributes, the study yielded a summated value for Status, with 1 representing high status and 3 representing low status. As Table 6 showed, the mean of Asian models’ status was 1.87 73
(SD = .376), suggesting that U. S. colleges and universities tended to portray a neutral
image when representing Asians on their Web sites. Thus, to answer RQ2, more Asian images tended to be portrayed as neutral, neither in a low status or a high status. This finding echoes previous study that Asian models tend to play neutral roles in a mixed- ethnic group (Thomas et al., 2006).
Power position portrayed
In addition to the discussion on an individual Asian model’s Status portrayed, the examination of power positions interprets the interactions between Asian minorities and other ethnic groups.
H3 predicted that Asian images were more likely portrayed in a less powerful position in relations with other ethnicities. This study defined the power positions from four sub-dimensions, comprising visual position, relative size, function rank and subornation. Table 15 illustrated the frequencies of Asian images’ power positions from four sub-dimensions in interaction with other ethnic models. Hence, H3 was essentially composed of four secondary hypotheses.
Visual position
H3a stated that when appearing along with others on college and university Web sites, Asians would be more likely positioned as a background role rather than the visual focus on photographs.
As shown in Table 15, most of the Asian models (68.83%) were portrayed visually equal to others, χ2 = 140.51, d.f. = 2, p < .001. Only 13.77% of the Asian models in the sample appeared in a background role and 17.41% appeared as a visual focus. Apparently,
H3a is not supported because Asian images are neither downplayed nor dominating the 74 photographs; however, Asian models’ neutral visual position is significant, which reflects
the previous studies that Asian models are playing neutral roles in a mixed-ethnic group
(Thomas et al., 2006).
Table 15 Frequencies for Asian images’ power positions in presence of other ethnic models in the sampled college and university Web sites
Power Position Frequency Visual position* Visual focus Cannot tell, neutral Background role 43 170 34 χ2 = 140.510, d.f. = 2, p < .001
Relative size* Relatively big Cannot tell, neutral Relatively small 43 122 82 χ2 = 37.903, d.f. = 2, p < .001
Function rank* Executive role Cannot tell, neutral Submissive role 44 162 41 χ2 = 115.684, d.f. = 2, p < .001
Subornation* Physically elevated Cannot tell, neutral Physically lower head and body body 21 154 72 χ2 = 109.368, d.f. = 2, p < .001 * indicates the association is significant at .05 level.
Relative size
H3b predicted that when appearing along with others on college and university
Web sites, Asian images would be portrayed relatively smaller in size than others.
Table 15 showed that approximately half of the Asian models (49.39%) in the
sample were portrayed equally as big as others; about one-third of the sampled Asian
images (33.20%) were relatively smaller than others. They were occasionally portrayed
relatively bigger than others, but not frequently (17.41%). A Chi-square suggested that
such a distribution was significant, χ2 = 37.903, d.f. = 2, p < .001. In other words, Asian 75 models are more likely portrayed equal to or relatively smaller than other models, but they are rarely seen bigger than others when appeared in a mixed-ethnic group. H3b is partially supported.
Function rank
H3c predicted that when presented along with others on college and university
Web sites, Asian models were more likely portrayed as action receivers than in executive roles.
Results in Table 15 showed that Asians were frequently portrayed neither as action receivers nor in executive roles, but neutral (65.59%), χ2 = 115.684, d.f. = 2, p
< .001. Unlike the stereotypes found in previous studies, Asian models do not possess less or more power than others in an interaction. Instead, Asian images tend to be neutral, consistent with this study’s previous findings and previous studies (Thomas et
al., 2006). Thus, H3c is not supported.
Subordination
H3d: If presented along with others in college and university Web sites, Asian images were more likely portrayed in a subordinate position than a dominating one.
Results in Table 15 exhibited that Asians were mostly portrayed neutrally
(62.35%), followed by physically lowering bodies (29.96%); they seldom appeared to be physically elevated (8.50%) though. A Chi-square suggests that Asian models are more frequently portrayed in a neutral or subordinate position than a dominating one, χ2 =
109.368, d.f. = 2, p < .001. Thus, H3d is partially supported.
76
Summary
To summarize the attributes of Asian models’ power position in the interactions
with other ethnic roles, a summated variable, power position, was calculated based on
Asian images’ visual positions, relative sizes, function ranks and subordination. By computing the average of each model’s power position, where 1 represented the most powerful position and 3 represented the least powerful position, results discovered that the mean of Asian models’ power position was 1.97 (SD = .392), suggesting that U. S.
colleges and universities portrayed Asians on their Web sites as a neutral role when they
were photographed with other models.
H3 predicted that when presented along with others, Asian models were
portrayed in a less powerful position than others, which was not supported. In fact,
Asian images seemed not too powerful or too submissive in the interaction with others
on college and university Web sites. Consistent with individual model’s status attributes,
Asian images are neutral.
Gender differences
To explore how genders differ in the portrayals of Asians, two research questions were posed.
Status of genders
RQ6 asked whether the portrayals of Asian males and females on college and
university Web sites would vary in terms of their status. In Table 16, Chi-squares showed
that Asian models’ genders were significantly associated with their postures and interactions.
Literature in gender advertisement studies suggested women were frequently portrayed in a passive, submissive posture (Goffman, 1979). By controlling Asian models’ 77 genders in the analysis, this study reached a consistent result that female Asian models were more likely to be bending their knees or leaning their bodies (43.72%) than standing tall and upright (24.12%), seen in Table 16.
When comparing male and female Asian models’ interactions, this study found that male Asians most likely were or appeared alone in the photos (48.88%); while female Asians were portrayed most likely to be in a neutral position, keeping a distance from others (40.20%). Although neither male nor female Asians closely interacted with others, males were portrayed even more passively and receding (14.61%) than female counterparts (25.23%).
Thus, male and female Asian models are portrayed differently in their posture and interaction attributes. Although results show Asian models on college and university
Web sites seem not to appear submissive in postures as suggested in previous studies of
stereotyping Asians, female Asian models still carry certain stereotypical female features,
such as bent knees and bowed bodies.
Additionally, in terms of interactions, female Asians are portrayed as relatively more active and approachable than males. This result is also consistent with previous
studies of sexual stereotypes that imbued Asian women with stereotypical sexual power
and attractiveness, while Asian males are often seen as nerdy, incompetent and
unattractive (Fong, 2002; Kim, 1986; Tierney, 2006). 78
Table 16 Frequencies of Asian images’ status attributes in the sampled sites by gender
Status Frequency Gaze Look directly at Can’t tell Look away from camera or camera or others others male 107 2 69 female 121 4 74 Total 228 6 143 χ2 = .533, d.f. = 2, p = .766
Posture* Standing tall Neutral Knee bent, leaning body male 57 66 55 female 48 64 87 Total 105 130 142 χ2 = 6.865, d.f. = 2, p = .032
Hands/arms Gesturing hand Neutral At rest, fold at side male 25 76 77 female 22 81 96 Total 47 157 173 χ2 = 1.272, d.f. = 2, p = .53
Interaction* Interact w/ others Neutral Alone or appearing alone male 26 65 87 female 50 80 69 Total 76 145 156 χ2 = 10.069, d.f. = 2, p = .007
Expression Cheerful, confident Can’t tell Concerned, serious male 118 28 32 female 154 21 24 Total 272 49 56 χ2 = 5.756, d.f. = 2, p = .056
Setting Social settings Can’t tell Study and research settings male 78 54 46 female 99 45 55 Total 177 99 101 χ2 = 2.951, d.f. = 2, p = .229
Activities Social activities Can’t tell Study and research related male 56 75 47 female 76 60 63 Total 132 135 110 χ2 = 5.873, d.f. = 2, p = .053 * indicates the association is significant at .05 level.
79
Gendered power positions
RQ7 asked whether the portrayals of Asian males and females vary in terms of their power positions. Table 17 shows that significant associations exist between Asian models’ genders and visual positions and between genders and function ranks.
Asian models in general were not frequently portrayed as the visual focus or
background roles in their visual positions. However, male and female Asian models
differed in their chances of being visual focus or background roles. Consistent with their
gender status as suggested by Fong (2002) and Jackson et al. (1997), male Asians unsurprisingly appear more likely in a background role (20.79%) than females (8.84%); meanwhile, female Asian (17.69) models tend to be more often the visual focus in a photograph more often than male Asians (16.83%). As a result, female Asian models are portrayed in a relatively higher power position than male Asian models when they appear in a mixed-ethnic group.
In contrast, the association between gender and function rank is fairly surprising because results show male Asian models are more likely to perform submissive roles than female Asian models when interacting with other ethnics, seen in Table 17. Even though Asian models are not usually portrayed as executive roles or submissive roles, genders differ significantly when they are playing those roles in college and university
Web sites. Table 17 showed that Asian females were more likely to be portrayed in an executive role than Asian males, χ2 = 7.542, d.f. = 2, p = .023. Female Asian models mostly were seen in a neutral role (71.92%) and most unlikely to be portrayed as a submissive role (11.64%). However, 23.76% of male Asian models were portrayed as action receivers, more often than being portrayed in executive roles (19.80%).
80
Table 17 Frequencies for Asian images’ power positions by gender in presence with other ethnic models in the sampled college and university Web sites
Power Position Frequency Visual position* Visual focus Cannot tell, neutral Background role male 17 63 21 female 26 107 13 Total 43 170 34 χ2 = 7.144, d.f. = 2, p = .028
Relative size Relatively big Cannot tell, neutral Relatively small male 20 47 34 female 23 75 48 Total 43 122 82 χ2 = .743, d.f. = 2, p = .690
Function rank* Executive role Cannot tell, neutral Submissive role male 20 57 24 female 24 105 17 Total 44 162 41 χ2 = 7.542, d.f. = 2, p = .023
Subornation Physically elevated Cannot tell, neutral Physically lower head and body body male 8 67 26 female 13 87 46 Total 21 154 72 χ2 = 1.310, d.f. = 2, p = .519 * indicates the association is significant at .05 level.
Thus, when comparing power positions according to gender, this study found that male Asian models were portrayed in a lower power position than their female counterparts. The power position between Asian males and females were portrayed in the opposite of that in the majority’s world, where males were stereotypically placed in a higher power position than females (Goffman, 1979).
Summary
Table 18 summarizes the answers to the research questions and the results of testing the hypotheses in this study. 81
Table 18
A summary of the answers to the research questions and results of hypothesis tests
Research questions and hypotheses Results Proportionality RQ1 Will the proportion of Asian images The overall Asian proportion in a college on a college or university’s Web site or university’s student body, measured by exceed the proportion of Asian the broad definition of “Asian,” exceeded American and Asian students in the proportion of Asian images, measured that institution’s student body? by the narrow definition of “Asian,” on that institution’s Web site. Asians were significantly under-represented as compared to their enrollments (disregarding the statistical error caused by two definitions of Asians).
RQ2 Will the proportion of Asian images The representation in the West was still on college and university Web sites disproportionate to Asians’ percentages in West Coast states differ from on those campuses. that of colleges in East Coast states?
RQ3 Do public and private colleges and No significant differences were found universities differ in the between public and private colleges and proportions of Asian images used universities regarding the proportion of on their Web sites? Asian images and the level of misrepresenting Asians on their Web sites
RQ4 Do undergraduate instructional, Although Asians were commonly under- masters instructional and represented on all college and university doctoral/research instructional Web sites, the disproportionate portrayals colleges and universities differ in of Asians on doctoral/research proportion of Asian images universities’ sites were most substantial. presented on their Web sites?
H1 There is a direct relation between Not supported. the proportion of Asians’ images on college and university Web sites and changes in Asian Americans’ buying power in those states. 82
Table 18 (continued)
Research questions and hypotheses Results Proportionality H2 The proportion of Asian images on Supported. the Web sites of lower-ranking colleges and universities is more accurate than that of higher- ranking colleges and universities in matching the proportion of Asians in student bodies.
Status portrayed RQ5 Will Asian images tend to be in a Asian images tended to be portrayed as low status as opposed to a high neutral, neither in a low status or a high status in college and university status. Web sites?
RQ5a Will Asians’ gaze directions be Asian models were more likely to look more likely looking away from the directly at the camera or others rather camera/others, or looking directly than looking away, especially when they at the camera/others? were photographed alone.
RQ5b Will Asians be more likely bending Asian models’ body postures were or leaning their bodies, or standing neutrally portrayed in general. tall and upright?
RQ5c Will Asians’ hands and arms be Asian models were portrayed more likely more likely at their side/at rest, or to rest their hands and arms than actively raised/gesturing/waving? gesture or wave their hands and arms.
RQ5d Will Asians be more likely The Asian models were or appeared to be alone/appearing alone or alone, and were also likely to be neutral, interacting with others? keeping a distance from others.
RQ5e Will Asians more likely appear Asians on colleges Web sites usually serious/concerned or appeared cheerful and/or confident rather cheerful/confident? than serious or concerned.
RQ5f Will Asians more likely appear in a Asian models were frequently presented study- and research-related setting in a social setting, especially outdoors. rather or in social settings?
RQ5g Will Asians more likely engage in Asians did not engage in significantly study- and research-related more social activities than study- and activities or socializing? research-related activities.
83
Table 18 (continued)
Research questions and hypotheses Results Power position portrayed H3 If presented along with others in Not supported. college and university Web sites, Asians are portrayed in a less powerful position in interactions with other ethnicities.
H3a If presented along with others in Not supported. college and university Web sites, Asians are more likely positioned in background roles rather than the visual focus in a photograph.
H3b If presented along with others in Partially supported. college and university Web sites, Asians are portrayed relatively smaller in size than others.
H3c If presented along with others in Not supported. college and university Web sites, Asians are portrayed more often as action receivers than in executive roles.
H3d If presented along with others in Partially supported. college and university Web sites, Asians are portrayed more often in a subordinate position than others.
Gender differences RQ6 Will the portrayals of Asian males Male and female Asian models were and females on college and portrayed differently in their posture and university Web sites vary in terms interaction attributes. Female Asian of their status? models still carried certain stereotypical female features, but were portrayed as relatively more active and approachable than Asian males.
RQ7 Will the portrayals of Asian males Male Asians appeared more likely in a and females on college and background role than females. university Web sites vary in terms of their power positions?
84
Other results
Along with Asian Americans, African Americans and Hispanics are the three largest ethnic minority groups in the United States (“National population estimates,”
2000; Taylor et al., 1995). Studies about the proportions of other ethnicities’ images on college and university Web can further distinguish the disproportionate portrayals of
Asians. Because of the lack of intercoder agreements on coding Hispanic and White models, this study only conducted comparisons between the portrayals of African
Americans and Asians.
Figure 4 shows that in contrast to Asian Americans and Asians, the African
American ethnic minority is proportionately represented.
14% proportion of images 12.03% 12% proportion of population 10.72% 10% 9.05% 8%
6% 5.14%
4%
2%
0% Asian African American
Figure 4: The proportions of Asian and African American images on college and university Web sites compared to the proportions of Asian and African American students in the student body
African Americans generally accounted for 10.72% (SD = 15.08) of the student body. By their appearances, 893 were identified as African Americans as shown in Table
19. On average, each institution’s homepage and admissions homepage contained 31.19 85 models, 3.37 of whom were African Americans (SD = 5.13), more than double the number of Asian models (M = 1.43, SD = 3.38). Compared to the proportion of Asian images shown in Figure 4, the proportion of African Americans’ images on college and university Web sites (12.03%) was rather consistent with their proportion in the student body (10.72%), t = -1.53, d.f. = 246, p = .13.
Table 19 Comparisons between the portrayals of Asians and African Americans regarding the frequencies of models and mean number of models for each institution by state
Frequency of models Asians African Americans f M SD f M SD California 270 2.27 4.75 378 3.18 4.51 Florida 45 .63 1.09 246 3.46 5.81 Michigan 41 .87 1.21 228 4.85 6.39 Maine 6 .30 .66 17 .85 1.53 Ivy League 16 2.00 1.41 24 3.00 1.31 Total 378 1.43 3.38 893 3.37 5.13
A linear regression analysis found that the predictors of the number of African
American models varied from those of Asian models. The proportions of African
Americans in the student body became the key factor, along with the number of photos,
in predicting the number of African American images, R2 = .416, adjusted R2 = .411, F (2,
244) = 86.941, p < .001. If a higher education institution aimed to employ more
photographs on its Web site and/or had a larger proportion of African Americans on
campus, the institution would be more likely to present more African American images.
A regression model was suggested to predict the use of African American images
below:
Predicted number of African American images = .122 total number of photos
+ .105 African Americans’ proportion in student body + .36 86
Table 20 shows that the number of photos used in college and university Web sites and the ranks of the institutions are two crucial predictors of the uses of Asian images. Unlike representing African Americans, colleges and universities seem to choose
Asian images not necessarily because of Asian American and Asian students’ presence on campus but based on, for example, institutions’ academic ranks.
Table 20 Comparisons between the portrayals of Asians and African Americans regarding proportionalities, predictors of the use of images and misrepresenting ethnicities by coast, by type of institution and by institutions’ rank
Asians African Americans Proportionality Under-represented* consistent
Predictors to uses of Total number of photos,* Total number of photos,* images rank* proportion in population*
West Coast less under-represented* Over-represented* East Coast Under-represented* Under-represented*
Public institutions Under-represented Over-represented** Private institutions Under-represented Under-represented**
Doctoral institutions Least under-represented* Over-represented Other institutions Under-represented* Over-represented
Top universities Less under-represented* Over-represented Unranked institutions Under-represented* Over-represented * indicates p ≤ .001. ** indicates p ≤ .05.
When taking student enrollment into consideration, Asians were under- represented. On the contrary, the mean of the ME for African Americans (MEAfrican American)
was 1.37 (SD = 10.59), which suggested African Americans were somewhat over-
represented compared to the actual enrollments of African American students (see Table
20). 87
When comparing the markets between the East Coast and West Coast, this study revealed that because of the significantly larger proportion of African American students on East Coast campuses (M = 11.031%, SD = 8.85) than on the West (M = 6.288%, SD =
5.56), t = 4.394, d.f. = 152.9, p < .001, and the comparable proportion of African
American images on both Coasts (MWest = 9.242%, MEast = 10.333%), t = .841, d.f. = 216, p = .401, the East Coast slightly under-represented African Americans (-1.44%), which set it apart from the West Coast, where African Americans were over-represented
(3.379%), specifically in California, t = -3.248, d.f. = 201, p = .001 . This finding is the opposite of the situation with Asians, who were largely under-presented in the West (see
Table 20).
This study found that public and private institutions did not differ in terms of under-representing Asians. Interestingly, however, public institutions as shown in Table
20 tend to over-represent African Americans (MEAfrican American = 3.71%) whereas private
institutions slightly under-represent African Americans on their Web pages (MEAfrican
American = -.18%), t = 2.48, d.f. = 244, p = .014.
Moreover, prestigious universities, including Ivy League universities, tended to
use fewer Asian images than other institutions, but did not differ from other colleges and universities in representing African Americans, F (4, 260) = 1.238, p = .295. Higher- ranking and lower-ranking colleges and universities seemingly treated African American images in the same fashion. No significant difference was found in their degrees of misrepresenting African Americans F (4, 242) = .616, p = .65. In contrast, ANOVA showed that Asian images were substantially under-represented in the top universities and Ivy League universities (see Table 20).
Additionally, as shown on Table 20, doctoral/research institutions were found to
use fewer Asian images, and Asians were less under-represented than in masters and 88 baccalaureate institutions. In the comparisons of African American images, the differences among doctoral/research universities, masters colleges and universities and baccalaureate colleges were not significant. 89
Chapter 5
DISCUSSION AND CONCLUSIONS
This study was a quantitative content analysis of 3,644 human photos on 265 college and university homepages and admissions homepages. The sampled higher education institutions comprised 257 four-year-and-above accredited colleges and universities from California, Florida, Michigan and Maine as well as eight Ivy League universities. The analysis identified 378 Asian models from a total of 8,319 human models.
Rationale
This study concentrated on the proportionality and stereotypical portrayals of
Asian Americans and Asians as an ethnic minority on U.S. college and university Web sites. By analyzing the quantity and quality of Asian images appearing on higher education institutions’ homepages and admissions homepages, this study explored the marketing and cultural impact of the use of visuals on the Internet.
Of many tools to market to prospective students, college and university Web sites become crucial because of the increasing use of the Internet in the college search. In addition to the ideal of equal opportunity, the movements against racial discrimination and the employment of affirmative action, the rapid growth of ethnic minority populations and economic power drives higher education marketers to reach out to and portray a diverse population. Reflected on college and university Web sites, an illusion of
“cultural diversity” to match that ideal seems to have been created by the over- representation of ethnic minorities (Alexander, 2007). Therefore, Web sites serve not only as a marketing tool but also a cultural artifact. 90
As an attempt to examine the practices of emerging higher education marketing and the evolving cultural influences, this study analyzed the visuals, specifically photographs of human models, on the Web. Empirical research exhibits the efficacy of photographs in attracting attention, delivering messages and influencing affects (Blair,
2000; Branthwaite, 2002; Stoner, 2004; Zillmann, Knobloch & Yu, 2001). Photographs on college and university sites enable prospective students to gain a general feel about the campus (Jones, 2006; “Use of the Web,” 1998).
Due to their growing populations, buying power and academic achievements,
Asian Americans are becoming a unique ethnic group targeted by U.S. colleges and universities. However, Asian Americans’ fame as a model minority might have led them to face a complex situation in higher education admissions because U.S. higher education’s ethnicity-conscious admissions policy may discriminate against rather than benefit Asian Americans (Fisher et al., 2000; Schmidt, 2003; Takagi, 1990).
Consequently, the portrayals of ethnic diversity, especially of Asian Americans, on U.S. campuses may represent the negotiation of marketing, educational, cultural, philosophical, legal and political concerns. Therefore, this study focused on college and university Web sites to investigate Asian portrayals’ marketing and cultural implications.
Theoretical framework
Research on visual consumption and schema theory provided this study with the theoretical framework.
The notion of visual consumption stresses the interactions between consuming and producing social identities (Schroeder, 2002). Consumers are aware of and actively pursue the associations between products and the way products are linked to group identities. Thus, product consumption becomes a consumption and representation of 91 imagery, desires and identity (Schroeder & Zwick, 2004). Photography is a central way of creating, managing and representing social identity (Bourdieu, 1990). Empirical evidence shows that including the image of a minority in an ad enhances the campaign’s marketing effects (Stevenson & Swayne, 1999).
Schema theory takes a cognitive approach in explaining how people make sense of an image and form an attitude toward the object portrayed in the image. Schemas serve as data structures for representing the knowledge stored in human memory
(Rumelhart, 1984; Taylor & Falcone, 1982) and for interacting with new knowledge
(Brewer & Nakamura, 1984). During the interactions between internal mental schemas and external information, a related framing effect occurs. Framing is conceptually similar to schemas in communication research (Entman, 1991). Schema theory and framing can connect studies of media content and perception and thus are widely used to examine media messages.
The rich body of empirical research literature on the portrayals of Asian
Americans presents two research traditions: proportionality and stereotypes. The proportionality approach compares the frequency of Asian Americans’ presence to their proportion in a certain population. It has its roots in racial ideology and hegemony—that under-representing an ethnic minority causes a perception that that minority group carries little weight in a society (Hirshman, 1993; Knobloch-Westerwick & Coates, 2006).
Thus, through the examination of proportionality of Asian images, this study shed light on Asian minorities’ social role in a higher educational context.
The stereotype approach manifests the stereotypical portrayals of Asian
Americans on the U.S. media over many decades. It also provides the content analysis in this research with visual schemas and cues to measure Asian images’ status and power positions portrayed on college and university Web sites. This study analyzed such visual 92 cues as gaze directions, body postures, hands/arms, interactions, settings and activities
to evaluate Asian models’ status; and analyzed Asian models’ visual position, relative
size, function rank and subordination in the presence of other ethnicities to assess their
power position portrayed in interaction to others.
Additionally, previous studies introduced gender differences in stereotyping
Asian Americans (Chang, 1993; Fong, 2000; Jackson et al., 1997; Kim, 1986; Lee, 1999;
Marchetti, 1993; Paek & Shah, 2003; Tierney, 2006). Thus, the analysis was controlled
for gender.
Under-represented Asians
Results showed that Asian American and Asian students were significantly
under-represented on the Web compared to their proportion in the student body
(disregarding the statistical error caused by two definitions of Asians). The number of
human photos and an institution’s rank were found to correlate with the use of Asian
images on the institution’s Web site. Asians were more likely to be overlooked if a college
or university presents fewer human photos. In other words, when an institution was
going to present human models on the Web, the priority would be given to non-ethnic
Whites or other ethnic groups instead of Asians. Asian images would be seen only when
an institution presented a large number of human photos. According to the cultural and
social implications of the proportionality research suggested by Hirshman (1993) and
Knobloch-Westerwick and Coates (2006), Asian Americans and Asians are still of less
ideological, political and social importance compared to the non-ethnic majority and
other ethnic groups. This finding echoes previous proportionality studies of advertising
in the U.S. media (Bowen & Schmid, 1997; Frith et al., 2004; Knobloch-Westerwick &
Coates, 2006; Thomas et al., 2006). 93
Web sites, among other uses, are a marketing tool for colleges and universities to recruit prospective students. Although literature suggested population shifts (Barnes &
Bennett, 2002; Harris, 1999) and economic factors (Pietilainen, 2006) had a positive impact on the media’s representation of ethnicities, the size of the Asian American population and Asian Americans’ buying power were found not to significantly correlate with the frequency of their Web presence. Results of this study showed the size of the
Asian American population negatively correlated with the degree of misrepresenting
Asians. The growth of the Asian American population increased both the use of Asian images and the enrollment of Asian students in colleges and universities. However, the increase of Asian enrollments was much greater than the increase of the use of Asian images; thus, the degree of under-representing Asians on the Web grew apace. One can use California as an example. It “houses” the largest Asian American population
(4,155,685, 12.3% of its total population) among U.S. mainland states, and its colleges and universities exhibit the greatest proportion of Asian images (5.94%)—yet, California
Asians are noticeably under-represented (-6.82%) compared to their rather monumental proportion in the student body.
Results also showed that the market’s force was overpowered by external factors.
The use of Asian images was limited if the institution held a low academic rank.
Comparisons between high-ranking and low-ranking colleges and universities revealed that institutions of lower ranks had smaller Asian enrollments, F (4, 260) = 3.194, p
= .014, and tended to present fewer human photos on their Web pages, F (4, 260) =
33.15, p < .001. Therefore they were less likely to use Asian images.
However, since lower-ranking institutions had relatively smaller Asian enrollments, the representation of Asians on their Web sites tended to be more accurate than that of higher-ranking institutions’ Web sites in matching the proportion of Asian 94 students in the study body. Compared to enrollments, Asian images were significantly under-represented in the top universities, including Ivy League universities, compared to
Tier Three schools, Tier Four schools, the best colleges and unranked colleges and universities.
Furthermore, doctoral/research universities presented significantly fewer Asian images than baccalaureate colleges and masters colleges and universities. Even though
Asians were commonly under-represented across institutions, the disproportionate portrayals were the most substantial on doctoral/research universities’ Web pages.
Thus, there seems a correlation between Asian American and Asian students’ enrollment and the degree of under-representing Asians. High-ranking colleges and universities, top universities, Ivy League universities and doctoral/research universities, with a larger proportion of Asian students than other colleges and universities, tend to under-represent Asians. Of the three different means of categorizing institutions (high- ranking, Ivy League, top and doctoral/research universities) all prestigious schools studied in this sample appear to devote their efforts to recruiting other minority students
rather than Asians, as the literature suggested (Dong, 1995; Schmidt, 2003, Takagi,
1990). Asian Americans, as a unique ethnic group, are reportedly facing serious
discrimination in admissions (Fisher et al., 2000; Takagi, 1990). This discrimination, as
an external factor, might well explain the “unrealistic” portrayals of Asians on those
prestigious college and university Web sites.
African Americans and Asians
To further understand the disproportionate portrayals of Asians on college and
university Web sites, this study contrasted the representation of African Americans with
that of Asians. Results found that in contrast to under-represented Asians, African 95
Americans were proportionately represented on college and university Web sites. The reported proportion of African Americans in the student body positively correlated with the frequency of the portrayals of African Americans. When taking student enrollment into consideration, African Americans were somewhat over-represented on the Web sites,
whereas Asians were under-represented.
This study also found that public institutions tended to over-represent African
Americans, but private institutions tended to under-represent African Americans.
Conversely, Asians were found to be equally under-represented in public and private institutions. Interestingly, the distinctive under-representation of Asians in prestigious universities, including Ivy League universities, did not occur for African Americans. No significant difference was found between prestigious universities and other institutions in terms of misrepresenting African Americans.
As Doug Cox, university Webmaster and director of new media communications at California State University, Long Beach, pointed out, to represent the student population proportionately, ethnic diversity was one of the top criteria for universities to choose photographs for their Web pages (D. Cox, 2007, personal communication, April
20, 2007). The U.S. Supreme Court’s landmark ruling in 2003 and affirmative action directives lead colleges and universities to be ethnic cautious in admissions and marketing to students. Reflected on college and university Web pages, however, African
Americans are seemingly overshadowing other ethnicities in playing a central role in symbolizing diversity. This study found the representation of African Americans almost perfectly matched the proportion of African Americans in the student body across different types and ranks of institutions. On the contrary, the representation of Asians was disproportionate compared to the enrollment of Asians and different in various types and ranks of institutions. These findings were consistent with previous studies that 96 suggested African Americans were over-represented in the U.S. media (Knobloch-
Westerwick & Coates, 2006; Zinkhan, Qualls & Biswas, 1990). African Americans are the primary racial minority in the United States (Thomas et al., 2006). If marketers use a simplified version of diversity, the idea of diversity may tend to be equated solely with
the presence of African Americans.
Neutral Asians
The findings indicated that stereotypes about Asian Americans were fading in the
higher education context. Instead of being portrayed as passive, submissive and devoted
to work (Paek & Shah, 2003; Taylor et al., 1995; Taylor & Stern, 1997), Asian Americans
appeared neutral in terms of their status and power positions. For example, Asian models’ body postures tended to be neutral (status/posture); they kept a neutral distance with others when presented together with other models (status/interaction); and their activities were not always study- and/or research-related (status/activities).
When interacting with others, Asian models were neither the visual focus nor the
background role, but natural (power position/visual position); they were more likely portrayed equal to or relatively smaller than others (power position/relative size); they
were not dominant or dominated by others in an ethnic-mixed group (power
position/function rank); and most frequently, they tended to be in a neutral or
subordinate position (power position/subordination).
Overall, Asian images were likely portrayed neutrally, neither in a low status nor
a high status, and often played a neutral role when photographed with others in this
study. This finding supported recent advertising research that Asian models play neutral roles in a mixed-ethnic group (Thomas et al., 2006). 97
In addition, portrayals of Asian Americans were much improved in some attributes. Sometimes, Asian models were even portrayed as active and of high status.
Results showed that Asian models were frequently seen looking directly at the camera or others (status/gaze); they appeared cheerful and confident in photos
(status/expression); and they were often seen in social settings, in particular outdoors
(status/settings). Part of the reason for the favorable changes is due to the marketing purpose. Marketing and advertising campaigns are usually a distorted mirror to social reality. Visual representations in marketing practice both reflect and create social norms, identity and cultures and are aimed to stimulate viewers’ fantasies (Lippke, 1995;
Schroeder & Zwick, 2004; Stern & Schroeder, 1994). Therefore, Asian models on college and university Web sites may be chosen on purpose to create and exemplify an improved, active and confident image.
Many colleges and universities proactively photograph ethnic minorities on campus to represent diversity10 (D. Cox, 2007, personal communication, April 20, 2007).
For instance, among 83 Asian models photographed alone (34.02%), approximately 70% of them were portrayed looking directly at the camera; a great number of models were presented outdoors, which might be a result of taking advantage of natural light for photography. These photographs might be staged portrayals; only a survey of photographers and designers could determine whether some of the Asian models’ active status and power position were manipulated.
Although Asian images on college and university Web sites are improving, a few stereotypical characteristics from prior research still existed in this study. Asian models’ hands and arms were frequently portrayed at rest, rather than actively gesturing or
10 The researcher contacted every Webmaster of the sampled colleges and universities in California, Michigan and Maine via e-mail, inquiring into the criteria for choosing photos for college and university Web sites. Thirty-seven colleges and universities responded with valuable and informative remarks. 98 waving (status/hands and arms). Asians seemed to be portrayed as a bit shy and isolated in interaction with other ethnic models. Asian models tended to interact more with people of the same ethnicity rather than other ethnic models; whereas, when with other ethnic models, Asians were portrayed passive and alone in the group. They also had direct eye contact with other Asians more often than other ethnic models. Although they were more often portrayed equal to others in terms of visual size, many times they were seen relatively smaller than others. They were also portrayed to be physically lowering their bodies and being subordinate when interacting with others.
Nevertheless, the overall portrayals of Asians are improving as Asian Americans are more often shown playing a neutral role. This finding is seemingly paradoxical compared to the disproportionate representation of Asians. As research suggests
(Hirshman, 1993; Knobloch-Westerwick & Coates, 2006), the under-representation of
Asians leads to a perception that Asians, as an ethnic group and prospective students, do not merit so much attention from the education recruiters, compared to other ethnic minorities. However, the improving portrayals of Asians can serve as part of the marketing strategies to positively influence prospective students’ choices in higher education, according to visual consumption theory (Schroeder, 1998, 2000, 2002).
Images of an ethnic minority probably mirror marketers’ utilitarian strategies and social norms and ideologies. The complex portrayals of Asian Americans likely result from negotiation and balancing of various concerns. With the changing of markets and society,
Asian images transform accordingly.
Female Asians
Male and female Asian models were evenly represented in the study. However, genders differed significantly in representing stereotypes of Asians. In the examination 99 of status, results show female Asian models tend to be portrayed in a passive, submissive
body posture, which is consistent with Goffman’s (1979) study about gender advertising.
Although Asian models seemed not to appear submissive overall as suggested in previous studies (Taylor & Stern, 1997), female Asian models still retain certain stereotypical female features, such as bent knees, bowed and leaning bodies.
Besides being portrayed in a passive body posture, Asian females surprisingly appeared more active in interacting with others and more often to be the visual focus than Asian males; in contrast, Asian males were more likely than Asian females to be portrayed appearing alone, submissive, as a background role and as an action receiver.
Such a seemingly reversed gender stereotype is actually consistent with previous
research (Fong, 2002, Kim, 1986; Paek & Shah, 2003; Tierney, 2006). Jackson et al.
(1997) reported that Americans tended to think of men in stead of women when asked to
imagine stereotypes in general. In other words, the stereotypes of Asians that Americans
may have are mostly about Asian males and accordingly represented through male Asian models in the media portrayals. Americans usually consider Asian women not much different from White women (Jackson et al., 1997).
Paek and Shah (2003) posited a contemporary gender stereotype that Asian females appear in major roles, affluent settings and as well-educated model minorities.
Studies about Asian American gender images often suggest that Asian females possess stereotypical sexual power and attractiveness to White males; in contrast, Asian males appear nerdy, incompetent, unattractive and asexual (Fong, 2002; Oren, 2005). Paek and Shah (2003) gave the example of an Asian American female teen looking at the camera when an Asian American male teen was seen sitting at his laptop computer.
According to Paek and Shah, who studied magazine advertising portrayals, the image of 100 exotic beauty and attractiveness was a common theme in representing Asian American females.
Social norms and ideology influence gender images, whereas the influences on images that combine gender and race are even more complex. For example, Asian females can be seen as an exotic creation for White male at the expense of Asian males
(Kim, 1986). A topic for future effects research could focus on whether the gender-ethnic hierarchy reinforces the non-ethnic majority’s dominant role, while enhancing the racial ideology and cultural hegemony in people’s perception.
Future studies
A few limitations of this study suggest future studies are needed to explicate portrayals of Asians. The proportionality research tradition has often used a broad definition of Asians in estimating the proportion of population and a narrow definition of
Asians in coding Asian images portrayed in media. Although both self-report population data and subjective coding process are based on people’s perceptions of Asians, the complex definitions may exaggerate the statistical errors in comparing those two proportions. Thus, a more accurate and comparable measurement is needed to define
Asian images and Asian populations in future studies. The results in this study and prior research should be used with an awareness of the measurement disparity.
Although this analysis provided a few predictions about the use of Asian images on college and university Web sites, many other factors drive the decisions on photo choices for Web sites. A survey or in-depth interview with college and university admissions officials may yield valuable insights in answering the research questions. For instance, the researcher contacted every Webmaster of the sampled colleges and universities in California, Michigan and Maine via e-mail, inquiring into the criteria for 101 choosing photos for college and university Web sites. Thirty-seven colleges and universities responded with invaluable and informative remarks. Future studies can systematically interview professionals and officials and textual-analyze their feedback.
Then, marketers and researchers will have a better understanding of the causes and consequences of the representation of an ethnic minority on Web sites.
College search and college marketing involve both verbal and visual information.
Individuals may search the college and university in different ways. For instance, studies show that people of different personality traits consume visual and verbal information differently (Sojka & Giese, 2001, 2006). This content analysis cannot assess the influence of Asian images on Web users’ perceptions and their further evaluation of the colleges and universities they are seeking. The effects of the images on college and university Web sites could be measured by other means, such as a longitude study on the use of images and students’ enrollments. Interviewing individuals are also useful in determining the effectiveness of the Web as a marketing tool.
This study focused on human photos used on college and university Web sites.
Visuals should include many other elements, such as symbols, non-human photos and multimedia. Non-human photos and symbols are even subtler in terms of creating and representing mental schemas. The influence of the latent information on people’s perceptions can be valuable to study. Future studies can investigate the portrayals of minorities through other visual elements.
Educational marketing should not be limited to a nation’s boundaries. In effect, international enrollments and global education programs extend the market to the world.
Therefore, an examination of portrayals of ethnicities and nationalities under a global context is necessary. Also, visuals travel across cultures and boundaries much more 102 easily and conveniently than verbal message. The effectiveness of visual representation underlines the importance of extending this study to a broader scope. 103
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126
APPENDIX A
All combinations of five races and one ethnicity (64 combinations)
Hispanic Not Hispanic or Latino or Latino*
Single race White 1 33 Black or African American 2 34 Asian 3** 35** American Indian or Alaska Native 4 36 Native Hawaiian or Other Pacific Islander 5 37
Combination of two races White and Black or African American 6 38 White and Asian 7** 39** White and American Indian or Alaska Native 8 40 White and Native Hawaiian or Other Pacific 9 41 Islander Black or African American and Asian 10** 42** Black or African American and American Indian or 11 43 Alaska Native Black or African American and Native Hawaiian or 12 44 Other Pacific Islander Asian and American Indian or Alaska Native 13** 45** Asian and Native Hawaiian or Other Pacific 14** 46** Islander American Indian or Alaska Native and Native 15 47 Hawaiian or Other Pacific Islander
Combination of three races White and Black or African American and Asian 16** 48** White and Black or African American and 17 49 American Indian, or Alaska Native White and Black or African American and Native 18 50 Hawaiian or Other Pacific Islander White and Asian and American Indian or Alaska 19** 51** Native White and Asian and Native Hawaiian or Other 20** 52** Pacific Islander White and American Indian or Alaska Native and 21 53 Native Hawaiian or Other Pacific Islander Black or African American and Asian and Native 22** 54** Hawaiian or Other Pacific Islander Black or African American and Asian and American 23** 55** Indian or Alaska Native 127
(continued) Hispanic Not Hispanic or Latino or Latino*
Black or African American and Native Hawaiian or 24 56 Other Pacific Islander and American Indian or Alaska Native Asian and Native Hawaiian or Other Pacific 25** 57** Islander and American Indian or Alaska Native
Combination of four races White and Black or African American and Asian 26** 58** and American Indian or Alaska Native White and Black or African American and 27 59 American Indian or Alaska Native and Native Hawaiian or Other Pacific Islander White and Asian and American Indian or Alaska 28** 60** Native and Native Hawaiian or Other Pacific Islander White and Black or African American and 29 61 American Indian or Alaska Native and Native Hawaiian or other Pacific Islander Black or African American and Asian and American 30** 62** Indian or Alaska Native and Native Hawaiian or Other Pacific Islander
Combination of five races White and Black or African American and Asian 31** 63** and American Indian or Alaska Native and Native Hawaiian or Other Pacific Islander
No race specified or refused 32 64 * includes not reported. ** indicates a category entirely or partially of Asian. Source: Institution of Education Sciences, n.d.
128
APPENDIX B
Coding sheet
ABOUT THE SCHOOL If a school has multiple photos, just record school info once.
1 Item number _____
2 Institution’s name ______
3 State 1.Calif. 2. Mich. 3.Maine 4. Fla. 5. Others____
4 School type A 1.Public 2.Private 3. Others____
5 School type B 1.Under 2.masters 3. doctoral 4. Others____
6 Enrollment of Asian American students____
7 Enrollment of Asian country students ____
8 Total enrollment ____
9 Total international enrollment ____
10 Mission statement 1. Include diversity 2.no diversity 3. Others____
11 Page 1. Homepage 2. Admission page
12 Number of human photos ______
13 School’s rank ____
ABOUT THE PHOTO If Question 12=0, stop; if Question 12>0, code each photo with models.
14 Number of Asian models ____
15 Number of African American models ____
16 Number of White and other models ____
17 Number of models undecided ____
(continued) 129
ABOUT THE MODEL If Question 14 = 0, stop; if Question 14 > 0, code each model.
18 Relation w/ others 1. Alone 2. w/ Asians 3. w/ other ethnics 4. w/ unidentified others
19 Gender 1. Male 2. Female 3. N/a
Status 20 Setting 1. Classroom 2. Library 3. Labs 4. Other study/research settings 5. Residence hall 6. Gym 7. Cafeterias 8. Outdoors 9. Other social settings 0. N/a
21 Activity 1. Social activities 2. N/a 3. Study/research related
22 Posture 1. Standing tall 2. N/a 3. Knee bent, bowed, and upright leaning body
23 Hands/ 1. Gesturing 2. N/a 3. At rest, fold at side arms hands, raised high
24 Interaction 1. Interact w/ 2. Normal 3. Alone/appear alone others distance/can't tell
25 Expression 1. Cheerful, 2. Can't tell 3. Concerned, serious confident
26 Gaze 1. Look directly at 2. Can't tell 3. Look up/down/with camera/ others eyes closed
Power Position 27 Visual position 1. Visual focus in 2. Equal to 3. Background role photo others/can't tell
28 Visual size 1. Relatively big 2. Equal to 3. Relatively small others/can't tell
29 Function rank 1. Executive role 2. Equal to 3. Submissive role others/can't tell
30 Subordination 1. Physically 2. Can't tell 3. Physically lower body elevated body
130
APPENDIX C
Illustrations
C1. An example of a human photo portraying an Asian male standing (activity) outside (setting) alone (relation to others). He is happily (expression) looking at the camera (gaze) and relaxing with arms at rest (hands/arms).
Source: California State University Channel Islands
131
C2. An example of a human photo portraying an Asian male chatting (activity) with others (relation to others) outdoors (setting). Because he looks directly at others (gaze) with his hands and arms at rest (hands/arms), his expression is unknown (expression), but he keeps a normal distance with others (interaction). In the interaction with other models, he appears in a background role (visual position), visually smaller than others (visual size). His body is lowered and seems submissive (function rank).
Source: California State University Stanislaus
132
C3. An example of a human photo portraying an Asian female performing a research- related activity (activity) in a lab (setting) with other ethnic models (relation to others). She stands upright (posture), gesturing her hand (hands/arms), looking away from the camera (gaze) and smiling (expression). She is the visual focus in this photo (visual position), as big as others (visual size) and in an executive role (function rank) with her head and body elevated (subordination).
Source: Columbia University
C4. An example of a human photo portraying an Asian female studying (activity) in the library (setting) alone (relation to others). She looks away from the camera (gaze) and looks serious (expression).
Source: Columbia University