PERCEPTIONS OF DISCRIMINATION WITHIN A PROFESSIONAL WORK SETTING By Smriti Patil A THESIS Submitted to Michigan State University in partial fulfillment of the requirements for the degree of Human Resources and Labor Relations—Master of Human Resources and Labor Relations 2021 ABSTRACT PERCEPTIONS OF DISCRIMINATION WITHIN A PROFESSIONAL WORK SETTING By Smriti Patil With the rise of diverse workforces, the subject of workplace policies and their lack of inclusive nature should be studied. These policies were created solely through the lens of and for specific demographics and need to be re-analyzed with the voices of an ever-changing workforce. That is why this paper was created to study the impacts discriminatory work policies have on those who to do not conform to the traditional American worker and to identify if those in marginalized communities identify higher levels of discrimination in these policies as compared to those who are not in marginalized communities. This was done through a survey asking over 200 participants to self-identify as being part of one or more identities that fall under marginalized communities and then providing scenario-based questions for them to rate the level of discrimination they can perceive on a scale of 1-5, with 5 being the highest level. ii TABLE OF CONTENTS LIST OF TABLES ......................................................................................................................... iv CHAPTER 1: Introduction ............................................................................................................. 1 1.1 Purpose of Study ....................................................................................................................... 2 CHAPTER 2: Literature Review .................................................................................................... 4 2.1 Dress Codes .............................................................................................................................. 4 2.2 Hair Policy ................................................................................................................................ 7 2.3 Language Discrimination .......................................................................................................... 9 2.4 Summary ................................................................................................................................. 11 CHAPTER 3: Research Method ................................................................................................... 14 3.1 Sample..................................................................................................................................... 14 3.2 Measurement ........................................................................................................................... 15 3.3 Results ..................................................................................................................................... 17 3.4 Discussions ............................................................................................................................. 23 CHAPTER 4: Conclusion ............................................................................................................. 25 BIBLIOGRAPHY ......................................................................................................................... 27 iii LIST OF TABLES Table 1a. Group Statistics – Dress Codes (white and non-white)…….……….……………….. 17 Table 1b. Independent Samples Test – Dress Codes (white and non-white)………..……….…. 17 Table 2a. Group Statistics – Hair Policy_Hijab (white and non-white)…………….….………..18 Table 2b. Independent Samples Test – Hair Policy_Hijab (white and non-white)…….....……..18 Table 3a. Group Statistics – Hair Policy_Straight Hair (white and non-white) ……….………..18 Table 3b. Independent Samples Test – Hair Policy_Straight Hair (white and non-white)………19 Table 4a. Group Statistics – Hair Policy_Grooming (white and non-white) …………..………..19 Table 4b. Independent Samples Test – Hair Policy_Grooming (white and non-white)……...….19 Table 5a. Group Statistics – Language (white and non-white) ………...………………………..20 Table 5b. Independent Samples Test – Language (white and non-white)………..…...………....20 Table 6a. Group Statistics – Dress Code (gender)…………………………...…………………..20 Table 6b. Independent Samples Test – Dress Code (gender)………………..……………….….20 Table 7a. Group Statistics – Hair Policy_Hijab (gender) …………………...…………………..21 Table 7b. Independent Samples Test – Hair Policy_Hijab (gender)………..………..………….21 Table 8a. Group Statistics – Hair Policy_Straight Hair (gender)………………………………..21 Table 8b. Independent Samples Test – Hair Policy_Straight Hair (gender)……..…...………….22 Table 9a. Group Statistics – Hair Policy_Grooming (gender) …………..………..……………..22 Table 9b. Independent Samples Test – Hair Policy_Grooming (gender) ……..…...………….22 Table 10a. Group Statistics – Language (gender) …………………………………...…………..23 Table 10b. Independent Samples Test – Language (gender)……………..…………..……….....23 iv CHAPTER 1: Introduction The COVID-19 pandemic has opened our eyes to the many disparities within the United States (US) and brought attention to wealth inequities and the power dynamics that certain demographics have over each other. People are forced to come to terms with the racism and inequity embedded within the structural basis of many fields, including business. “Many U.S. businesses showed they are willing to profit off of racial inequality — or even support policies that entrench racial inequality.” (Ray, 2021) As a result, it is insinuated that these policies and guidelines have been built around people in positions of power. This paper will primarily focus on the effects of discrimination caused by these power dynamics within workplace settings and the disconnect of perceptions of discrimination between communities. It is important to understand that the demographics of the US have come a long way since the 1930s, around when the National Labor Relations Act was formed and the concept of advocating for employees became more prevalent. During this time, the general demographics of a US employee was typically a middle-aged, white, cisgender male, and while that still holds true today, the diversity of our labor force is significantly higher (U.S Census Bureau, 1933, p. 74). Despite the ever-changing demographics “in the workplace, white supremacy culture explicitly and implicitly privileges whiteness and discriminates against non-Western and non- white professionalism standards related to dress code, [and] speech” (Gray, 2019). Policies that were created to cater to middle-aged white men were more prominent when this demographic was the overwhelming majority. However, many policies that organizations enforce today are still catered to that same demographic (Gray, 2019). They are simply not as apparent as they used to be. 1 Professional dress codes are discriminatory toward those who do not identify as either male or female or are transgender because of discrimination toward the LGBTQ+ community. According to a report done by the University of California, Los Angelos School of Law Williams Institute in September 2021, 46% of members of the working LGBTQ+ community have faced discrimination because of their identity. Additionally, “Discrimination in HR-related decision- making by organizational decision makers can contribute to women being paid less than men are” (Stamarski & Hing, 2015). Policies regarding hair are discriminatory toward Black Americans and/or Muslim women who choose to wear a hijab. (ACLU, 2008) The concept of speaking professionally is discriminatory toward Black Americans who speak African American Vernacular English (AAVE) and toward those who have English as a Second Language (ESL) who may struggle with diction. All these organizational policies, and more, are still only applicable to and beneficial for middle-aged, white, cisgender men, yet are allowed to exist in most organizations because of their historical implications. “Working in contexts of diversities means working in continually changing contexts of complexity and unpredictability” (Vandenbroeck, 2012). It is time to reconsider what has been, for the most part, the status quo and adapt to the ever-changing climate of the US in order to increase inclusivity as a response to the increase of diversity in race, gender, age, and all other demographics, instead of requiring everyone to follow policies historically created for one. 1.1 Purpose of Study The purpose of this paper is to understand the context of everyday organizational policies such as dress codes, hair policies, and language guidelines and re-examine their use in today’s world through the lens of different demographics. The recent shift to emphasize a good work culture is essentially a reinstatement of organizational policies and is typically “perpetuating 2 workplace discrimination and segregation” (Green, 2005). Green identifies work culture as a reason for discrimination for employees as well as the increasing “demands to assimilate” as a result to increasing diverse employee populations, instead of creating more inclusive policies. It is important to examine which policies fall under the guise of culture but that inherently have high levels of discrimination in order to move forward by altering these accordingly. In this study I will look at historically non-marginalized groups and their perceptions of discrimination compared to dominant groups. The purpose of this study is to identify the disconnect between people in positions of power who might not recognize discrimination, and those who are in marginalized communities. An understanding of this disconnect may bring light to why perpetuations of discrimination exist despite multiple movements to end it. The findings from this study contribute to diversity in workplace literature by calling attention to the gap in perceptions of discrimination by racial majority and minority groups. 3 CHAPTER 2: Literature Review For the purpose of this paper, the definition of discrimination is the employee perception of unjust and/or negative treatment based on the identification of a person (Dhanani et al., 2018). This is a broad generalization due to the fact that there are identities that are not covered under the legal definition of discrimination that will be mentioned in this paper. Professionalism has a myriad of definitions that all depend on the industry, however, for the purpose of this paper, will be working with the definitions established by Davis (2016) in the sense that professionalism is a set of standards concerned with appearance (including dress, speech, and grooming) as to appear competent and respected/respectful. In other words, professionalism can be considered general business etiquette. Business etiquette can further be defined as “a set of guidelines that determine how you interact with colleagues, upper management, customers and other stakeholders. Business etiquette includes […] dressing appropriately for the office and communicating respectfully” (Williams & Smith, 2020). These guidelines, or policies, dress codes, and communication requirements all encompass what it means to be an arguably good professional but are these policies inherently discriminatory? 2.1 Dress Codes It is no secret that discrimination is still prevalent in today’s workforce. Most dress codes go against religious requirements as well as gender identities and even result in cases of sexual discrimination. Cases of restaurants and bars requiring female servers to dress differently from male servers have cause for liability (Westall, 2015). In a specific incident regarding dress codes in 2004, a server was asked to wear a bikini top while working so she then took her case to the British Columbia (B.C) Human Rights Tribunal and was awarded $6,000. This was because it was found that men and women had vastly different clothing expectations, with women being 4 expected to be subjected to clothing with sexual connotations. It is rare for these complaints to arise, however, because according to Geoffrey Howard, an employment lawyer at Gowling Lafleur Henderson LL, "simply complying with the dress code seems like the path of least resistance." Similarly, it can be alluded to that many complaints regarding dress codes that disrespect religions are also tossed aside because it is easier to simply comply. While companies must legally adhere to religious and disability accommodations, the dress codes themselves are rooted in misogyny, racism, or religious bias, and they force employees to ask for exceptions when in most cases, dress codes are unnecessary and have no correlation to work performance. (Rollings, 2020) “61% of employees are more productive when the dress code is relaxed, and 80% of people who work in an environment with a dress code responded that they don’t find them useful” (Rollings, 2020). Furthermore, while employers can legally have dress codes, “allowing clothing unique to a person’s religion can lead to better motivated and more loyal employees” (Borstorff, 2011). Despite seeing higher performance with lax dress codes, some companies still have strict dress code requirements. In the case that attire is linked to employee safety within manufacturing plants or any other situation involving safety hazards, strict dress codes are permissible if they are tied to employee health and safety. In all other cases, dress codes simply are a hindrance to employees and employers alike. In the case Bostock v. Clayton County (2020), the Supreme Court ruled that gender identity and/or sexual orientation was covered by Title VII in the prohibition against discrimination on sex, protecting members of the LBGTQ+ community against discrimination. This case sets an important precedent when it comes to protecting the LGBTQ+ community in terms of self- expression at work, and in dress attire. Similarly, in the case R.G. & G.R. Harris Funeral Homes 5 Inc. v. Equal Employment Opportunity Commission (2020), a transgender woman, Aimee Stephens, was wrongfully terminated after expressing her identity through dress attire and won the lawsuit against her employer. Aimee Stephens had previously presented as a man and wore clothes that were male presented as it was according to the dress code, and then decided to wear a skirt and jacket as well as informed her employer that she would be transitioning from male to female and then was terminated. Dress codes were historically not designed to respect identities that did not conform to the traditional straight male attire, and it is crucial for employers to understand the importance of having flexible work attire that makes their employees feel at ease and comfortable to express themselves. It is also important for companies to be aware of religious requirements, clothing attire, and general information regarding different ways, especially because “a survey performed by Public Agenda revealed that most Americans are ignorant of religions other than their own” (Borstorff, 2011). This ignorance could potentially explain why there is such a gap between employment policies and the reality of workforce demographics. For example, in the EEOC v. Abercrombie & Fitch (2015) case, Samantha Elauf was not hired because she was a Muslim woman who wore a hijab, as per her religious requirements. The Supreme Court ruled in favor of EEOC as Abercrombie’s decision had violated Title VII. After Elauf had expressed interest in working at Abercrombie, she was denied due to the dress code that existed at the time, banning headwear, under the excuse that Elauf was not conforming to the “look policy.” Abercrombie’s dress code and the inherent religious discrimination within their policies was extremely problematic and deterred many Muslim woman from seeking employment with the company. Overall, the multiple cases filed regarding dress codes and the research indicating that employees choosing their work attire allude to lax dress codes being 6 much more beneficial to the employee and the employer and that dress codes are a hassle because of their inherent discrimination. 2.2 Hair Policy In addition to dress codes, policies on hair are also deeply rooted in discrimination. Policies involving hair may have “a disparate impact on those with Afro-textured hair” because their hair is perceived as unprofessional (Cohen, 2021). Requiring hair to be straight is additional, uncompensated work for employees who have naturally very curly hair, and it can conflict with identities of Black Americans. This is also very prevalent in the education system, where Black girls have often been sent home for wearing their hair naturally, which “criminalize[s] their Black identity” (Lattimore, 2017). Education policies similar to these that are accepted are then transferred into the workforce, which perpetuates discrimination and forced assimilation. “U.S. courts are still divided about African Americans’ right to wear their natural hair in the workplace.” (Griffen, 2019) In 2010, a Black woman, Chastity Jones, was asked to cut her dreadlocks off after receiving a job offer and filed a complaint with the EEOC, which then launched the EEOC v. Catastrophe Management Solutions, Inc. case. Jones ended up losing the case because it was found that dreadlocks were not inherited physical characteristics of Black people, despite having historical and cultural significance. (Griffen, 2019) A related case exists with beard bans. Additionally, “razor bumps, known medically as pseudo folliculitis barbae, are an inflammatory skin condition. They mostly affect people with coarse, curly hair who remove it by shaving or plucking. When tightly coiled hair is shaved closely, it may retract below the skin’s surface and break through the follicle wall. The razor bumps that result can lead to dark marks, scar tissue, and even infection.” (Nittle, 2018) This skin condition has affected many Black men 7 who work within a company that imposes a beard ban because the best treatment for this ailment is to stop shaving altogether. One Black man, Langston J. Bradley, was told to shave his beard for his part-time job at a pizza place, Pizzaco, whose franchiser is Dominos and found this policy unfair, especially because he was given a waiver during his time in the military. Bradley filed a claim and in the case Bradley v. Pizzaco of Nebraska, Inc. (1993) the employer was found guilty of employment discrimination. Despite this decision, “in 1990, a survey by The New York Times of 40 state and municipal police departments around the country found that all but three generally prohibited employees from growing beards.” (Lewin, 1993) Beard bans and hair policy exist despite numerous claims of discrimination, which makes it extremely hard for employees to fight for their medical accommodations. As previously mentioned, in regard to dress codes, it is easier for many employees to simply comply. Likewise, Indian American men who practice Sikhism are prohibited from cutting their hair due to religious reasons and are also discriminated against because of the beard ban. Surjit Singh Saund attempted to apply for a job at a convenience store and was denied because Saund did not conform to the grooming policy of being clean-shaven, which is against Saunds religion. Saund explained his situation and the company remained by their position of employing only clean-shaven people, stating that they would offer a job if Saund removed his turban, cut his hair, and shaved his beard, all vital aspects of the Sikhism religion. Saund ended up filing a discrimination claim, Saund V. M. M. Fowler, Inc. to defend his religious accommodations. Similarly, employers requiring hair to be visible is discriminatory against Muslim women who choose to wear hijab, as was previously discussed in regard to dress codes. There is a major culture clash with Islam and Western values and the general understanding of personal identification and freedom, which is prominent in work in the form of policies involving hair. 8 Muslims have historically been seen in the West as “fundamentally uncivilized and unwilling to conform to the values of the West” (Afshar, 2008), which is why there is the continued tradition of pushing Muslim people to assimilate in the US. While religious freedom and the right to wear religious clothing is federally protected, policies involving hair visibility forces Muslim women to ask for accommodations and have still “been harassed, fired from jobs, denied access to public places, and otherwise discriminated against because they wear hijab” (ACLU, 2008). Just as it was found in the EEOC v. Abercrombie & Fitch (2015) case, employers should not be permitted to enforce dress codes or hair policies that conflict with religious requirements. 2.3 Language Discrimination Communication, or language, is another aspect of business etiquette previously discussed that is subject to discrimination. Perceived accent and dialect evoke positive or negative reactions from listeners (Carlson & McHenry, 2006), and when brought into work settings, can have a positive or negative bias from co-workers, supervisors, and/or and subordinates. The concept of professional communication can be extremely difficult for those who do have different dialects and backgrounds. Black employees are expected to “code-switch [which] involves adjusting one’s style of speech, appearance, behavior, and expression in ways that will optimize the comfort of others in exchange for fair treatment, quality service, and employment opportunities,” which is a strategy used to navigate interracial situations and largely impacts economic advancement (McCluney et. al, 2019). According to Mcluney et. al (2019), there are three reasons why employees will code- switch: (a) Downplaying association of marginalized communities will increase perceptions of professionalism, (b) Black employees can be seen as leaders by avoiding any negative 9 associations with Black racial identity, and (c) Promoting association with the dominant groups at a company will increase the likelihood of promotions. What is interesting to note here is, again, the perceived perception of professionalism based on a person's identity to the point of employees changing their entire persona. In a study conducted by Mcluney et. al (2019), the biggest reasons why Black employees will code-switch are leadership aspirations, fit beyond race - which is the idea that employees can connect on hobbies, interests, and other ways beyond their racial identity - vigilance, and to promote a diverse environment. According to Carlson and McHenry (2006), there are three major dialects that are different from Standard American English (SAE), which are AAVE, Spanish-influenced English, and Asian-influenced English, yet there are multiple dialects from varying communities. Listeners associate these dialects with social status (Carlson & McHenry, 2006), because of stereotypes and implicit bias, which then instigates prejudice within professional settings. Employees are expected to communicate in SAE, which is generally accepted as professional communication (Oetting, 2020), however, all dialects should be considered professional and acceptable, because language is an aspect of someone’s identity and employees should not be expected to hide their identities to be accepted at work. What is important to add regarding code-switching is that there is another level of emotional labor when it comes to remote work, according to Ekemezie (2021), because it is even harder to consciously code-switch within the comfort of one's home, where people are meant to be themselves. “As remote work blends the personal and the professional, this may have a negative effect on the wellbeing of workers who have relied on code-switching to get through their workdays.” (Ekemezie, 2021) In addition to dialects, professionals who speak ESL also face discrimination. The burden of ensuring the listener understands typically falls on the non-SAE speaker while those who do 10 speak SAE feel the entitlement of expecting those around them to understand their own dialect (Pent et al., 2020). This re-stigmatizes accents at work as well as pushes for assimilation, which is impelled to those who do not speak SAE, instead of those who do speak SAE. The responsibility of communication and comprehension must fall equally upon both speakers to form a fully inclusive environment and the first step is to abolish the policy of professional communication being limited to only SAE. 2.4 Summary There is plenty of research that identifies discrimination at work yet not enough regarding the policies that allow this to happen. Further research needs to be done regarding the link between historical (and current) workplace policies that are still in existence and their perpetuation of discrimination at work. Universally accepted policies such as dress codes and hair policies, as well as the general perception of what it means to be a professional need to be re-assessed through the lens of increasing diverse perspectives, religions, cultures, and lifestyles. The fact that these policies exist despite the multiple lawsuits and claims of discrimination further illustrates the gap of perceptions of discrimination at work between marginalized and non- marginalized communities. This paper extends the work done by Stamarski and Hing (2015) in different ways. Stamarski and Hing (2015) proposed that workplace discrimination was a direct consequence of HR practices while alluding to extending organizational structure and leadership impacting HR strategies and thus, workplace policies. Their study also focused primarily on sexism and gender inequality at work and briefly mentioned other forms of discrimination. This paper extends on the work done by including other forms of discrimination, focusing on specific policies such as dress codes, hair policies, and language, instead of fixating on a specific community. My study 11 in this paper was a measure of the impacts of these discriminatory policies upon affected communities, which is a component Stamarski and Hing (2015) hoped to examine in further research. What I hope to achieve through this paper is a contribution to diversity research at organizations by examining potential roots of perpetuating biases and injustices through policymaking. Organizations need to critically analyze the impacts that their policies have on marginalized communities and re-evaluate the need for such policies in a workforce setting that exists today. This paper also extends the work done by Davis (2016) and his study regarding Anti- Blackness within professional environments. While Stamarski and Hing (2015) focused on sexism, and Davis (2016) emphasized on Anti-Blackness, I wanted this paper to further elaborate on the different demographics and the gaps of understanding between communities. Davis (2016) set important precedents on the operational domains of Whiteness and Blackness as well as the “anti-Black bias in the definition and enforcement of professionalism.” His paper re- emphasized the existence of discrimination within professionalism and prompted the existence of this study, with similar hypotheses and goals to further the understanding of professionalism and discrimination at work. Research by Dobbin and Kalev (2011) suggest that people from historically marginalized groups will not only be more sensitive and empathetic to workplace discrimination and will be more willing to advocate for under-represented groups. Based on this, I believe that women and members of underrepresented groups will be more likely to identify as discriminatory workplace policies and practices that are based on traditional, white, male cisgender norms that may negatively impact members of historically marginalized groups. Thus, I offer the following hypotheses: 12 Hypothesis 1: Women will be more likely to label as discriminatory traditional work policies that address (a) dress codes, (b) hair policies, and (c) language. Hypothesis 2: Members of minority groups are more likely to label as discriminatory traditional work policies that address a) dress codes, (b) hair policies, and (c ) language. 13 CHAPTER 3: Research Method The purpose of this study is to examine the responses of those in marginalized communities to answer the research question: (1) do people in marginalized communities perceive higher levels of discrimination in workforce policies under the guise of professionalism compared to those who are not in marginalized communities? Based on the research done regarding discrimination in work policies as well as the definition of professionalism derived from Davis (2016), I wanted to analyze the disconnect between communities. This study thus focused on scenarios with dress codes, hair policies, and linguistic discrimination because these are recurring issues seen in a professional environment, which is proven by the numerous cases and complaints filed by individuals in minority communities. 3.1 Sample The sample consisted of 238 responses collected using Amazon MTurk. Participants were asked to fill out survey questions with the first portion of questions being related to demographic data, including but not limited to age, gender, sexuality, and ethnicity. Participants were then asked to read scenario-based questions and then rate the level of discrimination perceived within each scenario. Out of 238 responses, I did not include data from participants who did not answer all the survey questions. This lowered the sample size to 219. I also did not collect any identifying information about any respondents. Out of the 219 participants, 66.66% identified as male or man. Ages ranged from 18-72. Out of 219 responses, 75.63% of participants identified as Not Hispanic, Latino, or Spanish origin, and 24.73% identified as Hispanic, Latino or Spanish origin. 14 Out of 226 responses, 21.24% of participants identified as Mexican, Mexican American, or Chicano. 3.54% identified as Puerto Rican. 3.84% identified as Cuban. 71.68% identified as Not Hispanic, Latino, or Spanish. Out of 229 responses, 10.04% identified as Black or African American, 67.69% identified as White, 6.99% identified as Native American/Indigenous Peoples/American Indian, 13.97% identified as Asian or Pacific Islander, .44% identified as Other, and .87% declined to respond. Out of 222 responses, 51.80% identified as Not Asian or Pacific Islander, 22.07% identified as Asian Indian, 5.6% identified as Other Asian, 5.41% identified as Other Pacific Islander, 4.05% identified as Chinese, 3.60% identified as Native Hawaiian, 1.80% identified as Filipino, 1.80% identified as Japanese, 1.80% identified as Guamanian or Chamorro, 0.90% identified as Samoan, 0.45% identified as Korean, and 0.45% identified as Vietnamese. Out of 232 responses, a majority of 87.00% of participants had work experience while 13.00% did not have work experience. Out of 224 responses, 60.71% identified as not being part of the LGBTQ+ community, 13.39% were unsure or still deciding, and 25.89% identified as being a part of the community. 3.2 Measurement In order to answer the research question about perceptions of workplace discrimination, I had participants rate scenario-based questions on a scale of 1-5, with 1 being the lowest level of discrimination. The first scenario-based question addressed dress codes: A business wants to set expectations on professionalism that involves a strict dress code for all people-facing roles. The manager wants to have everyone wearing the same colors so that the staff maintains a unified front. The manager 15 dictates that all men should be wearing black slacks, white button-downs, and black blazers. The manager also dictates that all women should be dressed in black dresses with white aprons. Many employees who identify as non-binary and/or transgender have asked for exceptions for this uniform requirement, yet management wants to enforce this rule according to the respective sex assigned at birth to enforce the formality of the business. Participants were then asked to answer in a similar way to the second question. (Note: a brief explanation preceded the second question that read Hair Policy: The business also has a strict policy regarding hair. Everyone’s hair must be straightened, neat, and visible (no hats are allowed). There is also a policy banning any facial hair, enforcing shaved faces. The second question addressed hair policies for three separate occasions: (1) Muslim women have repeatedly told management that this interferes with their religious requirement of wearing a hijab. (2) Women of African descent have also brought up issues with styling their hair in a straight hairstyle because it adds time, often requires them to go through a chemical and/or heat straightening process, and it is costly. (3) Black men have issue with this policy because of a common skin ailment that affects their face when they shave. It is easier and less painful to allow facial hair to grow. The last scenario-based question was again answered in the same way as the first two and addressed language: Language: A supervisor wants to speak to a Black associate regarding their recent emails. Lately, this employee has been using diction that is commonly associated 16 with AAVE (African American Vernacular English) when communicating with clients that have a similar background to the employee. An example of AAVE in this context is the Black associate acknowledging their clients struggle with a new software system, replying with “I been there.” The supervisor wants to have a discussion surrounding unprofessionalism and AAVE and wants to uphold standards of speaking in SAE (Standard American English). The employee states that there has been no issue with communication and no complaints have arisen from any of his clients. If anything, speaking in AAVE builds a stronger relationship with those who also speak in AAVE. 3.3 Results A two-sample t-test was performed to compare perceptions of discrimination in marginalized groups and non-marginalized groups. The marginalized groups were further divided into racial categories and gender. Table 1a. Group Statistics – Dress Codes (white and non-white) N Mean Std. Deviation Std. Error Mean White 81 2.9 1.578 0.175 Not White 144 3.27 1.23 0.103 Table 1b. Independent Samples Test – Dress Codes (white and non-white) Leverne's Test for Equality of Variances T-Test for Equality of Means Sig. (2- Std. Error F Sig. T df tailed) Mean Difference Difference Equal variances assumed 12.256 .001 -1.949 223 0.053 -0.37 0.19 Equal variances not assumed -.1820 135.213 0.071 -0.37 0.203 17 In Table 1 there was no significant difference in perceptions between white (M = 2.90, SD = 1.578) and non-white (M = 3.27, SD = 1.230); t(135.213) = -.1820, p = 0.071, two-tailed. The magnitude of the differences in the means (mean difference = -0.37, 95% CI: -0.771 to 0.032) was very small (eta squared = 0.015). The results from this table do not support Hypothesis 1a. Table 2a. Group Statistics – Hair Policy_Hijab (white and non-white) N Mean Std. Deviation Std. Error Mean White 76 2.97 1.549 0.178 Not White 142 3.3 1.242 0.104 Table 2b. Independent Samples Test – Hair Policy_Hijab (white and non-white) Leverne's Test for Equality of Variances T-Test for Equality of Means Sig. (2- Std. Error F Sig. T df tailed) Mean Difference Difference Equal variances assumed 6.326 .013 -1.670 216 0.096 -0.322 0.193 Equal variances not assumed -.1820 135.213 0.12 -0.322 0.206 In Table 2 there was not a significant difference in perceptions between white (M = 2.97, SD = 1.549) and non-white (M = 3.30, SD = 1.242; t(135.213) = -.1820, p = 0.12, two-tailed. The magnitude of the differences in the means (mean difference = -0.322, 95% CI: -0.73 to 0.086) was very small (eta squared = 0.011). The results from this table do not support Hypothesis 1b. Table 3a. Group Statistics – Hair Policy_Straight Hair (white and non-white) N Mean Std. Deviation Std. Error Mean White 76 2.97 1.549 0.178 Not White 142 3.3 1.242 0.104 18 Table 3b. Independent Samples Test – Hair Policy_Straight Hair (white and non-white) Leverne's Test for Equality of Variances T-Test for Equality of Means Sig. (2- Std. Error F Sig. T df tailed) Mean Difference Difference Equal variances assumed 3.940 .048 -0.626 215 0.532 -0.121 0.193 Equal variances not assumed 0.590 129.994 0.556 -0.121 0.205 In Table 3 there was not a significant difference in perceptions between white (M = 3.18, SD = 1.529) and non-white (M = 3.30, SD = 1.253); t(129.994) = 0.590, p = 0.556, two-tailed. The magnitude of the differences in the means (mean difference = -0.121, 95% CI: -0.526 to 0.284) was very small (eta squared = 0.002). The results from this table do not support Hypothesis 1b. Table 4a. Group Statistics – Hair Policy_Grooming (white and non-white) N Mean Std. Deviation Std. Error Mean White 76 3 1.47 0.169 Not White 141 3.3 1.298 0.103 Table 4b. Independent Samples Test – Hair Policy_Grooming (white and non-white) Leverne's Test for Equality of Variances T-Test for Equality of Means Sig. (2- Std. Error F Sig. T df tailed) Mean Difference Difference Equal variances assumed 3.243 .073 -1.575 215 0.117 -0.305 -0.194 Equal variances not assumed -1.518 138.235 0.131 -0.305 0.201 In Table 4 there was not a significant difference in perceptions between white (M = 3.00, SD = 1.470) and non-white (M = 3.30, SD = 1.298); t(215) = -1.575, p = .117, two-tailed. The magnitude of the differences in the means (mean difference = -0.305, 95% CI: -0.687 to 0.077) was very small (eta squared = 0.011). The results from this table do not support Hypothesis 1b. 19 Table 5a. Group Statistics – Language (white and non-white) N Mean Std. Deviation Std. Error Mean White 76 2.72 1.457 0.167 Not White 143 3.36 1.241 0.104 Table 5b. Independent Samples Test – Language (white and non-white) Leverne's Test for Equality of Variances T-Test for Equality of Means Sig. (2- Std. Error F Sig. T df tailed) Mean Difference Difference Equal variances assumed 2.805 .095 -3.378 217 0.001 -0.633 0.187 Equal variances not assumed -3.217 133.538 0.002 -0.633 0.197 In Table 5 there was a significant difference in perceptions between white (M = 2.72, SD = 1.457) and non-white (M = 3.36, SD = 1.241); t(217) = -3.378, p = .001, two-tailed. The magnitude of the differences in the means (mean difference = -0.322, 95% CI: -1.002 to -0.264) was very small (eta squared = 0.050). The results from this table support Hypothesis 1c. Table 6a. Group Statistics – Dress Code (gender) N Mean Std. Deviation Std. Error Mean Male 152 3.13 1.316 0.107 Female 73 3.15 1.497 0.175 Table 6b. Independent Samples Test – Dress Code (gender) Leverne's Test for Equality of Variances T-Test for Equality of Means Sig. (2- Std. Error F Sig. T df tailed) Mean Difference Difference Equal variances assumed 1.882 .171 -0.097 223 0.922 -0.019 0.196 Equal variances not assumed -0.093 126.995 0.926 -0.019 0.205 20 In Table 6 there was not a significant difference in perceptions between male (M = 3.13, SD = 1.316) and female (M = 3.15, SD = 1.497); t(223) = -.097, p = .922, two-tailed. The magnitude of the differences in the means (mean difference = -0.019, 95% CI: -0.405 to 0.367) was very small (eta squared = 4.219E-05). The results from this table do not support Hypothesis 2a. Table 7a. Group Statistics – Hair Policy_Hijab (gender) N Mean Std. Deviation Std. Error Mean Male 145 3.19 1.293 0.107 Female 73 3.16 1.5 0.176 Table 7b. Independent Samples Test – Hair Policy_Hijab (gender) Leverne's Test for Equality of Variances T-Test for Equality of Means Sig. (2- Std. Error F Sig. T df tailed) Mean Difference Difference Equal variances assumed 5.983 .015 1.47 216 0.884 0.029 0.196 Equal variances not assumed 1.40 127.012 0.889 0.029 0.206 In Table 7 there was not a significant difference in perceptions between male (M = 3.19, SD = 1.293) and female (M = 3.16, SD = 1.500); t(127.012) = .140, p = .884, two-tailed. The magnitude of the differences in the means (mean difference = 0.029, 95% CI: -0.379 to 0.436) was very small (eta squared = 9.073E-05). The results from this table do not support Hypothesis 2b. Table 8a. Group Statistics – Hair Policy_Straight Hair (gender) N Mean Std. Deviation Std. Error Mean Male 144 3.19 1.292 0.108 Female 73 3.4 1.47 0.172 21 Table 8b. Independent Samples Test – Hair Policy_Straight Hair (gender) Leverne's Test for Equality of Variances T-Test for Equality of Means Sig. (2- Std. Error F Sig. T df tailed) Mean Difference Difference Equal variances assumed 5.214 .023 -1.043 215 0.298 -0.203 0.195 Equal variances not assumed -1.000 129.441 0.319 -0.203 0.203 In Table 8 there was a significant difference in perceptions between male (M = 3.19, SD = 1.292) and female (M = 3.40, SD = 1.470); t(129.441) = -1.000, p = .319, two-tailed. The magnitude of the differences in the means (mean difference = -0.322, 95% CI: -0.604 to 0.199) was very small (eta squared = 0.005). The results from this table do not support Hypothesis 2b. Table 9a. Group Statistics – Hair Policy_Grooming (gender) N Mean Std. Deviation Std. Error Mean Male 144 3.17 1.34 0.112 Female 73 3.25 1.422 0.166 Table 9b. Independent Samples Test – Hair Policy_Grooming (gender) Leverne's Test for Equality of Variances T-Test for Equality of Means Sig. (2- Std. Error F Sig. T df tailed) Mean Difference Difference Equal variances assumed 1.579 .210 -0.371 215 0.711 -0.073 0.197 Equal variances not assumed -0.364 137.381 0.716 -0.073 0.200 In Table 9 there was not a significant difference in perceptions between male (M = 3.17, SD = 1.340) and female (M = 3.25, SD = 1.422); t(215) = -.371, p = .711, two-tailed. The magnitude of the differences in the means (mean difference = -0.073, 95% CI: -0.586 to 0.181) was very small (eta squared = 0.001). The results from this table do not support Hypothesis 2b. 22 Table 10a. Group Statistics - Language (gender) N Mean Std. Deviation Std. Error Mean Male 146 3.31 1.263 0.104 Female 73 2.79 1.462 0.171 Table 10b. Independent Samples Test – Language (gender) Leverne's Test for Equality of Variances T-Test for Equality of Means Sig. (2- Std. Error F Sig. T df tailed) Mean Difference Difference Equal variances assumed 2.545 .112 2.690 217 0.008 0.514 0.191 Equal variances not assumed 2.562 126.993 0.012 0.514 0.201 In Table 10b there was a significant difference in perceptions between male (M = 3.31, SD = 1.263) and female (M = 2.79, SD = 1.462); t(217) = 2.690, p = .008, two-tailed. The magnitude of the differences in the means (mean difference = 0.514, 95% CI: -0.46 to 0.314) was very small (eta squared = 0.032). The results from this table support Hypothesis 2b. 3.4 Discussions According to the tables discussing perceptions between white and non-white communities, Tables 1-4 do not support Hypotheses 1a and 1b (p>0.05) for each result. Table 5 supports Hypothesis 1c (p<0.05). According to the tables discussing perceptions between genders, Tables 6-9 do not support Hypothesis 2a and 2b (p>0.05) for each result. Table 10 support Hypothesis 2c (p<0.05). These results indicate that marginalized communities do in fact perceive discrimination differently than those who belong to non-marginalized communities when it comes to language. Both non-white communities and women identified higher levels of discrimination within the language policy. This could be because marginalized communities have noticed conversations 23 being considered as unprofessional for discriminatory reasons as opposed to dress codes and hair policies. There was no significant difference between groups for hair policies and this could be because even though there was a significantly higher number of non-white participants, most of these participants had Asian descent and might not come into contact with the same discrimination people of African descent do in terms of hair. Similarly, in terms of dress policies, there were no participants who identified as non-binary, therefore there was a lack of representation from people who might have been in a similar situation as the dress policy. It may be difficult for binary participants (men and women) to emphasize with non-binary people and their perception of discrimination. 24 CHAPTER 4: Conclusion A limitation of this study is the single source research method designed to draw data from. Ideas for future research would be multiple methods in the form of interviews with participants to create a personal effect, observations of participants who are placed in situations with discrimination and examining behavior that is differentiated between marginalized communities, and a mixed method of the above options. More ideas of future research could be further dividing the different responses and/or reactions of marginalized communities instead of studying marginalized and non-marginalized communities. This way, reactions of model minorities could potentially differ from participants who do not identify as the model minority. Other researchers such as Stamarski and Hing (2015) have shown the detrimental effects of discrimination on marginalized communities, specifically women, and Davis (2016), who have further emphasized the effects on Black people, yet these studies have relied on survey and self- reported data. Survey data has been proven to be problematic due to the necessity of introspection on behalf of the participants (Porath & Erez, 2007). According to Porath and Erez (2007), these lead to several limitations on studies based on the use of survey data, one of which being participants at time guessing the purpose behind the survey and answering questions accordingly. In this case, it is quite easy for participants to know the purpose behind the survey, as they were required to submit consent forms that went over a brief summary of the survey and the reasoning behind it. Thus, the validity of this particular study may be skewed based on participants answering questions with a pre-conceived notion of answering “correctly.” Ideas for future research should include an observation of participants being subjected to discriminatory situations to perceive reactions based on facial expressions, self-identified emotions, and/or conversations. 25 It is critical to understand that racism not only exists in the workforce but is perpetuated within policies and the general understanding of what it means to be professional. These policies are kept in place by people in power who may not understand the inherent discrimination within them. That is why this study will potentially offer insight into the gaps in perceptions between marginalized and non-marginalized communities and create further understanding as to why many everyday policies are outdated and harmful through the lens of different communities (Stamarski and Hing, 2015). People of higher privilege who have created and sustained such policies need to understand the implications behind dress codes, hair policies, and communication standards and the barriers that exist for minorities to succumb to such guidelines. Discrimination takes mental tolls on affected communities (Ekemezie, 2021), so it is essential to re-evaluate what keeps discrimination in the workforce and how to dismantle the very system that sustains it. 26 BIBLIOGRAPHY 27 BIBLIOGRAPHY Afshar, H. (2008, January 16). Can I see your hair? choice, agency and attitudes: The dilemma of faith and feminism for Muslim women who cover. Taylor & Francis. Retrieved September 15, 2021, from https://www.tandfonline.com/doi/full/10.1080/01419870701710930. American Civil Liberties Union (ACLU). Discrimination against Muslim women - fact sheet. American Civil Liberties Union. (2008,10, December 14). Retrieved September 15, 2021, from https://www.aclu.org/other/discrimination-against-muslim-women-fact-sheet. Bradley v. Pizzaco of Nebraska, Inc. 7 F.3d 795 (8th Cir. 1993) Borstorff, P. (2011). PROTECTING RELIGION IN THE WORKPLACE? WHAT EMPLOYEES THINK. Journal of Legal, Ethical and Regulatory Issues, 14(1), 59-70. Retrieved from http://ezproxy.msu.edu/login?url=https://www.proquest.com/scholarly- journals/protecting-religion-workplace-what-employees/docview/886552633/se- 2?accountid=12598 Bostock v. Clayton County, Georgia, 590 U.S. (2020) Carlson, H.K. and McHenry, M.A. (2006), Effect of accent and dialect on employability. Journal of Employment Counseling, 43: 70-83. https://doi.org/10.1002/j.2161- 1920.2006.tb00008.x Census. (1933). 1930 Census: Volume 5. General Report on Occupations. United States Census Bureau. Retrieved 2021, from https://www2.census.gov/library/publications/decennial/1930/population-volume- 5/41129379v5ch3.pdf. Cohen, S. (2021, March 8). The Truth within our Roots: Exploring Hair Discrimination and Professional Grooming Policies in the Context of Equality Law. HeinOnline. Retrieved September 15, 2021, from https://heinonline.org/HOL/LandingPage?handle=hein.journals%2Fyorklr2&%3Bdi v=9&%3Bid=&%3Bpage=. Davis, Mark D., "We were treated like machines: professionalism and anti-Blackness in social work agency culture" (2016). Masters Thesis, Smith College, Northampton, MA. https://scholarworks.smith.edu/theses/1708 Dhanani, L. Y., Beus, J. M., & Joseph, D. L. (2018). Workplace discrimination: A meta-analytic extension, critique, and future research agenda. Personnel Psychology, 71(2),147–179. https://doi.org/10.1111/peps.12254 Dobbin, F., Kim, S., & Kalev, A. (2011). You can’t always get what you need: Organizational determinants of diversity programs. American Sociological Review, 76(3), 386-411. 28 EEOC v. Abercrombie & Fitch, 575 US (2015) Equal Employment Opportunity Commission v. Catastrophe Management Solutions, Inc. No. 14-13482 (11th Cir. 2017) Gray, A. (2019, June 4). The bias of 'professionalism' standards (SSIR). Stanford Social Innovation Review: Informing and Inspiring Leaders of Social Change. Retrieved December 3, 2021, from https://ssir.org/articles/entry/the_bias_of_professionalism_standards. Green, T. K. (2005). Work Culture and Discrimination. California Law Review, 93(3), 623–684. http://www.jstor.org/stable/3481474 Griffin, C. (2019, July 9). How natural black hair at work became a civil rights issue ... How Natural Black Hair at Work Became a Civil Rights Issue. Retrieved November 28, 2021, from https://daily.jstor.org/how-natural-black-hair-at-work-became-a-civil-rights-issue/. Lattimore, K. (2017, July 17). When black hair violates the dress code. NPR. Retrieved September 15, 2021, from https://www.npr.org/sections/ed/2017/07/17/534448313/when- black-hair-violates-the-dress-code. Lewin, T. (1993, November 3). Beard ban ruled unfair to blacks. The New York Times. Retrieved November 28, 2021, from https://www.nytimes.com/1993/11/03/us/beard-ban- ruled-unfair-to-blacks.html. McCluney, C. L., Robotham, K., Lee, S., Smith, R., & Durkee, M. (2021, January 28). The costs of code-switching. Harvard Business Review. Retrieved November 28, 2021, from https://hbr.org/2019/11/the-costs-of-codeswitching. Nittle, N. (2018, September 28). Why workplace bans on facial hair marginalize men of color. Vox. Retrieved November 28, 2021, from https://www.vox.com/the- goods/2018/9/28/17916056/workplace-beards-facial-hair-black-men-sikhs-publix-chick- fil-a. Oetting, J. B. (2020, November 16). General American English as a dialect: A call for change. @ASHA. Retrieved September 15, 2021, from https://leader.pubs.asha.org/do/10.1044/leader.FMP.25112020.12/full/. Parvini, S., & Simani, E. (2019, March 28). Are Arabs and Iranians white? census says yes, but many disagree. Los Angeles Times. Retrieved September 15, 2021, from https://www.latimes.com/projects/la-me-census-middle-east-north-africa-race/. Peng, Y., Genç, E., Nicholson, B. et al. (2020) Not professional enough to be a therapist: international therapists’ experience of language discrimination. https://doi.org/10.1007/s12144-020-00848-4 Porath, C. L., & Erez, A. (2007). Does rudeness really matter? The effects of rudeness on task performance and helpfulness. Academy of Management Journal, 50, 1181-1197. 29 Ray, V. (2021, January 25). Why did companies take so long to divest from white supremacy? Harvard Business Review. Retrieved December 3, 2021, from https://hbr.org/2021/01/why-did-companies-take-so-long-to-divest-from-white- supremacy. Rollings, M. (2021, June 24). Does what we wear to work affect our productivity? Hive. Retrieved September 15, 2021, from https://hive.com/blog/office-dress-productivity/. R.G. & G.R. Harris Funeral Homes Inc. v. EEOC, 590 U.S. 140 S. Ct. 1731 (2020) Saund v. M.M. Fowler - Complaint (U.S. District Court for the Eastern District of North Carolina) Sears, B., Mallory, C., Flores, A., & Conron, K. (2021, October 6) LGBT People's experiences of workplace discrimination and harassment. Williams Institute. Retrieved December 3, 2021, from https://williamsinstitute.law.ucla.edu/publications/lgbt-workplace- discrimination/. Stamarski, C. S., & Son Hing, L. S. (1AD, January 1). Gender inequalities in the workplace: The effects of organizational structures, processes, practices, and decision makers' sexism. Frontiers. Retrieved November 28, 2021, from https://www.frontiersin.org/articles/10.3389/fpsyg.2015.01400/full. Westall, R. (2015, April 1). Asking servers to wear revealing clothes could violate rights | CBC News. CBCnews. Retrieved September 15, 2021, from https://www.cbc.ca/news/canada/restaurant-dress-codes-open-to-sexual-discrimination- complaints-1.3012522 Williams, V., & Smith, J. (2020, September 1). Chapter 14: Professionalism, etiquette, and ethical behaviour. Fundamentals of Business Communication. Retrieved September 15, 2021, from https://pressbooks.bccampus.ca/businesswritingessentials/chapter/10-2- professionalism-etiquette-and-ethical-behaviour/. Vandenbroeck, M. (2012). Evidence-Based Practice, Professionalism and Respect for Diversity: A Tense Relation. Asia-Pacific Journal of Research in Early Childhood Education, 6(1), 1–20. 30