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Introduction
The Universal Declaration of Human Rights proclaims that everyone is equal from the very birth. The principle of equality is of paramount importance not only for the individual but also for the state, striving to establish fair social relations. Departure from this principle, discrimination on various grounds, poses a serious threat to the normal existence of modern human society. The relevance of the fight against discrimination is evidenced by numerous legal acts aimed at overcoming this negative phenomenon, which is firmly rooted in everyday life. The prohibition of discrimination is one of the most important institutions of modern international labor law.
This paper examines and analyzes the concept of discrimination based on national origin and its application in practice. The sources have been selected to answer four questions. The first source answers the question about the essence of the concept. The second one deals with legislative approaches to it, while an essential feature of this article is a cross-national comparison of approaches. The third paper offers solutions to the problem, and finally, the fourth article points out the current technological barriers to combating discrimination in the workplace.
Gregg Learning. National Origin Discrimination . YouTube (2019): Web.
This video helps distinguish between racial and national origin discrimination and explains the essence of the latter. Such type of negative bias manifests itself in treating employees or applicants differently on the grounds of their ancestry, association, and particular national origin. These features also involve a person being from a certain part of the world or exhibiting some accent associated with a particular ethnicity. National origin discrimination also includes treating an employee differently because they are married or associated with a person of a particular nationality. Some features that indicate an unfavorable national group are linguistic, physical, and cultural traits. While racial discrimination refers to physical characteristics as such (for example, skin color), national origin discrimination is rather based on geographical and cultural characteristics. Of course, it is not always easy to distinguish since a persons origin and race often correlate. As the narrator states, Race refers to a persons physical characteristics, most typically skin color. National origin, on the other hand, refers to where a person was from, or where that persons ancestors were from. The confusion is easy to make since a persons national origin is generally correlated with their race (2:01).
The narrator introduces the Equal Employment Opportunity Commission (EEOC) and its statement concerning the US employers and their language requirements, which are discriminative. Such preconditions are discriminative when are posed for those applicants or employees whose job does not presuppose language fluency for its efficient and safe operation. From this point, it becomes possible to start distinguishing between legal and illegal discrimination.
As the narrator states, Making an employment decision based on an applicants or employees accent when the accent does not interfere with job performance is considered discrimination (1:27). This quote opens up the space for further discussion of legal and illegal discrimination based on national origin. Even though all people are equal in their rights, legislation and law enforcement practice enable the employer to practice discrimination based on ethnicity on a legal basis. This video is popular science and is intended for the broadest audience. Since it provides an introduction to the topic at hand, the language is clear and straightforward, and the presentation is neutral.
Heymann, Jody, et al. Legislative Approaches to Nondiscrimination at Work: A Comparative Analysis Across 13 Groups in 193 Countries. Equality, Diversity, and Inclusion: An International Journal, 7 July 2020. Emerald Insight Journals. Web.
This paper presents the cross-national research on legislative approaches to nondiscrimination at work. The studys sample was secondary data from 13 groups in 193 countries representing each items labor codes, penal codes, equal opportunity legislation, and anti-discrimination legislation. The authors provide a useful analysis of the subject, adding social groups, areas of work, and countries income to their consideration. One of the most relevant to the present discussion findings was that protection across migrant status and national origin was the least common for all groups. Another essential insight is that anti-discrimination measures were mostly focused on the hiring process rather than on promotion/demotion and other practices in the actual working process. The authors provide valuable literature and legislation acts review, as well as discuss the existing practices of discrimination in the workplace. When analyzing the latter, they focused on two areas, hiring and pay, for the reason that literature concerning these domains is the most robust worldwide.
The authors writing style is neutral since the intended audience is scholars and policy-makers concerned with the raised issues. The studys purpose was to widen the scope of academic knowledge in terms of protection practices worldwide, their extent. The researchers also aimed at outlining social groups which were best protected. Although this study is exceptionally encompassing and insightful in terms of its scope and questions analyzed, there are still some issues that need to be raised in future research. Discrimination at the workplace is not limited by the two processes discussed in the study but also includes discriminatory practices in the working everyday routine (for example, bullying) and other forms of unfavorably biased behavior. However, the knowledge about such actions and attitudes is still limited. One could suggest that to fill this gap, an ethnographic study of workplaces and qualitative interviews with people experiencing national-origin discrimination in their workplace could be of benefit.
The disadvantageous findings are expressed in the following quote: Legal protections from discrimination at work based on migrant status, foreign national origin, gender identity or sexual orientation are significantly less common (p < 0.01). Less than 40% of countries in the world provide any form of protection from discrimination at work for migrants (38%, p < 0.01) and workers of different foreign national origins (38%, p < 0.01) (7). The author also argues that discrimination is undesirable for the economy as a whole: Discrimination violates fundamental principles that all people should be treated equally and violates all global human rights agreements; it is also economically inefficient. Discrimination leads to having fewer people in the workforce and leads to selection for positions on bases other than merit. Both reduce productivity. These principles hold across groups (11).
Jefferys, Steve. The Context to Challenging Discrimination against Ethnic Minorities and Migrant Workers at Work. Transfer: European Review of Labour and Research, vol. 21, no.1, 2015, pp. 9-22.
The article discusses issues of xenophobia and anti-immigrant sentiment in Europe while focusing on anti-Muslim prejudice, which has developed in response to the 11 September 2001 events. The author suggests the critique of the Racial Equality Directive, which entered into force in 2003, arguing that it had not had a substantial impact on the underlying levels of racism. One of the essential advantages of this study is its contextualization in political and economic dimensions, wherein the anti-discrimination policy was being developed and implemented.
The article argues that racism is playing a growing role in justifying unequal treatment in employment (9). This quote shows that while analyzing discrimination against ethnic minorities and migrants, the author does not distinguish between racial and national origin discrimination. The author states: Raising immigration barriers and stoking up prejudice against the racialized outsider help place responsibility for the day-to-day problems faced by national workers from rising income inequality to lower levels of welfare support and higher unemployment on the minority (10). From this quote it becomes apparent that it is also a matter of a future sophisticated analysis to find out ways of national workers conceptualization of non-nationals : whether they are perceived as racialized outsiders or as non-nationals in a direct sense.
The paper is intended for a scholarly and politically responsible audience. Since the authors are affiliated with the Department of World Policy Analysis Center at the University of California of Los Angeles, the paper can be considered credible. At the same time, for the same reason, the style of the paper is more persuasion-oriented and critical than an academic paper.
Kim, Pauline T. Data-driven Discrimination at Work. William & Mary Law Review vol. 58, 2017, pp. 857-936.
This paper analyzes the consequences of the data revolution at the workplace in terms of how employers manage their workforces. Data-driven algorithms are also used to make personnel decisions, including choosing who will be interviewed, hired, and promoted. Currently, employers get access to such tools by developing models predicting future job performance. These technologies, also often called people analytics, are designed to help decision-makers to recruit and predict a probability of ones success. The crucial point here is that a large stream of research has shown that data is never neutral, and often it is biased, inaccurate, and unrepresentative. One of the results for the models at the present discussion is that they implicitly discriminate against applicants based on the prejudices inherent to employers and people in general. One such bias is an unfavorable attitude towards a race and a national origin. Most importantly, while employers think that they decrease their anti-discrimination behaviors by delegating a significant part of the recruitment to a machine, they are not aware of these problems inherent in data used for building a predictive model.
In either case, an effective legal response will require developing the doctrine to meet the particular challenges posed by data-driven discrimination (916). This quote shows the authors argument concerning the future of employment legislation. Today, due to the rapid and efficient proliferation of data-driven technologies in all domains of life, it has become impossible to follow the pre-existing logic of dealing with various issues. The following quote seconds this argument: Given the different reasons that data analytics may produce biased outcomes, an effective legal response must differ from traditional disparate impact doctrine in several ways. First, the law should not require employers to purge sensitive information, such as race and sex, from datasets; instead, preserving such data is important to avoid bias (917).
This papers audience is rather broad since it encompasses a wide range of professionals involved in dealing with data-driven technologies at the workplace and discriminatory practices. Although the article is written in an academic style and follows a relatively neutral tone, its message resembles a sort of manifesto for future work in the discussed direction. The most powerful insight here is that it is not enough to delegate ones work to a machine to exclude any form of discrimination.
Conclusion
National origin discrimination at work is a persisting and multi-faceted problem worldwide. Although discriminatory practices in the workplace have been recognized at large, protection from this particular type of unfavorable bias is the least common. At the same time, legal acts aimed at decreasing and mitigating non-national prejudice do not always work as intended, leaving all the underlying prejudices. On the other hand, the practice related to the justification of discrimination, enshrined in the legal field, is also ambiguous. There is legal and illegal discrimination in US legislation, and by the rationale for certain discriminatory actions against an employee, company policy can be justified.
With the rapid development of digital technologies and data-driven tools for prediction and decision-making, negative biases do not disappear. On the contrary, inherent prejudices become even more crucial to recognize and deal with since the ways discriminatory practices become embedded in algorithmic predictive models are not explicit. Thus, there is a danger of reinforcing biased attitudes and actions unknowingly.
Works Cited
Gregg Learning. National Origin Discrimination . YouTube (2019): Web.
Heymann, Jody, et al. Legislative Approaches to Nondiscrimination at Work: A Comparative Analysis Across 13 Groups in 193 Countries. Equality, Diversity and Inclusion: An International Journal, 7 July 2020. Emerald Insight Journals. Web.
Jefferys, Steve. The Context to Challenging Discrimination against Ethnic Minorities and Migrant Workers at Work. Transfer: European Review of Labour and Research, vol. 21, no.1, 2015, pp. 9-22.
Kim, Pauline T. Data-driven Discrimination at Work. William & Mary Law Review, vol. 58, 2017, pp. 857-936.
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