Draft:Ellis Monk

• Comment: Much of this content inadequately cited to any source. Much of it seems to be a personal reflection then factual information based on third party reliable sources. McMatter ^(talk)/_(contrib) 04:21, 4 March 2025 (UTC)

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Ellis Monk

Ellis Monk is a professor of sociology at Harvard University, where he has taught since 2018. His academic interests are centered around comparative perspectives on race/ethnicity and technology, skin tone and colorism, and sociology of the body.

Before working at Harvard, Monk worked as a Neubauer Family Assistant Professor of Sociology at the University of Chicago from 2015-2016 and as an Assistant Professor of Sociology at Princeton University from 2016-2018. His work in discovering correlations between skin-color in the African-American community as well as developing the Monk Skin Tone Scale has been considered highly influential to others in his field.

Education

Ellis Monk earned a B.A. in Sociology from the University of Michigan, Ann Arbor, where he studied from 2002-2006. He then pursued a master’s degree in Sociology at the University of California, Berkeley, which he completed in 2008. Lastly, he earned a PhD in Sociology from the University of California, Berkeley, where he wrote a dissertation titled Color, Bodily Capital, and Ethnoracial Division in the U.S. and Brazil, which provided the foundational research that he later expanded on in his professional works...  

Professional Career

Monk has held various positions at top institutions. He began as a Provost’s Postdoctoral Scholar in the Department of Sociology at the University of Chicago (2013–2015), later serving as the Neubauer Family Assistant Professor of Sociology (2015–2016) and affiliating with the Population Research Center, NORC, as well as the Center for the Study of Race, Politics, and Culture, and the Center for Latin American Studies.

He later moved to Princeton University (2016–2018). He was an Assistant Professor of Sociology, a Faculty Associate at the Office of Population Research (OPR) and Princeton Institute for International and Regional Studies (PIIRS), and a Faculty Affiliate with the Program in Latin American Studies, the Center for Health & Wellbeing, and the Kahneman-Treisman Center for Behavioral Science & Public Policy.

He continued his career at Harvard University, where he served as an Assistant Professor of Sociology (2018–2020), then Associate Professor (2020–2023), and currently as a Professor of Sociology. He also holds affiliations with the Weatherhead Center for International Affairs, African and African American Studies (AAAS), the Afro-Latin American Research Institute (ALARI), and the Center for Population and Development Studies.

In addition to their academic roles, he has been a Visiting Faculty Researcher at Google since 2022, further expanding their contributions to research and interdisciplinary collaboration.

Research and Ideas

Infracategorial Model of Inequality

In Monk’s Inequality Without Groups, he introduced his theory of the Infracategorical Model of Inequality (ICMI), which posits that sociological research on inequality should shift its focus from simply looking between different social identity groups (e.g. Black vs White, male vs female), to looking at the different categories within these groups. He identifies the former paradigm as the Standard Model of Inequality (SMI), which involves using state categorized race, ethnicity, and gender categories to analyze various inequalities.

Monk believes that viewing inequality with the ICMI rather than only using the SMI would result in a deeper, more analytical understanding of inequality. He also felt that bringing such research in alignment with contemporary, rather than classical Aristotelian theories of categorization by:

1. Shifting from identifying membership in nominal categories
   1. Monk felt that simply identifying individuals’ membership in certain categories of social identity (e.g. race, ethnicity) did not capture the nuances of how inequality impacts people in their everyday lives. Instead, he believed that inequality research should focus on cues of categories (overlapping characteristics of each social identity group), subcategories, and individuals’ perceived typicality with the ideal norm of their social identity group. One method of studying this “perceived typicality” is levels of graded membership, which Monk defines as the degree to which a respondent self-identifies as belonging to social identity category.
2. Centering the role of the body in inequality
   1. Monk also believed that one’s body plays an important role in signifying social differences and perceived discrimination. Thus, he believed that there is value in looking beyond highly visible categories of difference and attempting to more deeply understand the nuances of social categorization. As an example, Monk noted the subcategory of skin tone in Brazil, which was found to be a stronger predictor of socioeconomic inequality than state categorized racial identity in the country.
3. Increasing the analysis of intra-group inequalities to the level of intergroup inequalities
   1. Monk believed that the focus that sociological research had on between-group inequalities often either did not address or distracted from those that develop within-group.
4. Focusing on aspects of social division that are not currently addressed
   1. By dedicating increased attention to aspects of social categorization that are not as fully addressed, Monk believed that research could be used to highlight existing inequalities that were not being addressed.

In all, Monk felt that an increased focus on using the ICMI, rather than the commonly (and in most cases, solely) used SMI in sociological research would allow for a more holistic view of inequality and how it impacts individuals in their daily lives.

Skin Tone, Race, and Ethnicity

Skin Tone-Discrimination-Health Pathway

In Monk’s The Cost of Color: Skin Color, Discrimination, and Health Among African Americans, he identifies a concept he terms the skin tone-discrimination-health pathway, which posits that skin color discrimination within the black community results in negative health outcomes among African-Americans. Additionally, skin-color discrimination within the African-American Previous to The Cost of Color, very few studies had attempted to test this correlation, largely to inconclusive results. He measures this effect on two measures: physical and mental health.

Skin Color and Discrimination:

While similar studies measuring the impact of discrimination on health outcomes examine relationships interracially, Monk took an intraracial approach by focusing on how skin color differences are crucial in determining health outcomes for African-Americans. In doing so, he determined that health differences within the African-American racial group often exceeded those between black and white populations.

Monk’s first significant finding was a strong association between skin-color and perceived discrimination in daily life. He found that darker-skinned respondents identified higher rates of discrimination/unfair treatment in their everyday lives from white people, with these respondents having 126% higher odds of perceiving more skin color discrimination from white people than lighter-skinned respondents. Furthermore, a respondent’s self-rated skin color was an even stronger indicator of perceived discrimination than interviewer-rated skin color scales. Monk identified self-rated skin color as a form of subjective social status (one’s perceived rank compared to others in a group).

Monk also took an intraracial perspective on discrimination, measuring how much discrimination within the African-American community was perceived by members of certain skin color groups. As a result, he discovered that intraracial skin color discrimination has very different patterns than interracial skin color discrimination. Whereas the latter form revealed increased discrimination towards darker-skinned individuals and decreased discrimination towards lighter-skinned individuals when perceived by white people, the former revealed both lighter and darker skinned individuals perceiving a strong degree of discrimination from within the black community.

Another interesting takeaway from Monk’s research is that African-Americans’ self-reported skin tone predicted perceived discrimination stronger than interviewer ratings. Thus, Monk’s study proves how skin-color ratings are not only a form of subjective social status, but also a form of embodied social status (one’s social standing based on physical characteristics). Thus, his study expanded on the original concepts of subjective social status by Nancy Adler, social status as defined by Max Weber, and habitus as developed by Bourdieu.

Physical Health:

Monk’s study identified a correlation between perceived discrimination and health outcomes. Specifically, respondents who reported higher rates of perceived discrimination (specifically from other Black Americans) had higher odds of reporting being in worse physical health. For example, he found that the darkest-skinned African-Americans had 94% higher odds of suffering from hypertension than the lightest skinned African-Americans.  

Mental Health:

Furthermore, Monk found that skin color is a predictor of self-reported mental health, even when controlling for other forms of discrimination. As with physical health, respondents who reported higher degrees of discrimination also self-reported having worse mental health. Interestingly, Monk found that the effect of skin color discrimination on African-Americans from other African-Americans was larger than that from white people. Monk also found higher rates of depression among darker-skinned respondents than lighter skinned respondents.

Monk’s work in establishing a relationship between skin color, discrimination, and health was crucial, as it links the previously interrelated variables of discrimination and health outcomes (specifically, that an increase in perceived discrimination results in poorer health outcomes), with a third variable, skin color.

Skin Tone in the US and Brazil

In his PhD dissertation titled Color, Bodily Capital, and Ethnoracial Division in the US and Brazil, Monk delves into many of the topics that he would continue to explore in his professional career, such as the impact of skin color on discrimination, the importance of self-reported data, and the relevance of intraracial classifications in sociological research. In this dissertation, Monk shows the importance of skin tone and hair types have on Black individuals’ social experiences in both the United States and Brazil. He takes a mixed-methods approach to the topic by combining data from nationally representative data sets in the U.S. and Brazil with 100 in-depth interviews.

In this dissertation, Monk comes to many significant conclusions about the social and economic impacts of skin tone on black Americans and Brazilians that he continues to examine in The Cost of Color, particularly his finding that skin tone and hair texture have been used as a classification/stratification system within black communities. Using this paradigm, Monk determined that both characteristics, but skin-tone especially, result in differentials in educational attainment, household incomes, and occupational status amongst black Americans and Brazilians. More specifically, darker-skinned individuals had worse outcomes in all three socio-economic categories compared to their lighter-skinned counterparts. Thus, this dissertation reveals that colorism and texturism exist as significant forms of discrimination no independent of cultural context.  

The Monk Skin Tone Scale

The Monk Skin Tone Scale (MST) is a 10-point skin color measurement system Ellis P. Monk Jr., developed to capture the diversity of human skin tones, particularly focusing on representation in the Americas and beyond. The scale was specifically designed to address limitations in existing skin tone classification systems, such as the well-used Fitzpatrick Skin Type (FST) scale, and to study skin tone stratification and colorism better

Background and Purpose:

Skin tone classification systems are used for a variety of purposes, including medical treatment, social science research, and more recently, artificial intelligence (AI) and machine learning. However, many of these systems have been inadequate in capturing the full range of skin tones. The MST was developed to improve color representation, address bias, and inequality in AI and machine learning applications, and provide a more socially informed measure that considers real-world implications of colorism and skin tone stratification.

1. Scientific Background
   • The scale emerged from research on skin tone stratification and colorism in the social sciences
   • It was explicitly designed to capture variation in human skin color for examining social inequality and discrimination
   • The development was informed by global research on the relationship between skin tone and UV radiation distribution
2. Design
   • Features 10 carefully selected skin tones to represent the dynamic range of human skin colors
   • Includes both orbs and squares for color matching, with orbs providing more nuanced shading
   • Designed to be practical and cost-effective for measuring common differences in human skin color

Adoption and Implementation

1. Industry Adoption
   • Google adopted the scale after internal testing showed greater efficiency compared to previous skin tone models
   • Facebook/Meta incorporated the scale into their Casual Conversations dataset for developing unbiased AI systems
   • MST has been adopted to improve fairness in machine learning systems, including facial recognition and image classification
2. Research Validation
   • A nationally representative U.S. study found the Monk Scale to be significantly more inclusive than the Fitzpatrick Scale
   • The scale performed particularly well among historically marginalized communities and people with darker skin tones
   • Research showed it achieved similar inclusivity ratings as the 40-point Fenty Beauty palette, despite having only 10 points 8

The Monk Skin Tone Scale represents an advancement in skin tone measurement, particularly in its ability to bridge social science research with practical applications in technology. It contributes to research on skin tone stratification and colorism. It has enabled a more accurate study of how skin tone differences correlate with various life outcomes. Its development and adoption demonstrate the importance of inclusive design in addressing social and technical skin tone classification challenges.

Minority Health and Technological Bias

In his NIH-funded research project, The Optics of Health: Race, Skin Tone, Minority Health, and Health Disparities in the U.S., Ellis Monk examined the relationship between race, skin tone, and health disparities in the United States. His research, funded by a $1.521 million grant from the National Institute of Mental Health, addressed the long-standing racial inequalities in health outcomes, with a particular focus on social stress and algorithmic biases in medical technology as contributing factors to these disparities

Health Disparities and Social Stress

Monk’s research highlighted persistent racial health disparities in the U.S., which were exacerbated by the COVID-19 pandemic. Studies have shown that Black Americans experienced earlier onset of disease, greater disease severity, and poorer quality healthcare than their White counterparts. Monk's methodology combines longitudinal, nationally representative surveys of African Americans with technological research, collaborating with optics experts to identify and correct biases in medical equipment. His project investigated how social stress, measured through dysregulation of the Hypothalamo-Pituitary-Adrenocortical (HPA) axis, contributed to these health disparities. His findings have revealed that health inequalities within the Black population along the skin tone continuum can be as substantial as the disparities between racial groups. This research has become particularly relevant during the COVID-19 pandemic, where studies showed that African Americans experienced a reduction in life expectancy at 3-4 times the rate of White Americans.

Algorithmic Bias in Medical Technology: Pulse Oximetry

The significance of Monk's work extends into practical healthcare applications. His studies have demonstrated how skin tone-related algorithmic biases in medical technology, particularly in pulse oximeters, devices widely used to measure blood oxygen levels, can significantly affect the quality of healthcare delivery. This is particularly crucial in the context of pulse oximetry readings, where inaccurate measurements could lead to delayed or missed medical interventions for patients with darker skin tones. His study revealed that pulse oximeters frequently overestimated oxygen saturation levels in individuals with darker skin, leading to missed diagnoses and inadequate treatment.

Monk worked to identify and correct these biases in pulse oximetry. His research contributed to the development of more equitable diagnostic tools designed to function accurately across all skin tones. For his contributions, Monk was awarded the 2022 NIH Director's New Innovator Award for his research.

Awards

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2023

• Theory Prize, American Sociological Association (ASA) Section on Theory, for "Inequality without Groups: Contemporary Theories of Categories, Intersectional Typicality, and the Disaggregation of Difference" (Sociological Theory)
• Distinguished Contribution to Scholarship Article Award, ASA Section on Race, Gender, and Class, for "Beholding Inequality: Race, Gender, and Returns to Physical Attractiveness in the U.S.A." (American Journal of Sociology)
• Best Article Award, ASA Section on the Sociology of Body and Embodiment, for "Beholding Inequality: Race, Gender, and Returns to Physical Attractiveness in the U.S.A." (American Journal of Sociology)

2022

• Devah Pager Article Award, Honorable Mention, ASA Section on Inequality, Poverty, and Mobility, for "Beholding Inequality: Race, Gender, and Returns to Physical Attractiveness in the U.S.A." (American Journal of Sociology)

2019

• George Kahrl Award for Excellence in Teaching, Department of Sociology, Harvard University

2018

• Oliver Cromwell Cox Article Award, ASA Section on Racial and Ethnic Minorities, for "The Cost of Color: Skin Color, Discrimination, and Health among African Americans" (American Journal of Sociology)

2016

• Outstanding Recent Contribution to Social Psychology Award, ASA Social Psychology Section, for "The Cost of Color: Skin Color, Discrimination, and Health among African Americans" (American Journal of Sociology)

2013

• Herbert Blumer Prize, Best Graduate Student Paper Award, University of California, Berkeley, for "The Cost of Color in the United States: Skin Color, Social Distance, Discrimination, and Health among Black Americans."

2012

• James E. Blackwell Distinguished Graduate Student Paper Award, Honorable Mention, ASA Section on Racial and Ethnic Minorities, for "Skin Tone Stratification among Black Americans, 2001-2003."

2010

• Herbert Blumer Prize, Best Graduate Student Paper Award, University of California, Berkeley, for "Towards a Regional Model of ‘Race’ in Brazil."

2009

• Herbert Blumer Prize, Best Graduate Student Paper Award, University of California, Berkeley, for "Race, Campaign Contributions, and the Road to Electoral Success."