{"id":313,"date":"2018-08-05T04:10:30","date_gmt":"2018-08-05T04:10:30","guid":{"rendered":"http:\/\/depts.washington.edu\/aromad\/?page_id=313"},"modified":"2026-04-23T17:10:23","modified_gmt":"2026-04-23T17:10:23","slug":"maximum-representation","status":"publish","type":"page","link":"http:\/\/depts.washington.edu\/aromad\/maximum-representation\/","title":{"rendered":"Maximum Representation"},"content":{"rendered":"

What is “maximum representation<\/span><\/strong><\/a>?”<\/p>\n

“The concept AND practice of maximum representation is utilized\/operates under the premise, one unique student can represent and possess two or more ethnic\/racial identities, and we are to respect, support and include these students\u2019 multiple identities in order to enhance the probability of inclusion to various academic and non-academic communities\/memberships\/opportunities for their success.<\/em><\/span>”\u00a0 \u00a0 \u00a0 Gene Kim, Director of Assessment and Research at the Office of Minority Affairs and Diversity\/Former TRIO McNair\/EIP year 2010\/2011 to present.<\/span><\/p>\n

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The concept and practice of “maximum representation” was generated by the OMAD assessment\/data personnel (Gene Kim and Arlyn Arquiza)<\/a> around 2010, when they found out the traditional data query methods inadvertently excluded some of the multiracial\/multiethnic students to specific events, and possible communities within UW (The technical algorithm originated\u00a0 from Gene’s postdoctoral fellowship at the University of Wisconsin-Madison back in the late 1990s\u00a0 where he was tasked to counting one unique student having multiple majors belonging to multiple schools and colleges and having to count them uniquely per schools\u00a0 and colleges within (example: one unique student majoring in history and economics within College of Letters and Science)\u00a0<\/strong> and between schools and colleges(example: one unique student belonging in College of Letters Science majoring in mathematics as well as School of Education majoring in elementary education)).
\nThe diagram below illustrates the need for maximum unique count of majors within and outside various schools and colleges for optimal student and staff support:<\/span>
\n<\/strong><\/span><\/em><\/p>\n

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The concept and practice of “maximum unique count” methods were also proposed to be utilized for unique student with multiple disabilities in the late 1990s at the University of Wisconsin-Madison(For example, one unique student having hearing and visual impairment are counted uniquely once in two categories (ex. visual and hearing impairment) to enhance the student’s support, learning, and success in higher education (When Gene was a young postdoc).\u00a0 T<\/strong>he diagram below illustrates the need for maximum unique count of multiple disabilities per unique individual(s) to optimize the students\u2019 support to enhance their probability of success :<\/strong><\/p>\n

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The\u00a0 maximum unique student count per schools and colleges algorithm as well as the maximum representation (in ethnicity\/race) algorithms were presented at UW-Madison, UW-Seattle,\u00a0 national and state wide conferences spanning 25+ years, and as of recent (December 2023), it was presented at the Washington Educational Research Association Conference via R<\/strong> and Python programming language<\/strong> when Gene was invited to demonstrate the algorithm by Dr. Kenneth Olden and Susan Hou).<\/a><\/p>\n

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To put it simply, maximum representation addresses some of the concerns related to the “two or more races” category and Hispanic\/Latinx “override” from the National Center for Education Statistics (Integrated Postsecondary Education Data System).<\/p>\n

For example, when a single unique multiracial\/multiethnic graduating senior who self-identified as African American and Native American and Pacific Islander, via traditional data query method may have only received one electronic invitation to the black graduation event.\u00a0 Utilizing the concept and the data query method of maximum representation<\/a> (via R and Python), our OMAD assessment data personnel (Gene Kim and Arlyn Arquiza)<\/a>\u00a0made sure our multiracial\/multiethnic graduating senior mentioned received multiple electronic invitation to all three (African American, Native American, and Pacific Islander) graduation events.
\nT<\/strong>he diagram below illustrates the examples of how some of our students self-identify with multiple race\/ethnicity:<\/strong><\/p>\n

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As noted, the concept and practice\u00a0 of maximum representation is a method where we count\/include\/respect the person’s MULTIPLE racial\/ethnic identities independently from counting the number of unique individuals.<\/p>\n

Maximum representation have also been utilized for reporting diversity in enrollment, graduation rates, and admissions data analysis as well as to for the past several years by the Assessment and Research at OMAD (AROMAD) team members<\/a>.<\/p>\n