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Why It's Unjust to Expect Location-Specific, Language-Specific, or Population-Specific Service from Students with Underrepresented Minority or Low-Income Backgrounds

Overview of attention for article published in The AMA Journal of Ethic, March 2017
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9 tweeters
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1 Facebook page

Citations

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18 Mendeley
Title
Why It's Unjust to Expect Location-Specific, Language-Specific, or Population-Specific Service from Students with Underrepresented Minority or Low-Income Backgrounds
Published in
The AMA Journal of Ethic, March 2017
DOI 10.1001/journalofethics.2017.19.3.ecas1-1703
Pubmed ID
Abstract

In this case we meet Amanda, a medical student of Native and Latin American ethnicity who receives financial aid. Her friends are surprised by her interest in an elite residency program. They suggest, rather, that with her language skills, ethnic background, and interest in social justice, she has a responsibility to work with underserved patient populations. In our commentary, we consider issues raised by the case and explore Amanda's friends' underlying expectations and assumptions that perpetuate the very inequities that the resolution of the case purports to address. We also identify the role of privilege and address the "burden of expectation" that appears to be associated with underrepresented minority (URM) medical students and normative assumptions about their career paths.

Twitter Demographics

The data shown below were collected from the profiles of 9 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 18 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 18 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 4 22%
Other 3 17%
Student > Master 2 11%
Professor 1 6%
Student > Ph. D. Student 1 6%
Other 3 17%
Unknown 4 22%
Readers by discipline Count As %
Medicine and Dentistry 6 33%
Nursing and Health Professions 2 11%
Social Sciences 1 6%
Environmental Science 1 6%
Engineering 1 6%
Other 0 0%
Unknown 7 39%