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This is distinguished from taste-based discrimination which emphasizes the role of prejudice (sexism, racism, etc.) to explain disparities in labour market outcomes between demographic groups. [2] The theory of statistical discrimination was pioneered by Kenneth Arrow (1973) and Edmund Phelps (1972). [3]
Comparisons between the impact of chronic, lifetime, and recent experiences of discrimination on mental health shows recent discrimination to have a stronger negative impact than lifetime discrimination; differences in impact based on type of discrimination measured were absent for physical health. [6]
In this framework, for instance, discrimination against black women cannot be explained as a simple combination of misogyny and racism, but as something more complicated. [7] Intersectionality engages in similar themes as triple oppression , which is the oppression associated with being a poor or immigrant woman of color.
As Becker conceptualized, discrimination is the personal prejudice or a "taste" associated with a specific group, originally formulated to explain employment discrimination based on race. The theory is based on the idea that markets punish the discriminator in the long run as discrimination is costly in the long run for the discriminator.
Statistical discrimination may refer to: Statistical discrimination (economics) Linear discriminant analysis (statistics) This page was last edited on 30 ...
This article shows that racism still affects the African American community. From the statistics above, the difference between dark-skinned black wages and white wages is $4.22. $4.22 may seem like a relatively small amount but over time it can accumulate which proceeds to have a substantial impact on financial stability and quality of life.
Achievement gaps in education may represent an example of institutionalized discrimination. Two recent studies aimed to explain the complications of assessing educational progress within the United States. One study focused on high school graduation rates, whereas the other study compared dropout rates in suburban and urban schools. By taking a ...
Some variables that help explain the non-adjusted gender pay gap include economic activity, working time, and job tenure. [35] Gender-specific factors, including gender differences in qualifications and discrimination, overall wage structure, and the differences in remuneration across industry sectors all influence the gender pay gap. [36]