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3 million. However, the difference in lifetime earnings between men and women cannot be simply attributed to differences in the popularity of certain degree fields since men receive higher earnings in every field. For example, while business degrees were popular and their graduates relatively well paid among both sexes, men earn an estimated $1. 9 million compared to $1. 4 million for womenabout 41 percent more. Even male graduates in fields associated with relatively low earnings among men still earn amounts comparable to the highest earnings of female graduates. Take men who complete bachelor's degrees in the music, fine and visual arts field: they earn roughly $1. 4 millionthe same as women earning degrees in business. The most popular master's degree fields for women and men at Indiana's public institutions are again notably different see Table 2. The most popular field for women is education 30 percent of all graduates followed by business 13 percent. In contrast, over a third of all men's master's degrees are in business, followed by education 16 percent.
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We argue that NPR categorizes groups of people into social classes regarding income inequality, and that it creates power relationships through binaries. Our findings show us that income inequality leads to classification of social categories; which are defined by money and often expressed as opposing binaries. We will now examine the patterns we found in our corpus that support our thesis. We will illustrate this claim by using discourse analysis tools from the Corpus Linguistics CL and Critical Discourse Analysis CDA approaches. This approach will allow us to narrow the focus of our large corpus to a more specified and in depth sub corpus that deals specifically with income inequality. We will also provide examples and explanations for the patterns and key findings we discovered during our research.