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How to discriminate between different classes?
Class discrimination is defined as classism. It is prejudice or discrimination based on social class. It involves individual attitudes, behaviors, systems of policies, and practices that are set up to benefit the upper class at the amount as the lower class.
Classism can define personal prejudice against lower classes and institutional classism, just as the term racism can define either strictly to personal prejudice or institutional racism. The latter has been represented as how conscious or unconscious classism is clear in the several institutions of our society".
Class discrimination can be viewed in several forms of media including television shows, films, and social media. Classism is also integral, and its implications can go unseen in the media that is consumed by society.
Class discrimination in the media acts as the knowledge of what a person understands and thinks about classism. When viewing class discrimination in films and television shows, persons are affected and understand that is how things are in real life, for whatever class is being presented.
Class discrimination or comparison mines descriptions that analyze a target class from its divergent classes. For example, the three classes including person, address, and elements are not comparable. But the sales in the last three years are comparable classes.
The attribute generalization for class characterization can be changed so that the generalization is implemented synchronously between all the classes compared. For instance, it needs to compare the data of XYZ Organization for sales i.e., 2002 and 2003, and then compare these for two classes. It is treated the dimension location with abstraction at the city, state, or country level, it is needed to generalize this to either the city level or state level. This type of comparison is more beneficial than comparing it for say, sales in China in 2002 with sales in India in 2003.
The general process for class comparison includes the following steps −
Data collection − The collection of relevant information by query processing and division into target class and another set of contrasting classes.
Dimension relevance analysis − If there are several dimensions and it is convenient to compare them analytically, then dimension relevance analysis must be implemented on these dimensions, and only the highly relevant dimensions are included for comparison.
Presentation of the derived comparison − The final result of the class comparison can be anticipated in the form of tables, graphs, and rules. This presentation includes conflicting measures that follow the comparison among the target and contrasting classes.
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