Across the last three units, you were introduced to a sociological phenomenon called "intersectionality." "Intersectionality" means that one category of marginalization (e.g., class or race) can overlap with another (e.g., gender). These three categories/variables (i.e., class, race, and gender/sexuality) significantly affect access, opportunity, and engagement with sport across several domains (i.e., college sport, pro sport, sport media, etc.), and when these variables intersect, barriers or rewards in the sport system can be amplified.

In May (2020), Vanderbilt announced that it removed the interim tag from their new hire as head athletics director (AD). Candice Storey Lee became the first woman A.D. in the SEC and, per the story, the second black woman to assume a head AD position at a Power 5 school. As you read the story in Vanderbilt's Lee Becomes SEC's 1st Woman Athletic Director(Links to an external site.), consider how both gender and race are the story.

After considering intersectionality as the media story on A.D. Lee presents it, review the TIDES data that show how marginalization and intersectionality play out across sport domains.The TIDES Lab out of UCF(Links to an external site.), run by Dr. Richard Lapchick, compiles the data on race and gender variables across several domains of sport. For your response to this discussion board, look through the report cards on the TIDES website(Links to an external site.). There are several TIDES 'Race and Gender Report Cards.' Please look through all of them. Some examples include the NFL(Links to an external site.), Media(Links to an external site.), and College(Links to an external site.) Report Cards.

If you noticed any patterns across the distributions of race and gender variables in leadership or participation in sport, consider how those might combine, or intersect, for people who fall into more than one category of marginalization...

Describe the consequences of intersectionality as they are evidenced in one or more of the TIDES report cards. Also, consider that layered into those data are class (i.e., resources), ability (vs. disability), and sexuality as variables that further intersect.