Olympic participation by country
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We have another lesson plan that deals with medal counts. This one deals with the harbinger of medal counts, participating in the games. Some sports have cultural biases, like skeet shooting. Others require higher degrees of apparatus to participate at a high level like gymnastics. While others require much less like running or football (i.e., soccer).
In this lesson students can use the visual graphs at the UK Guardian’s web site (http://www.guardian.co.uk/sport/datablog/interactive/2012/jul/27/olympic-athletes-list-visualised) to analyze the participants by country with a global mapping device. They can reduce it to a sport category or for overall participation. Or they can focus on gender participation–some country athlete delegations are entirely or almost entirely male, for instance.
What kinds of questions can be asked?
Compare sport configurations by country: How does the Olympic team for the United States compare with the Olympic team from Kenya? What patterns are noticed? (note: the % of total team which would be a good way to do this analysis doesn’t work properly at the site for teams with small numbers like Kenya-but can be hand calculated by students using total athletes instead by simply mousing over each part of the graph as illustrated). Note that both the United States and Kenya have beaches on oceans, but only the United States has a beach volleyball team in the Olympics. Note also the wide variety of sports in the United States compared to Kenya and the focus in Kenya on sports with lower barriers to entry (athletics-track&field as well as boxing). The screen shot below also shows that Kenya’s two swimmers are white, whereas all those in athletics and boxing are black–illustrating likely social class differences in access to higher level sports. The CIA World Factbook has the following breakdown by ethnicity for Kenya: https://www.cia.gov/library/publications/the-world-factbook/geos/ke.html
Kikuyu 22%, Luhya 14%, Luo 13%, Kalenjin 12%, Kamba 11%, Kisii 6%, Meru 6%, other African 15%, non-African (Asian, European, and Arab) 1%
Take a look at gender participation: Students might look for patterns among the lowest gender participating countries. Alternatively, students could compare gender participation with the country’s ranking in the Global Gender Gap report by the World Economic Forum.
Have students analyze the percent of team numbers: For instance, create a graph of percent of team for football (soccer). Students might be asked whether from the graph they can determine whether the men’s or women’s football team qualified for the United States.
The next challenge is why if the teams are all male and all female, we see countries as categories as 0% female, 50% female, or 100% female and 0% male, 50% male or 100% male–that the total is 57% male and 43% female.
See if students can figure out that there 12 women’s teams and 16 men’s teams from the graphical data.
The finally piece here is to see if students can help solve the riddle of Cameroon: a country not noted for gender equity but for whom 73 percent of its athletes are female (this may also help explain other disparities found) With Cameroon, where nearly 3/4’s of its athletes are female and 59 percent of the entire team is the women’s football squad. Yet Cameroon ranks only 119th (Saudi Arabia is 131) in the Gender Gap ratings. This could be a puzzle for students to figure out. See if students can figure out using Cameroon’s country profile that the women’s football team qualifying distorts their female participation.
Finally, students can debate whether total athletes or athletes per 100,000 is a better measure. They can also examine the use of scale and truncation versus rounding, as there are some limitations to the design.
The United Kingdom leads in total number of athletes, but students can find that on a per capita basis, the UK ranks 67th. The United States is second in total athletes but on a per capita basis ranks even lower at 134. However, the graph’s scale should be pointed out to students that by extending up to 40 per 100,000 to cover the Cook Islands, the scale isn’t able to show subtle but significant differences at the lower end where most countries are. However, the Guardian site also provides specific country sites that do show the figure more accurate. For the United States a full breakdown can only be hand calculated (it appears that truncation is used as the United States has more than 0.5 athletes per 100,000, but less than 1.0 athletes, but shows up as 0 per 100,000 in the graph). But at the country profile site, students can see the per capita membership as well as percent membership as well as male and female breakdowns for each sport.
Students can calculate the United States actual participation either from the spreadsheet or by manually adding for each sport category and then discuss why truncating as a rounding mechanism can be misleading, especially in this context.
Screen shots below: