Project description:

In early 2017, writer Dana Schwartz posed a question to the Twitter-verse: “Ladies, when was the first time you were made to feel embarrassed and sexualized for what you wore?” In our analysis of 481 school dress codes, we found 37 banned items that accentuate the body. 57% are primarily marketed in stores to girls, 38% to any gender, and only 5% are marketed primarily to boys. Rules that prohibit specific items due to their perceived sexiness (e.g., “short shorts”, “sheer clothing” etc.) impact students wearing clothing marketed to girls more than their peers.

Impact reached:

This project was shared widely by high schoolers on social media. We were even contacted by one student who had started a national campaign and survey to address dress code sexism. This project provided data evidence to confirm the lived experience of most female or female-identifying students.

Techniques/technologies used:

Using the National Center for Education Statistic’s (NCES) search function for public schools, we collected a list of over 8,000 public high schools in the US. We limited the resulting schools to just those that had a web address listed in NCES. Accessing the homepage web content from each site, we searched for words like “handbook”, “dress code”, and “code of conduct”, filtering my list of schools to just those that contain one of the above phrases. Then, we manually visited the resulting (2,000+) websites in an attempt to find the dress code. Dress codes were disqualified from analysis if they: had a uniform policy, were not from the 2018-2019 school year, or represented magnet or boarding schools (according to the NCES).

Once the list of dress codes was compiled, we manually recorded every rule listed in each dress code, the words used in the dress code’s rationale, as well as any listed sanctions for breaking the dress code. Only items and body parts that were explicitly listed were included in this analysis. Some minor subjectivity came into play when combining similar phrases from different handbooks (ex. “midriff shirt” = “crop top”, “shirt with open sides” = “muscle shirt” etc.).

The data was then analyzed in R and the front-end was built out using HTML/CSS, Javascript, and D3.js.

What was the hardest part of this project?

The hardest part was the data collection. Much of it was manual because school handbooks are not uniform and not easily accessible online.

What can others learn from this project?

1. If you put in the work, you can create a robust dataset where one has never existed before.
2. Don’t be afraid to tackle large data projects with a mix of code and manual labor.
3. If you’re dealing with a complex topic, but in the research to make sure you are presenting it responsibly.

Project links:

pudding.cool/2019/02/dress-code-sexualization/