Case Study 1: Data Transformation Stage 1

I created a simple spreadsheet using Google Docs to compile the information I was pulling out of the articles. This included the article name, author(s) name(s), year of publication, and the pronouns (if any) ascribed to the character Ariel. My method for finding this information was simple, but time and labor intensive. I opened each article, searched the text for the name Ariel, and read as many of the surrounding sentences were still discussing the character to see if there was a pronoun used. If the PDF was not searchable I would skim the entire article. There are likely programming methods that would have made this process go faster and easier, but there were some advantages to my method. The first is that it served my programming skill level, and demonstrates that having an advanced technical education is not always necessary for doing digital projects. The second is that it allowed this step to act as another point in which the documents were being checked for relevance. The third is that manually reading through the articles gave me a sense of the context in which Ariel was being discussed; something that eventually influenced the direction of the project.

The results of this stage were initially disappointing. Of the thirty-nine articles, book chapters, and dissertations, only two used gender neutral pronouns for the character. Ten never used a pronoun for Ariel. The other twenty-seven all used the male pronouns he/his.


Ariel SS 2 Ariel SS 2.5












I will admit that I had hoped for some kind of trend towards gender-neutral pronouns as time went on. As far as this data showed, the two instances of neutral pronoun use were in 2007 and 2014; both fairly recent but too isolated and scattered to predict any kind of trend.


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