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I spent a decent amount of time playing with the correlation tool for both the corpus and the Pamela text alone. I was to hoping
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I spent a decent amount of time playing with the correlation tool for both the corpus and the Pamela text alone. I was to hoping to try and correlate gendered titles with other words that could give me some context for Armstrong's arguments. Instead, I slowly realized the futility of the task that I had laid out. At first glance, mrs. has nice P-values when correlated with jealous, civil, crying, religion and love in the corpus. However, the sample size is surprisingly small with under two hundred hundred entries across the entire corpus for almost all of those words. Additionally, the correlations themselves have rather insignificant values. At this point, I dove through the documentation to understand what the correlation tool was actually doing. The tool, rather than doing a type of weighted distance analysis between words, was actually just comparing frequencies across the texts. Specifically in the corpus, the tool was simply comparing frequency trends between words with the indices being the documents itself. This type of analysis is never going to tell me much besides individual word frequency trends across documents, especially with only seven documents, and is not really what I was looking for. I think it would be interesting if correlations were more sentence specific, where I can instead look at words that frequently appear near other words, in a non-trivial sense (she, said (that would be trivial)). I looked at the same thing within just the Pamela source text, and instead of frequencies being divided by text, they seem to be divided by "segments," which I can't really find a definition for. More generally, my methodology doesn't make much sense because of the first person narration in Pamela, looking at a word like Mrs. is only theoretically going to give me correlations with Jervis and Jewkes. However, I did get interesting results when I looked at the word Pamela, as she is referred to almost always by other characters. I got strong P an R values with words like grave, design, girl, and loss. I'm not really sure how to deal with those words, especially design, but I suspect conversations involving a character calling her Pamela also involve said character referring to her gender in some form or another. Girl is not an insignificant sample either, with 169 mentions. I do still wish the segment form was replaced with something more specific.