That feeling when data you’re coding is just so bizarre that you don’t know what to make of it. Online communities are a heck of a thing to study.

Helping a student distinguish between backticks and single quotes and remembering the 8th grade keyboarding students from a decade ago who complained that I made them do code in a class they thought should be about learning to type properly. Gotta do the latter to do the former.

My college is floating the idea of investing in GPT-type technology to help researchers code text data. This reminds me of my longtime belief that the distinction between “qual” and “quant” is often less important than the distinction between different research paradigms.

Today I learned that if you replace code that’s held together by other code serving the role of duct tape with actual good code but forget to remove the metaphorical duct tape, the good code still doesn’t work.

I learn a lot of ggplot2 responding to reviewers’ suggestions about plots and a lot of CSS helping students with their questions about Twine games. Turns out I only learn code when I have a project that forces me to.

One of those afternoons where I’m auditing someone’s analysis code, but it’s an analysis of 4M rows of data, so I’m also doing spurts of grading while I wait for code to execute.

When I taught keyboarding, students complained about HTML lessons, asking what it had to do with typing. I explained that if you mistype things, you break things… I’m sure they laugh now every time I bork my website w/ a misplaced line break.

Today’s manuscript revision fun is detangling the results of a coding error that left out 3 hours and 56 minutes worth of tweets from my analysis. Just enough to make some very small differences in reported results.