CALI, Coding, and a Network Viewing Experiment

Last week I attended my first CALI conference — CALIcon16 at Georgia State University School of Law.  Props to the organizers for putting together such an excellent program! For those that don’t know already, CALI is the Center for Computer-Assisted Legal Instruction and it’s a pretty amazing outfit. Standing at a critical intersection between legal technology, educational theory, and access-to-justice, CALI sponsors tremendous innovation in teaching and learning while promoting great social values.

Since CALI is also one of the few gatherings where you’re likely to encounter law professors that code, I decided to dip my own toes into the bitstream. I’ve been slowly trying to learn the basics of HTML, CSS, and Javascript over the past year. (This has also meant trying to come to terms with frameworks like Bootstrap and JQuery and getting used to the Sublime text editor and Chrome’s developer tools. Coding these days seems to mean swimming in environment soup…) And I presented the results of my fledgling coding efforts in my CALIcon16 talk.

Specifically, I put together a four webpages designed to showcase SCOTUS Maps created with the free tool hosted on CourtListener. Each page focuses on a basic network theme and  is designed to permit the visitor to switch easily between maps that demonstrate that theme. One page highlights small SCOTUS networks. Another looks at big SCOTUS networks. A third page gives examples of low dissent networks. And the final page features high dissent networks. I’m not sure if this format worked well for others, but I liked it. If folks are interested in looking at networks through this lens, follow the links above and judge for yourselves! As always, I’d love to hear feedback.

Meanwhile, if you’d like to watch my entire talk in which I explain the CourtListener tool and the overall SCOTUS Mapping Project, check out the link to my entire talk right here.



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1 Response to CALI, Coding, and a Network Viewing Experiment

  1. John M says:

    Visualizing data that’s normally difficult to consume and interesting to access/understand is a cool thing. Keep it up! 🙂

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