Hagan: Judgepedia and crowdsourcing court-user info

Dr. Margaret Hagan of Stanford University has posted Judgepedia & crowdsourcing court-user info, at Open Law Lab.

Here are excerpts:

[… Judgepedia] is great in that it compiles disparate information that is available on lots of random sites around the web, and then creates a standard & searchable single experience for a user to more easily navigate. The standardization is a great benefit.

Still, there is lots of potential to expand from this basic educational information & get to a new service for consumers of court services. When I first saw the title Judgepedia, I was expecting more info for the legal user — for someone who will be encountering the judicial system and wanting to know how to deal with a certain judge.

That kind of product would provide stats & metrics about lawyers and judges — which seems like a forbidden territory in the legal domain. Even if such an evaluative product could be developed, it seems there would be serious vested interests that would block its implementation.

But still, that seems to be where the real need is.

The more I study legal consumers, the more it becomes clear that a main unmet need of lawyers & clients is to build better strategies to get legal tasks done. This is where there is huge promise in crowdsourced information. If we can share information on what strategies work best within specific parts of the legal system & with certain judges — and which ones fail — this would be a huge benefit to litigants. Or if we could build a stats system that tracks judges’ behavior & preferences, this would similarly equip legal users with ways to better prepare their strategies.

The outstanding challenge, then, is how to gather, check, & share this crowdsourced information (which would be a huge undertaking in itself) — and to do it in a way that would survive challenges by lawyers, judges, and others who have a vested interest in resisting evaluation. […]

For more details, please see the complete post.

HT @margarethagan

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