LLLotW 2023.23

New research: The lived experience of open educational resources (OER) creator-practitioners

Something you can join on Tuesday:

This presentation will outline new research on the lived experience of creator-practitioners of open educational resources (OER) and open educational practices (OEP) in United States (U.S.) higher education institutions.

Why Are UK Libraries Signing a Springer-Nature Deal They Don’t Seem to Like?

Despite being an article on Scholarly Kitchen this is actually quite good and provides a solid overview of the challenges academic libraries face as the filling in the scholarly publishing sandwich. Worth a read, especially if you don't understand why libraries won't just stop paying such extortionate fees to data miners uh I mean “scholarly publishers”.

“Low-Resource” Text Classification: A Parameter-Free Classification Method with Compressors

I admit I don't understand a lot of this paper but the gist seems to be that it's possible to do some basic processing with gzip and achieve pretty similar results to NLP tools that usually require enormous amounts of compute power:

Our method achieves an accuracy comparable to non-pretrained neural network classifiers on in-distribution datasets and outperforms both pretrained and non-retrained models on out-of distribution datasets. We also find that our method has greater advantages under few-shot settings.

Essentially, it's a smart hack to massively reduce the resources required to do large language model processing, especially with data sets that aren't well labelled (i.e. untrained). This has a lot of potential for smaller and niche pattern-matching tasks – which describes a lot of the potential applications of NLP/“AI” tools in GLAM.

Libraries and Learning Links of the Week is published every Monday by Hugh Rundle.

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