Women & Tolkien: Amazons, Valkyries, Feminists, and Slashers

This paper reports on an early pilot project that asks women who self identify as readers or fans of Tolkien\u27s work and/or teachers who have taught Tolkien\u27s work, and/or scholars who have published on Tolkien\u27s work to answer a few open-ended questions about their reasons for enjoying his work. By women, I mean anybody who identifies as a woman. By Tolkien\u27s work, I mean any of his published novels, stories, poems, or academic essays. The study arises from the question that is often asked of fans of Tolkien\u27s work: why do women so enjoy it, given the relatively minor narrative roles women play

When One Job Is Not Enough

More than 8–1/2 million workers held two or more jobs in May 1997. Four out of every ten did so to meet regular household expenses or to pay off debts. Other common reasons for working more than one job included enjoying the work on the second job (14.5 percent), wanting to save for the future (8.7 percent), wanting to get experience or build up a business (7.7 percent), and wanting some extra money to buy something special (7.9 percent). These results were quite similar to those that were obtained in May 1991, the last time that data on the reasons for working more than one job were collected

Cold Fusion: Training Seq2Seq Models Together with Language Models

Sequence-to-sequence (Seq2Seq) models with attention have excelled at tasks which involve generating natural language sentences such as machine translation, image captioning and speech recognition. Performance has further been improved by leveraging unlabeled data, often in the form of a language model. In this work, we present the Cold Fusion method, which leverages a pre-trained language model during training, and show its effectiveness on the speech recognition task. We show that Seq2Seq models with Cold Fusion are able to better utilize language information enjoying i) faster convergence and better generalization, and ii) almost complete transfer to a new domain while using less than 10% of the labeled training data

Monthly Talking Points, July 2023

Now that July is here, it’s important to streamline processes at work to allow time for enjoying our short and spectacular Maine summer

On the Web-WorldCat, Digital Publications, and New Editions

I hope everyone is doing well and enjoying the warmer weather! Despite the real arrival of spring and sun, the Reference Desk is expecting a huge pick-up in the library and in citation and research questions as we move towards the end of the semester and the due dates for final research papers. Apart from regular work at the Desk, I am still working on the Collection Development Project, now in the online section of the project. I’ve been working a lot with MUSCAT and WorldCat, trying to discover how many copies of the Parkin books are available in other libraries and to see how rare each book is. Some of the books could only be found in ten or so other libraries worldwide! [excerpt