TL;DR It’s annoying to be plagiarised, but what I’ve come to worry about more is how pay-to-publish predatory journals forgo peer review in order to prey on fellow academics and rob them of learning opportunities. Even if you know better than to publish in them, they are a symptom of the collective action problem that plagues much of academic publishing.

I serve on the advisory board of Language Science Press, a high quality open access publisher in linguistics. I alo co-edit a book series with the press. A recent query to the board concerned AI in submissions. I share my answer here because it may be useful beyond the LangSciPress community. Lightly edited to make more sense as a standalone post. I support the Press taking a clear stance in this matter. I think synthetic text (AI slop, i.e.

I recently came across a blog included in Rogue Scholar that was producing a barrage of posts along the lines of “Animals that start with [letter]”. They included the inspiring “Animals that start with P”, the highly original “Animals that start with H” and of course the intriguing “Animals that start with M”. Here is the introduction to that one: Any opening like this sets off my LLM alarm bells.

Oxford University Press is going full surveillance capitalist mode. They don’t do author offprints anymore because authors sharing their work equals “piracy”; want nothing more dearly than tracking their users’ every move; and would rather you didn’t even email your work to students and colleagues. God forbid anyone actually read your publicly funded scholarly work.

I saw a thing fly by on PsyArxiv and must write about it. Warning: snark detected. This is a new paper by Green, Kong, Brysbaert, and Keogh with the following abstract: “This paper revisits the Age of Acquisition (AoA) norms of Kuperman et al. (2012). Three studies were conducted.

Academic home pages are a special genre. Publication lists are a key part of it: our published scholarly work pretty much defines us (at least as far as our academic persona is concerned). I think every academic should have a full publication list somewhere —why do some universities make this so hard?— but home pages often just have a list of selected papers. How do people make this selection?

Knots are fascinating: they tie together topology, embodied experience, and material culture. As Thai textile artist and designer Nithikul Nimkulrath (2024) has pointed out, knots are the kind of thing we come to know “ through and in making”. One of her artworks (see photo) explorers the materiality of knots by translating a physical, hand-knotted container into a 3D render.

Like anyone active in the space of LLMs and generative AI, I get a growing amount of invitations to speak at conferences and colloquia on something or other LLM-related. A subset of these invites is about the relation between LLMs and academic writing. Recently I had the occasion to respond to such an invite.

I have been blogging at The Ideophone since 2007, and not all of it has been as ephemeral as my PhD promotor once feared. My short post documenting the etymology of Zotero is apparently the only scientific documentation of where Zotero’s name comes from; it has served as a source in Wikipedia for ages and has received over 15 scholarly citations.

Language makes us human. But there is an interesting asymmetry in our willingness to ascribe linguistic capacities to non-humans: animals are seen as having none, whereas computers may well master it according to many. What curious conception of language makes this asymmetry possible? And what do Descartes and Turing have to do with it? Notes from a new essay about language between animals and computers.

Interjections are, in Felix Ameka’s memorable formulation, “the universal yet neglected part of speech” (1992). They are rarely the subject of historical, typological or comparative research in linguistics, and as Aimée Lahaussois has shown (2016), they are notably underrepresented in descriptive grammars. As grammars are the main source of data for typologists, this is of course a perfect example of a self-reinforcing feedback loop.