Submit to the Theory Methods Conference by June 18! Even if you are not an expert in theory methods, submit to get some great feedback and connect with kindred spirits. Submit your proposal: edu.nl/mj9x6
For an overview of the conference program and keynotes: theorymethodssociety.org/conference.h...
Shape the future of social science as a PhD student of machine learning-informed theory construction, based on patterns in high-frequency longitudinal data! You will be part of vibrant communities like the INSIGHT Lab, Theory Methods Society, and Tilburg Experience Sampling Center
tiu.nu/23721
Working in modern academia means spending 75% of your time being lectured by admins about not following minutia details of 100+ page handbooks (often now LLM-written) and making endless formatting tweaks to documents you need approved for the work you’re supposed to spend 100% of your time doing.
EU scholars should be digitally autonomous, free from unreliable US big tech. In this article I discuss what YOU can do, which lessons the COVID-19 crisis teaches us, and how we can build on the most recent successful culture change in academia (open science) www.scienceguide.nl/2026/03/digi...
💠Come work with me, Mark Hoogendoorn, and Dimitris Rizopoulos! We are offering a 3 year PostDoc to do research on the intersection of machine learning (ML) and statistics. 🔢 💫 You will be part of the Stress in Action consortium: stress-in-action.nl/science-of-s...
Vacancy: lnkd.in/ewN5T6AA
Thanks for the question! It's a format, not reporting guideline, so it's only meant to guide the structure of the paper. We wrote it with different kinds of theories in mind, do you think any non-optional sections are incompatible with descriptive theories?
The "Theory Paper Format" is a template for writing psychological theory papers, developed by the Taskforce Theoretical Psychology (Lorentz Workshop, 2025). Use it to structure your theoretical paper, or (for editors) consider creating journal space for theory papers doi.org/10.17605/OSF...
Excellent article, @syeducation.bsky.social ! My 2¢ is that *generative* AI has no place in qualitative coding because coding does not require generating context-relevant text/extrapolating. It requires summarizing, labeling, and interpolation. Non-gen embedding models are probably more useful.
New post! "Valuing the Process vs. the Product in Research," in which I try to describe some of the tensions around using GenAI/LLMs in scientific research, and why it can be so difficult to have productive conversations on the topic. getsyeducated.substack.com/p/valuing-th...
Does your R-script work on your computer? Want to make it fully reproducible on ANY system, now and in the future? In this video, I demonstrate how to turn R scripts into reproducible, version-controlled projects with worcs, renv, targets, and testthat to verify reproducibility. youtu.be/3mgRFMr5APU
Yes! Assumptions in models are one place where theory often (implicitly) pops up, I'd be very curious to hear your thoughts about it.
Call for Submissions for the Theory Methods Conference 2026, September 30-October 2! theorymethodssociety.org/conference.h...
We invite you to:
1) Submit your proposal: edu.nl/mj9x6
2) Invite your colleagues/lab/(PhD) students, and encourage them to submit
3) Share this post
Are you open science-minded, technically savvy, and interested in mixed methods? Come build the future of mixed methods with Tamarinde Haven and @mariestadel.bsky.social. Our campus is green, our colleagues supportive, and our research excellent!
www.academictransfer.com/en/jobs/3583...
Everyone’s talking about the "theory crisis" - but do we fix it with formal- or agent-based models, DAGs, propositions? Regardless: we need a shared medium to exchange and improve ideas. That medium is FAIR theory: Findable, Accessible, Interoperable, Reusable doi.org/10.1177/1745...
Excellent! Do your round tables also touch on digital autonomy from US tech giants?
Open source software is powerful, but only if people know how to use it. After publishing 12 R packages, I'm shifting toward open educational materials with monthly deep-dive videos on data science in R. First up: mixed data (continuous/categorical) Latent Class Analysis with tidySEM! What's next?
Over christmas, I added tidySEM much-requested support for mixed-data latent class analysis (continuous/categorical)! This was technically possible, but the new implementation is easier, faster, with better convergence! Try it by running remotes::install_github("cjvanlissa/tidySEM"); ?mx_mixed_lca
Fantastic projects awarded, including two I'm part of: Hannes Datta's "ReproHub", which integrates reproducibility/checks into research infrastructure, and Terrence Jorgensen's "Infra-Structural Equation Modelling", which develops lavaan and related open educational material! Congratulations to all!
🟥 Ik staak tegen bezuinigingen op het hoger onderwijs. Investeren in de kenniseconomie is noodzakelijk om wereldwijde uitdagingen van klimaat, ongelijkheid, gezondheid, veiligheid, ea het hoofd te bieden. We roepen de overheid op: kies een andere koers.
Meer informatie: www.fnv.nl/ho
The Paul Meehl Graduate school provides FREE education for PhD students in Europe, especially in metascience and methodology paulmeehlschool.github.io Today is the kick-off of their annual conference!
"Preprints are read, shared, and cited — yet dismissed as incomplete until blessed by a publisher. [...] the true measure of scholarship lies in open exchange, not in the industry’s gatekeeping labels of what counts as published.
Against publishing - Univers magazine share.google/LSk8PkEKeRSb...
Yes, please! I'm fluent :)
Is anyone willing to share their slides on philosophy of science for undergraduate (statistics) students, especially as it pertains to the hypothetico-deductive framework? Here are my current notes on the topic: lnkd.in/eB-TZGDK
Any experiences with "Journal of Computational Social Science"? I reviewed a manuscript that should have been desk-rejected (grammatically incorrect, not embedded in relevant literature, ad-hoc and nonsensical analysis decisions); the decision was "minor revision" based on ONLY my review. How!?
Abstract: Under the banner of progress, products have been uncritically adopted or even imposed on users — in past centuries with tobacco and combustion engines, and in the 21st with social media. For these collective blunders, we now regret our involvement or apathy as scientists, and society struggles to put the genie back in the bottle. Currently, we are similarly entangled with artificial intelligence (AI) technology. For example, software updates are rolled out seamlessly and non-consensually, Microsoft Office is bundled with chatbots, and we, our students, and our employers have had no say, as it is not considered a valid position to reject AI technologies in our teaching and research. This is why in June 2025, we co-authored an Open Letter calling on our employers to reverse and rethink their stance on uncritically adopting AI technologies. In this position piece, we expound on why universities must take their role seriously toa) counter the technology industry’s marketing, hype, and harm; and to b) safeguard higher education, critical thinking, expertise, academic freedom, and scientific integrity. We include pointers to relevant work to further inform our colleagues.
Figure 1. A cartoon set theoretic view on various terms (see Table 1) used when discussing the superset AI (black outline, hatched background): LLMs are in orange; ANNs are in magenta; generative models are in blue; and finally, chatbots are in green. Where these intersect, the colours reflect that, e.g. generative adversarial network (GAN) and Boltzmann machine (BM) models are in the purple subset because they are both generative and ANNs. In the case of proprietary closed source models, e.g. OpenAI’s ChatGPT and Apple’s Siri, we cannot verify their implementation and so academics can only make educated guesses (cf. Dingemanse 2025). Undefined terms used above: BERT (Devlin et al. 2019); AlexNet (Krizhevsky et al. 2017); A.L.I.C.E. (Wallace 2009); ELIZA (Weizenbaum 1966); Jabberwacky (Twist 2003); linear discriminant analysis (LDA); quadratic discriminant analysis (QDA).
Table 1. Below some of the typical terminological disarray is untangled. Importantly, none of these terms are orthogonal nor do they exclusively pick out the types of products we may wish to critique or proscribe.
Protecting the Ecosystem of Human Knowledge: Five Principles
Finally! 🤩 Our position piece: Against the Uncritical Adoption of 'AI' Technologies in Academia:
doi.org/10.5281/zeno...
We unpick the tech industry’s marketing, hype, & harm; and we argue for safeguarding higher education, critical
thinking, expertise, academic freedom, & scientific integrity.
1/n
I was reminded today of the heroic work done by @eikofried.bsky.social and
@robinnkok.bsky.social to see what information Elsevier collects on academics and was re-horrified. 🧵 (1/5)
eiko-fried.com/welcome-to-h...
#academicsky
Day 2 Keynotes kicked off with Laura Nelson's inspiring presentation, “Why Qualitative Research Needs Computational Social Science”. What is the state of this maturing field called qualitative computational methods? What are the ongoing debates and futures? #ic2s2
Loving @ic2s2.bsky.social , but I wonder if we're asking the right questions. Is "How can I outsource this task to a proprietary, black box, resource-intensive, often un-validated LLM?" when fit-for-purpose classifiers abound a computational a computational research question? Or even scientific?