Michelle Ellefson

@michellefson.bsky.social

Professor of Cognitive Science @ University of Cambridge Faculty of Education Runs the INSTRUCT Lab (https://sites.google.com/site/instructlab/)

I was really happy with this piece - a tribute to the Great and Good John Flavell, a titan in the field who died this year. And also some semi-comic memories of the origins of Theory of Mind in the 80's and 90's. Open access. www.tandfonline.com/doi/full/10....

The Great and Good John Flavell

John Flavell had a unique combination of greatness and goodness. I outline his unique intellectual imagination and creativity, his ability to achieve theoretical insight through empirical brillianc...

tandfonline.com

after some in-depth discussions with my lab and also drawing on conversations on here, we've edited our new policy on AI usage in my lab feel free to adapt or re-use with attribution, or to reply to tell me how awful this policy is lol

New preprint! 🎉 I analysed 1660 papers from 4 psychology journals and found materials sharing went from 9% of papers in 2015 to 82% in 2025, and these materials *do* get downloaded — a median of 135 times each. BUT shared code is often hard to run. doi.org/10.31234/osf... Let's walk through it 🧵

Two-panel figure. Panel a is a flow diagram tracking 1,611 empirical psychology articles from publication year (545 in 2015, 552 in 2020, 514 in 2025) to repository-link type: 785 link an OSF project, 85 link another platform, and 741 link no repository. Of those with an OSF link, download counts were retrieved for 670 and not retrieved for 115. Panel b is a line chart of the share of empirical papers linking OSF across 2015, 2020 and 2025. The overall rate, shown as a dashed black line, rises from 9% to 57% to 82%. All four journals rise steeply and end close together: Psychological Science 92%, JESP 89%, JML 83%, Cognition 76%, with Psychological Science highest throughout.Three-panel figure. Panel a: ridgeline plot of downloads per file by material type on a log scale, with the percentage never downloaded labelled for each — archive 16% of 545 files, documents 20% of 2,970, code 12% of 3,471, other 17% of 1,646, data 21% of 10,051, media 35% of 2,120, images 35% of 4,102. Most files cluster between 1 and 10 downloads, with long right tails past 100. Panel b: ridgeline plot of downloads per paper by journal, log scale, with dashed median lines; Psychological Science is highest, then JESP, JML and Cognition. Panel c: stacked bars showing, for documents, data and code separately, the share of papers by download band (0, 1–10, 11–100, more than 100) in 2015, 2020 and 2025. The share exceeding 100 downloads falls sharply over time in all three types, from roughly two-thirds in 2015 to a quarter or less in 2025, as the 1–10 band grows.Four-panel figure. Panel a: statistical languages detected among 333 papers with retrievable code — R 88%, SPSS 12%, Stata 4%, SAS 1%. Panel b: code red flags among those 333 papers — 34% hard-code an absolute path, 40% reference a missing file — above documentation among 672 OSF-linked papers — 21% have a README, 30% are documented by README, description or wiki. Panel c: among 562 Elsevier papers with no repository link, 44% (245) host at least one journal supplementary file but only 14% (77) host data, code or an archive. Panel d: composition of those 448 hosted files — documents 52%, data 21%, media 9%, other 7%, archive 6%, code 3%, images 1%. The code panels are green, the journal-supplement panels blue.Coefficient plot (download predictors)

Dot-and-whisker plot of three standardised predictors of OSF download volume, each with a 95% confidence interval. Repository size (number of files) has the largest effect at about 0.76, citations about 0.38, and altmetric attention about 0.12. All three intervals sit entirely above zero, so each predicts more downloads, with repository size roughly twice the effect of citations and six times that of attention. X-axis: standardised effect, −0.2 to 1.0.

They do not tell you in grad school that success in academia is like one third good ideas, one third hard work, and one third relentless networking (the good kind—building authentic relationships, helping people, making connections for yourself and for others).

*Sharing for our department’s trainees* 🧠 Looking for insight on applying to PhD programs in psychology? ✨ Apply by Sep 21st to Stanford Psychology's 10th annual Paths to a Psychology PhD info session/workshop to have all of your questions answered! 📝 Application: forms.gle/4nujgDd3W2tx...

Paths to a Psychology Ph.D.: An Information Session and Workshop

Join Stanford Psychology graduate students, research assistants, and faculty for a free one-day virtual information session and workshop on applying to research positions and Ph.D. programs in psychol...

forms.gle

Neurons don't connect randomly. In this video by our #ElectronMicroscopy team, a blue neuron's axon forms a connection to a far neuron. Along the way, it links to some neighbors while skipping thousands. Connectomics seeks to understand what makes those connections special.

Since many are starting grad school soon, let me re-share my One Big Tip™️ for research! Research involves many skills - collaborating, writing, presenting, etc. But many of these skills can be unified under a single overarching ability: theory of mind Blog post link in reply

Illustration of the blog post's main argument, summarized as: "Theory of Mind as a Central Skill for Researchers: Research involves many skills.If each skill is viewed separately, each one takes a long time to learn. These skills can instead be connected via theory of mind – the ability to reason about the mental states of others. This allows you to transfer your abilities across areas, making it easier to gain new skills."