i find the framing as a crisis often counterproductive because I have experienced people rejecting that framing as it sounds more dramatic than people are willing to admit.

Post Doc at Uni Tübingen! 100% position for 3 (+3) years; they're looking for somebody to analyze large-scale longitudinal datasets in education research.

Expertise in machine learning is an advantage, commitment to research transparency desirable 😌 proficiency in German beneficial but not required

@manylanguagesc.bsky.social @academicmargin.bsky.social

We at ManyLanguages face a fascinating yet complex challenge: We try to scale up empirical efforts across cultures and languages. But how can we reach and incentivise participation of researchers from the Global South. We would love to hear your thoughts!

- How can we incentivise participation fairly and uniformly across populations with different resources and constraints?
- Are there models of partnership, training, or resource‑sharing that could help level the playing field?

This raises important questions:
- How do we meaningfully reach colleagues and communities in the Global South?
- What strategies have worked for building collaborations where institutional access is limited?

This month, we’re highlighting two interconnected #ManyLanguagesChallengeOfTheMonth challenges that sit at the heart of scaling ManyLanguages projects across diverse linguistic and cultural contexts.

This has been many years in the making. We wanted to do it right—not simply get it done.

Our goal was to contribute, however modestly, to an academia that genuinely strives for inclusivity.

May the AWoP—small as the step may be—help move academia toward greater inclusion. 🤝🫂🌈🍉🏳️‍⚧️✊⚖️♿🦮🌐

Me neither but I would like to work towards that goal. One obviously needs a well specified derivation chain to achieve that. Maybe I am delusional thinking that we will be able to define SESOIs for non-applied psych science in our life time, but I'd like to try.

That is a really nice example. Thanks for sharing, Anne.

I mean isn't the ACE effect removed from an application, too? and your SESOI in the paper is also not based on sth that matters? Do you think then that your ACE paper doesn't matter?Often the end goal is so far removed from the science that it is incredibly difficult to define it.

Yeah it's kind of a case of significant decimals right? Given the uncertainty in measuring the time (like when to stop the timer for a game), I guess ms might not be a useful indication. So it boils down to your measurement error example from above.

I kept telling myself, being in the nordic countries means being in rather stable democracies. The "rather" does a lot of heavy lifting these days.

Prior findings might be inflated outside of very well researched experimental findings. For most research, we need alternatives. In you example: "is probably very very small" I would love to hear your reasoning behind that statement. Is that based on prior effect magnitudes?

For example, even "just noticeable differences", which are indeed relevant concepts in speech perception, are problematic. JNDs are not absolute thresholds of perceptibility, they are merely arbitrary performance thresholds, usually whether you hear a contrast more than 75% of the time.

I am talking about the theoretical side of the field. Everything I see, including your own work, is heavily based on applied definitions. But many of us do basic cognitive sciences, where application is not in sight. Theoretically justifying a SESOI is probably not feasible yet for most.

i find it mind boggling that for the most commonly used measurement in cognitive psychology, we have no idea what we are looking at. Everybody just happy with "effect is not point zero"?

this is the first time I teach SESOIs in my advanced stats class. I really want my students to think about these things and find some support in the literature, but for the majority of measurements we care for, there is nothing. Great to hear you received funding to advance this blind spot!

and just to double check since you know the literature better than I do. Did you ever come across a theoretically derived SESOI for RT? It's such a common measurement, I can't imagine nobody has ever tried to define what a meaningful RT difference looks like. Anyone?

Thanks. I might miss something, but I cannot find a justification of the 3 different RT ranges that you report in the paper. Would you mind pointing me to more details about how you asked original authors about these ranges and possibly how they justify them.

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this made me laugh

@lakens.bsky.social did you ever come across SESOI definitions for reaction time measures that are neither based on prior effect sizes or arbitrary standardized effect size thresholds? I am looking for a psychologically/methodologically motivated SESOI for RTs.

I totally get how your motivation to be a good teacher is crushed over structural pressures in higher education. So many decisions are not in the best interest of the students in order to solve structural problems. Something needs to give I guess, but it does rob me of the 🔥 I felt when I started.

Very nice! or one of the ManyManys? ManyFarts?

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I think my dog has Tourette

if you try to estimate sample size for a bayesian version of these models through simulations, you don't think you run into practical problems? or what do you mean?

these models tend to be computationally very expensive and time consuming, which makes for example simulation-based sample size justifications much more difficult.

regardless of the psychological
nature of acceptability judgments, Likert and VAS scales require more complex mixture models because both tend to elicit many extreme responses at the end of the scales that might reflect a different (part of the) decision process and need to be modeled too!