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Clintin Davis-Stober @clintin.bsky.social · 14/07/2026

Excellent paper on the ethical complexities of Open Science reform. Highly recommend. Builds upon our previous work on epistemic alignment in replication decision making. @suyoghc.bsky.social @balazsaczel.bsky.social @ayeletfishbach.bsky.social

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Journal of Mathematical Psychology @mathpsych.bsky.social · 24/06/2026

How does the brain tell correlation from causation across time? Niels Verosky shows one small tweak to a classic associative learning rule lets the same machinery behind temporal difference learning compute causal contingencies, not just co-occurrences.

sciencedirect.com

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Richard D. Morey @richarddmorey.bsky.social · 02/02/2026

New draft: "Decline effects, statistical artifacts, and a meta-analytic paradox". In this manuscript I show how a common practice in meta-analysis (eg the 2015 Open Science Collaboration) creates artifactual signatures of poor scientific behavior. PDF: raw.githubusercontent.com/richarddmore... 1/x

The decline effect (Protzko & Schooler, 2017) is an observed phenomenon where effect sizes in experiments apparently diminish in size from the first paper demonstrating the effect to later replications. This has been taken as a symptom of an unhealthy scientific ecosystem, possibly caused by the "winner's curse" (selection on significance and regression to the mean), publication bias or opportunistic analyses. I show that decline effects can arise as an artifact from a much simpler source: the original article determining the sign of the effect in a meta-analysis. Moreover, such artifactual decline effects will show correlations with some of the same experimental properties that one would expect from biases from poor behavior, such as the sample size of the original study.

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Richard D. Morey @richarddmorey.bsky.social · 25/09/2025

Simonsohn has now posted a blog response to our recent paper about the poor statistical properties of the P curve. @clintin.bsky.social and I are finishing up a less-technical paper that will serve as a response. But I wanted to address a meta-issue *around* this that may clarify some things. 1/x

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Berna Devezer @devezer.bsky.social · 14/08/2025

I love this post about science and metascience. A lot of quotables but I’ll lead with this: “Those seeking a scientific method – one that can be written down and followed mechanically […] – betray a kind of childish impatience with a process they clearly don’t understand.”

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Carl T. Bergstrom @carlbergstrom.com · 12/08/2025

1. "'Trusting the experts is not a feature of either a science or democracy," Kennedy said." It's literally a vital feature of both science and of representative democracy. I've written a fair bit about trust in expertise as a vital mechanism in the collective epistemology of science.

scrippsnews.com

RFK Jr. in interview with Scripps News: ‘Trusting the experts is not science’

HHS Secretary RFK Jr. sat down with Scripps News for a wide-ranging interview, discussing mRNA vaccine funding policy changes and a recent shooting at the Centers for Disease Control and Prevention.

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Berna Devezer @devezer.bsky.social · 10/08/2025

here was our call for methodological standards in metaresearch four years ago. instead of getting fixated on a particular inference we'd like to make, we need to maintain scientific standards, do the hard work, respect the evidence. we can't keep jumping at self-serving solutions without question.

share.google

The case for formal methodology in scientific reform | Royal Society Open Science

Current attempts at methodological reform in sciences come in response to an overall lack of rigor in methodological and scientific practices in experimental sciences. However, most methodological ref...

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Berna Devezer @devezer.bsky.social · 10/08/2025

some of the discussion around the p-curve paper is depressing. i still see many missing the point clearly stated in the conclusion, and instead of demanding strong standards or questioning whether they're even asking good questions, they've immediately started asking for replacement methods.

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Clintin Davis-Stober @clintin.bsky.social · 09/08/2025

New paper with @richarddmorey.bsky.social now out in JASA, where we critically examine p-curve. Below is Richard’s excellent summary of the many poor statistical properties of p-curve (with link to paper). I wanted to add some conceptual issues that we also tackle in the paper.

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Daniel Heck @danielheck.bsky.social · 12/06/2025

New paper by my PhD student @semihaktepe.bsky.social now published 🚀 "Revisiting the effect of discrepant perceptual fluency on truth judgments" tinyurl.com/2eepue5y --> Two experiments & a meta-analysis indicate that high visual contrast does not lead to higher truth judgments.

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Berna Devezer @devezer.bsky.social · 31/05/2025

wherein I'm quoted with "Science is essentially effective to the extent that it can remain independent, decentralized, and democratic." (gift link, email required)

wapo.st

Why Trump’s push for ‘gold-standard science’ has researchers alarmed

Many scientists fear the Trump administration’s new standard means putting political appointees in charge, which could undercut independent research.

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Daniel Heck @danielheck.bsky.social · 28/05/2025

🚀Postdoc position @unimarburg.bsky.social in the project: "Bridging the Gap Between Verbal Psychological Theories & Formal Statistical Modeling with Large Language Models" (funded by @volkswagenstiftung.de) 📅Start: 01.10.2025 | ⏳4 years 🔗 Apply now: uni-marburg.de/jhbCen 🔄 Thanks for sharing!

uni-marburg.de

Postdoc

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Iris van Rooij 💭 @irisvanrooij.bsky.social · 14/05/2025

NEW paper! 💭🖥️ “Combining Psychology with Artificial Intelligence: What could possibly go wrong?” — Brief review paper by @olivia.science & myself, highlighting traps to avoid when combining Psych with AI, and why this is so important. Check out our proposed way forward! 🌟💡 osf.io/preprints/ps...

Table 1
Typology of traps, how they can be avoided, and what goes wrong if not avoided. Note that all traps in a sense constitute category errors (Ryle & Tanney, 2009) and the success-to-truth inference (Guest & Martin, 2023) is an important driver in most, if not all, of the traps.

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Richard D. Morey @richarddmorey.bsky.social · 15/05/2025

If you'll be at APS2025 in DC next week, I'll be talking about the terrible statistical properties of the p curve procedure in the "Current Issues in Meta-Science" session Saturday, May 24th at 3pm. This will likely be my last US conference in a very long time. A brief summary follows. 1/

Screenshot of the APS program for "Current Issues in Meta-Science", Saturday, May 24, 3:00pm

Titles and authors in the session:

* Statistical Power in the Light of Methodological Reform (Jolynn Pek)

* The Poor Statistical Properties of the P-Curve Procedures (Richard Morey)

* Consistent Methods Protect Against False Findings Produced By p Hacking (Duane Wegener)

* Accumulating Evidence across Studies (Blakeley McShane)

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Daniel Heck @danielheck.bsky.social · 23/04/2025

I am looking forward to expanding the scope of my professorship by combining cognitive and statistical modeling with LLMs😊 There will be two job openings for postdoc positions soon - one starting in September 2025 and another one a year later.

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Berna Devezer @devezer.bsky.social · 21/04/2025

Another reminder that this online event will take place this Friday. I might be alone representing the West Coast (it's at 7am PT) but hope colleagues from other time zones consider stopping by and joining the discussion. My talk will be not-so-subtly titled "Replication Is (Not)".

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APA Journals @apajournals.bsky.social · 27/03/2025

Special Issue Spotlight: Decision research meets #AI. Read a short summary of the special issue from guest editors Ido Erev, Sudeep Bhatia, and @clintin.bsky.social bit.ly/3FkGX0N

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Iris van Rooij 💭 @irisvanrooij.bsky.social · 23/02/2025

Not being anti-fascist at this moment in history is anti-science. Probably always was. But cannot be clearer than these last few weeks.

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Katie Witkiewitz @katiew.bsky.social · 15/02/2025

A visualization I created to share with family and friends about how the NIH indirect rate costs will hurt science AND our economy.

To understand the devastation for U.S. science right now. Here is how NIH grants work:
somebody comes up with a research idea, like a tree sapling
NIH invests in the “direct cost” of that idea, aka buys the sapling
Let’s say that sapling is $100

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Joachim Vandekerckhove 🏖️ @joachim.cidlab.com · 06/02/2025

Since everyone is talking about research funding, this perspective by the vice-president of the European Research Council might be of interest. Blue states: Consider joining a multinational research council.

pnas.org

Alternative models of funding curiosity-driven research | PNAS

Funding of curiosity-driven science is the lifeblood of scientific and technological innovation. Various models of funding allocation became instit...

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Stephan Lewandowsky @lewan.uk · 06/02/2025

My latest column just appeared in Science, entitled "Free speech, fact-checking, and the right to accurate information”. (www.science.org/doi/10.1126/...) I use one of President Trump’s first executive orders to unpack the terrain between misinformation and claims to free speech 1/n

science.org

Free speech, fact checking, and the right to accurate information

True to his campaign promises, on 20 January 2025, US President Donald Trump signed a broad range of Executive Orders, the scope of which ranged from renaming the Gulf of Mexico to “Gulf of America” t...

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Ayelet Fishbach @ayeletfishbach.bsky.social · 03/02/2025

🚨 New Paper Alert! 🚨 How should scientists decide what to replicate & how? Our latest article explores: 🔍 Book of Truths vs. Book of Conversations – What's the purpose of replication? 📊 Balancing epistemic values, public trust & transparency. www.pnas.org/doi/10.1073/... @clintin.bsky.social

pnas.org

PNAS

Proceedings of the National Academy of Sciences (PNAS), a peer reviewed journal of the National Academy of Sciences (NAS) - an authoritative source of high-impact, original research that broadly spans...

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Rebecca Sear @rebeccasear.bsky.social · 30/01/2025

Dialogues about the practice of science "In this Feature: Should scientists reform the way they carry out research; if so, how? Should we reform the institutions that currently serve as scientific gatekeepers? How do recent technological & cultural revolutions affect the practice of science?"

pnas.org

PNAS

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Clintin Davis-Stober @clintin.bsky.social · 28/01/2025

Now out in PNAS, we provide a conceptual framework for assessing replication decisions and replication reform. Do you view the scientific literature as a "book of truths" or a "book of conversations"? www.pnas.org/doi/abs/10.1... #philsci #science #SciSci #Metascience

pnas.org

PNAS

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Ayelet Fishbach @ayeletfishbach.bsky.social · 28/01/2025

Which scientific results should be replicated? Our new PNAS suggests the decision depends on whether you subscribe to “the book of truth” or “book of conversation” @pnas.org @clintin.bsky.social

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Clintin Davis-Stober @clintin.bsky.social · 28/01/2025

pnas.org

PNAS

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Ed Merkle @edgarmerkle.bsky.social · 15/01/2025

New preprint with @winterstat.bsky.social and Ellen Fitzsimmons on ordinal factor analysis, where the latent variables are scaled so that they generally take values from 1 to # of ordered categories. The scaling is intuitive because it is what you use when you treat ordinal variables as continuous.

arxiv.org

Identification and Scaling of Latent Variables in Ordinal Factor Analysis

Social science researchers are generally accustomed to treating ordinal variables as though they are continuous. In this paper, we consider how identification constraints in ordinal factor analysis ca...

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Clintin Davis-Stober @clintin.bsky.social · 14/01/2025

I'm excited to announce that I am the new editor-in-chief of the Journal of Mathematical Psychology. Please send your best work investigating human behavior with formal approaches. Wish me luck!

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Iris van Rooij 💭 @irisvanrooij.bsky.social · 11/01/2025

🎬🎥🍿 Video of my keynote at MathPsych2024 now available online www.youtube.com/watch?v=WrwN... #CogSci #CriticalAI #AIhype #AGI #PsychSci #PhilSci 🧪

youtube.com

Iris van Rooij keynote at MathPsych/ICCM 2024

YouTube video by Society for Mathematical Psychology

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Berna Devezer @devezer.bsky.social · 09/01/2025

Simonsohn says prereg is only useful to distinguish btw exploratory & confirmatory analyses (a distinction we just wrote against) Gelman: "I disagree, partly bec I think that confirmatory and exploratory statistical analyses are the same thing, partly bec I very rarely care about p-values anyway"

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Berna Devezer @devezer.bsky.social · 07/01/2025

Alright it's here! Where we push back against the exploratory-confirmatory distinction that's become canonized in metascience and talk about what we think exploratory research (including exploratory experimentation and modeling) means and why our view is incompatible with 'unplanned data analyses'.

philsci-archive.pitt.edu

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Iris van Rooij 💭 @irisvanrooij.bsky.social · 04/01/2025

My 2 cents metatheorist.com/Is-the-Brain...

metatheorist.com

Is the brain (just) a computer?

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Berna Devezer @devezer.bsky.social · 03/01/2025

Just because I keep seeing the "replications show which effects are real" or "effects that didn't replicate once are flukes" heuristics repeatedly showing up on my TL today, I'm re-upping this thread. I beg everyone to please stop searching for quick and conclusive judgments on what's "true".

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Berna Devezer @devezer.bsky.social · 28/11/2024

what an odd score-keeping theater. what do these criteria even mean? and ultimately it all comes down to statistical significance again. largest sample sizes will win science! have we learned anything?

Abstract

We suggest four criteria for considering an effect to be well replicated: many supportive findings, preferably with multiple
methods and multiple labs, and few or no contrary significant findings; preregistered successful replications; significant findings
from multi-site replication; and real-world or non-laboratory findings. Ego depletion is the finding that after expending effort on
one self-control task, performance on other self-control and decision tasks is impaired. It does well by all four criteria. In particular,
only five findings have survived multi-site replication attempts in social psychology, and ego depletion is one of them. It has a
stronger record by the other criteria than the other four. Although possibly other criteria would yield a different conclusion, the case
for ego depletion as social psychology’s best replicated finding is quite strong.

Keywords: Self-control; Self-regulation; Ego Depletion; Replication

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Clintin Davis-Stober @clintin.bsky.social · 28/11/2024

Something interesting to read in between turkey and football

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Stefan Herzog @stefanherzog.bsky.social · 20/11/2024

🌟🤖📝 **Boosting human competences with interpretable and explainable artificial intelligence** How can AI *boost* human decision-making instead of replacing it? We talk about this in our new paper. doi.org/10.1037/dec0... #AI #XAI #InterpretableAI #IAI #boosting #competences 🧵👇

Article information

Title: Boosting human competences with interpretable and explainable artificial intelligence.

Full citation: Herzog, S. M., & Franklin, M. (2024). Boosting human competences with interpretable and explainable artificial intelligence. Decision, 11(4), 493–510. https://doi.org/10.1037/dec0000250

Abstract: Artificial intelligence (AI) is becoming integral to many areas of life, yet many—if not most—AI systems are opaque black boxes. This lack of transparency is a major source of concern, especially in high-stakes settings (e.g., medicine or criminal justice). The field of explainable AI (XAI) addresses this issue by explaining the decisions of opaque AI systems. However, such post hoc explanations are troubling because they cannot be faithful to what the original model computes—otherwise, there would be no need to use that black box model. A promising alternative is simple, inherently interpretable models (e.g., simple decision trees), which can match the performance of opaque AI systems. Because interpretable models represent—by design—faithful explanations of themselves, they empower informed decisions about whether to trust them. We connect research on XAI and inherently interpretable AI with that on behavioral science and boosts for competences. This perspective suggests that both interpretable AI and XAI could boost people’s competences to critically evaluate AI systems and their ability to make accurate judgments (e.g., medical diagnoses) in the absence of any AI support. Furthermore, we propose how to empirically assess whether and how AI support fosters such competences. Our theoretical analysis suggests that interpretable AI models are particularly promising and—because of XAI’s drawbacks—preferable. Finally, we argue that explaining large language models (LLMs) faces similar challenges as XAI for supervised machine learning and that the gist of our conjectures also holds for LLMs.

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Clintin Davis-Stober @clintin.bsky.social · 18/11/2024

Greetings my bluesky friends. I've been quiet for a while, but that is soon coming to an end. I've been getting recharged to post about science and all kinds of goodness.

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Mark Joseph Stern @mjsdc.bsky.social · 14/11/2024

To state the very obvious, this would put an avowed anti-vaxxer in charge of vaccines, allowing him to thwart the development and approval of life-saving shots. It's almost too horrific to fathom—a potential death sentence for our families and children. It's lethal. www.politico.com/news/2024/11...

politico.com

Trump expected to select Robert F. Kennedy Jr. to lead HHS

The choice will roil many public health experts after his years of touting debunked claims that vaccines cause autism.

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Berna Devezer @devezer.bsky.social · 14/11/2024

Finally our editorial for the "What makes a good theory?" special issue is out (co-edited with @irisvanrooij.bsky.social, @jcskewes.bsky.social, Sashank Varma, and Todd Wareham). It's an interdisciplinary issue and the contents are transdisciplinary. #philsci #metasci #cogsci #ai #psych 🧪

link.springer.com

What Makes a Good Theory? Interdisciplinary Perspectives - Computational Brain & Behavior

Computational Brain & Behavior -

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Joe Bak-Coleman @jbakcoleman.bsky.social · 12/11/2024

Metascience starter pack for the new folks! Interested in how science works? This is the pack for you! bsky.app/starter-pack...

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Iris van Rooij 💭 @irisvanrooij.bsky.social · 26/10/2024

What are your favourite women scientists in decision-making research and/or behavioral economics? Bonus points if their work is on decision-making under certainty.

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Katie Witkiewitz @katiew.bsky.social · 24/10/2024

Hey everyone, i created an addiction starter pack and I am sure I am missing folks - please send me a note to get added. go.bsky.app/KVDa5PD

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Jean Czerlinski Ortega @jeanimal.bsky.social · 20/10/2024

Double descent enables a chat bot with a billion parameters to perform well and not overfit. But how does double descent work? I use simulations fitting linear regressions, plots, and tables for solving systems of equations to build intuition. medium.com/@jeanimal/ho...

medium.com

How double descent breaks the shackles of the interpolation threshold

Insights for deep learning from solving N equations with N unknowns

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Berna Devezer @devezer.bsky.social · 16/10/2024

I was a reviewer on this exciting paper by @fedeadolfi.bsky.social & colleagues that just came out in our forthcoming special issue on scientific theories. Finding worthwhile scientific problems in a theoretical space is a largely neglected part of the scientific process and deserves more attention!

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