I don't get why this is a big deal. Why can't we have exploratory results, clearly labeled and separate from registered results, and treated accordingly?

Thinking about how this might go Listener: My chains aren't converging Andrew: Your model is bad Aki: Your parameterization is bad Richard: The Buddha teaches us that numerical integration is suffering

Happy to share my conversation with Alexander Gibson about unreliable datasets and why they're so damaging to science! youtu.be/blNIZKYKo_Q Alex's work was recently covered at Nature: www.nature.com/articles/d41...

Registered Reports improve the credibility of scientific claims by rewarding big questions, sound methods and solid analyses. They need to become a standard tool in research. go.nature.com/4dP1rwk

What's wrong with peer review? We are obsessed with "narrative", replacing the science with the story. Devaluing the paper in favor of a researcher’s contribution is the first step to fixing this. #science #research #stem #metascience #ethics

Why AI for Science Will Never Work Training AI on scientific literature is a "Garbage In, Garbage Out" trap of 1) false positive data, and 2) lack of null data. Firms are spending millions to redo experiments because they don't trust the literature. #AI #MachineLearning #Science #Research #STEM

“The United Kingdom should establish a committee to monitor efforts by the nation’s universities to properly conduct misconduct investigations, a parliamentary inquiry recommends.” Removing incentives for positive data >> better policing of research misconduct The latter is the War on Drugs model.

How to Fix Peer Review Open data, predicting replicability, checking antibody validation, and not treating peer review as a simple binary are among the new initiatives at @cos.io and their new platform, LifeCycle Journal. #science #biology #stem #research #publishing

Why are drug costs so high? Part of the reason is low replicability rates in preclinical research. Tim Errington breaks down the "clinical vs. preclinical" divide and where different types of institutions fit in the translational ecosystem. #Metascience #Innovation #Academia #DrugDiscovery

Science Has Too Many Pet Theories, Not Enough Falsification Science rewards positive findings, but how do we decide what not to keep pursuing? “Fail faster” research models may make science more reliable. #ReplicationCrisis #Falsification #OpenScience #ScientificMethod #MetaScience

The "magical" science scam Why do scientists always get the results reviewers want? The Center for Open Science is introducing Registered Reports at the revision stage to bring transparency to peer review #science #research #stem #ethics #registeredreports

Part 2. Registered reports remove the incentive for positive data (the original sin of science). Publication is conditional on following peer-reviewed methodology, not having "novel" results or p<0.05. This is Part 2, check out Part 1 if you missed it. #science #research #stem #ethics #podcast

Registered reports remove the incentive for positive data (the original sin of science). Publication is conditional on following peer-reviewed methodology, not having "novel" results or p<0.05. This is Part 1 of this clip, stay tuned for Part 2. #science #research #stem #ethics #podcast

Why Science is like The War On Drugs Positive data -> Papers -> Grants Scolding one bad apple won't fix a system that rewards noise over truth. We can’t just attack individual fraud; we have to enable a global change in how science is practiced. #science #research #stem #ethics

This is what happens when the primary goal is the individual one of making a career instead of the societal one of discovering the scientific truth.

Yeah, I think people know data fabrication is fraud. But selective reporting to make the effect size seem larger is not seen as fraud, even though it has a terrible effect on science.

it’s all about sins of omission seeming OK, whereas sins of commission seem more culpable

People justify selective reporting like this by saying (1) they need to support early career researchers, and/or (2) they don't want to have to cut staff. But the harm from bad science--especially when it becomes the norm--is larger than than impact on one lab.

Apart from careerism, I think that part of the story here is our core scientific dogma that big robust phenomena exist and it’s our job to uncover them. Once you’ve bought into that it’s not too difficult to start selecting the data that show the sought-for effect in the cleanest way

The normative fraud that Errington describes is something I've seen my whole career. A biologist once told me, if p is very small, it can't be a false positive. Teams condition on null being false, see anything that makes p small as truth-seeking. These traditions spread bc they get you published.

A wise man once likened science to a chicken coop youtu.be/d8LqFO1dk-w?...

SHOCKING stories of data fabrication Tim Errington shares a never-before-told story of data fabrication in cancer biology. Scientists go to extreme measures, even engaging in data fabrication, to secure a publication in prestigious journals. #science #truth #medicine #stem #shorts

The need for positive data is the original sin of science. To exist in science, you need grants. To get grants, you need to publish papers. To publish papers, you need positive data. This leads to null data staying in file drawers, and false or misleading positive data being published.

For many Iranian students, Neuromatch was one of the few bridges to the international neuroscience community. Iranian students and TAs have contributed so much to it. Many of us, including me, found neuroscience through Neuromatch. This decision by Trump’s gov is cruel, unjust and a loss for science

Neuroscience is a global endeavor whose main promise is curing the many brain related diseases. Global collaboration is the key to that. I am so sad that our Iranian friends will, once again, be excluded.

Here’s my conversation with Charles Piller, investigative correspondent at Science, and author of Doctored. We discussed his reporting, reactions from the field, his process working with a team of sleuths, and his opposition to the Trump administration’s attacks on science.

More details about the Bayesian Workflow book and case studies now available on the book web site avehtari.github.io/Bayesian-Wor... (but you still need to wait a bit for the book)

It was great fun to chat with Randy about metascience and replicability. Check out his podcast!

Here are my conversations with @briannosek.bsky.social and Tim Errington on Metascience Matters Brian: www.youtube.com/watch?v=4DCV... Tim: www.youtube.com/watch?v=-EDA... We discussed their replication projects in psychology and cancer biology, the Center for Open Science, and many other topics.

If you’re in the Boston area, please join me on April 16 for my talk about the tragedy of fraudulent or false Alzheimer’s research – and the response to my book “Doctored.” Talk and reception sponsored by MIT Knight Science Journalism. ksj.mit.edu/event/lectur...

7/ The policy impact is striking: reproducibility rises from 29.6% before Data Access and Research Transpareny (DA-RT) to 79.8% after.

Update from the Metascience Alliance: A synthesis of input gathered so far is now available. It reflects back what’s been heard and highlights five emerging themes to guide next steps. 📝 Read the synthesis: www.cos.io/hubfs/Met... 💡 Learn how to get involved: cos.io/metascience-a...

>5h recordings and slides for most #LoveReplicationsWeek talks are now available on our updated website. Thank you so much everybody who contributed to this wonderful week, participated in the talks, and partnered-up with us. I think there should be a replication of this. forrt.org/LoveReplicat...

Statistical Rethinking 2026 is done: 20 new lectures emphasizing logical and critical statistical workflow, from basics of probability theory to causal inference to reliable computation to sensitivity. It's all free, made just for you. Lecture list and links: github.com/rmcelreath/s...

Hidden Markov Models - Lecture B10 of Stat Rethinking 2026. Hidden state models, inference of latent strategies, time series, is the president dead?, capture-recapture and demographic inference, Guerilla Bayesian Workflow. This is the final lecture for 2026. www.youtube.com/watch?v=fuon...

My favorite is this kind of convo that turns into a neverending journey! Scientists in the Boston area interested in preventing mistakes from escalating into egregious fraud cases, please join our Meetup 7pm Sunday night at the Lavender room in Somerville Armory.

Here's my conversation with @eugenie-reich.bsky.social, an attorney representing scientific whistleblowers, on Metascience Matters: www.youtube.com/watch?v=SMRC... We discuss her cases, the False Claims Act, whistleblower awards, pressures on scientists to produce positive data, among other topics.

Working hypothesis: If you're doing research and don't occasionally have a small existential crisis, either you've been blessed to work in an exceptional field (do tell which one it is!), or maybe you're being a bit naive.

Happy to announce that the RR for ManyNumbers 3 was accepted (in principle) at Developmental Science today. This project will investigate the socio-demographic correlates of preschool numeracy in US sites participating in ManyNumbers 1. If you're interested, it's not too late to join these projects.

Here's my conversation with @jamesheathers.bsky.social, Founder/Director of the Medical Evidence Project, on Metascience Matters: www.youtube.com/watch?v=QH87... We discussed his book on Forensic Metascience, the story behind the GRIM test, how technology can enable metascience, and other topics.

Replication Research (R2), a 🆕 community-led Diamond OA journal, makes replication studies more discoverable, publishable & rigorously evaluated—without subscription barriers or author fees. Ahead of #LoveReplicationsWeek, R2's senior editors shared their vision in our Q&A:

Wonderful to see this replication effort in the physical sciences using the models of many labs, preregistration, and transparency that have benefitted other fields. And, an investment of $9.5 million to do it! www.nature.com/articles/d41...

Here's what a Cohen's d = 22 looks like. Totally normal. See it all the time in my own data...

Today in that-didn't-happen: Cohen's d = 22. Williams et al. (2014) has 145 citations, putting it in top 1% of most cited psych articles. It is a load-bearing publication in its area, despite having impossible results. pubpeer.com/publications...

I have a new paper. We look at ~all stats articles in political science post-2010 & show that 94% have abstracts that claim to reject a null. Only 2% present only null results. This is hard to explain unless the research process has a filter that only lets rejections through.

Without publication bias, we might not need many replications. With publication bias, 20% to 40% might be justified (but of course, extremely dependent on the assumptions in the simulations!). If the field is a mess, we need a lot of replication studies to clean up!

My colleague Krist Vaessen wrote a new book: “Neomania: How our obsession with innovation is failing science, and how to restore trust”. It's a great analysis how the drive for novelty hinders reliable scientific progress. Open Access, so read it here: books.openbookpublishers.com/10.11647/obp...

Here's my conversation with Mu Yang on Metascience Matters: www.youtube.com/watch?v=E2EK... We discussed her work as a scientific sleuth, academic incentives for positive data, individual cases she has pursued, and why she loves being a sleuth. Also on Spotify: open.spotify.com/episode/16R6...

New submission format at SBE: “Replications as Registered Reports” link.springer.com/journal/1118... You can get "in-principle acceptance" before data collection even begins; final paper gets published regardless the results, if the study is conducted rigorously. #EconSky

Call for metascience grants has a focus on three areas: 🔸️ The impact of artificial intelligence on scientific practice and the research landscape 🔸️ The effective design and leadership of research organisations 🔸️ Scientometrics approaches to understanding research excellence, efficiency and equity