#metascience — Public Fediverse posts
Live and recent posts from across the Fediverse tagged #metascience, aggregated by home.social.
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1/ If you're following the debacle on the Democratic National Committee autopsy on the 2024 election, here's my #metascience take on the problem.
Why Kamala Harris lost in 2024 is an empirical question. It's a complicated empirical question with dozens, hundreds, or thousands of relevant factors. It's made even more complicated by the presence of background preferences and wishful thinking.
If we're not careful, it's a tangled mix of descriptive empirical questions (why did some previous Dem voters shift to the right) and normative questions (what should we do next time to prevent that). Here I'll bracket the normative questions and focus on the empirical ones.
When scientists address complicated empirical questions, we don't expect one researcher or team to identify all the relevant factors in one publication. We don't even expect the entire field to identify all relevant factors in one generation. We expect incremental advances. We expect many researchers to identify many factors over time, tussle over the empirical evidence for and against them, give different factors different weights, differ on which factors are most salient, and differ in how to take the most salient factors into account. And we do all that in public.
#Democrats #DNC #Metaresearch #USPol #USPolitics
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1/ If you're following the debacle on the Democratic National Committee autopsy on the 2024 election, here's my #metascience take on the problem.
Why Kamala Harris lost in 2024 is an empirical question. It's a complicated empirical question with dozens, hundreds, or thousands of relevant factors. It's made even more complicated by the presence of background preferences and wishful thinking.
If we're not careful, it's a tangled mix of descriptive empirical questions (why did some previous Dem voters shift to the right) and normative questions (what should we do next time to prevent that). Here I'll bracket the normative questions and focus on the empirical ones.
When scientists address complicated empirical questions, we don't expect one researcher or team to identify all the relevant factors in one publication. We don't even expect the entire field to identify all relevant factors in one generation. We expect incremental advances. We expect many researchers to identify many factors over time, tussle over the empirical evidence for and against them, give different factors different weights, differ on which factors are most salient, and differ in how to take the most salient factors into account. And we do all that in public.
#Democrats #DNC #Metaresearch #USPol #USPolitics
🧵
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1/ If you're following the debacle on the Democratic National Committee autopsy on the 2024 election, here's my #metascience take on the problem.
Why Kamala Harris lost in 2024 is an empirical question. It's a complicated empirical question with dozens, hundreds, or thousands of relevant factors. It's made even more complicated by the presence of background preferences and wishful thinking.
If we're not careful, it's a tangled mix of descriptive empirical questions (why did some previous Dem voters shift to the right) and normative questions (what should we do next time to prevent that). Here I'll bracket the normative questions and focus on the empirical ones.
When scientists address complicated empirical questions, we don't expect one researcher or team to identify all the relevant factors in one publication. We don't even expect the entire field to identify all relevant factors in one generation. We expect incremental advances. We expect many researchers to identify many factors over time, tussle over the empirical evidence for and against them, give different factors different weights, differ on which factors are most salient, and differ in how to take the most salient factors into account. And we do all that in public.
#Democrats #DNC #Metaresearch #USPol #USPolitics
🧵
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1/ If you're following the debacle on the Democratic National Committee autopsy on the 2024 election, here's my #metascience take on the problem.
Why Kamala Harris lost in 2024 is an empirical question. It's a complicated empirical question with dozens, hundreds, or thousands of relevant factors. It's made even more complicated by the presence of background preferences and wishful thinking.
If we're not careful, it's a tangled mix of descriptive empirical questions (why did some previous Dem voters shift to the right) and normative questions (what should we do next time to prevent that). Here I'll bracket the normative questions and focus on the empirical ones.
When scientists address complicated empirical questions, we don't expect one researcher or team to identify all the relevant factors in one publication. We don't even expect the entire field to identify all relevant factors in one generation. We expect incremental advances. We expect many researchers to identify many factors over time, tussle over the empirical evidence for and against them, give different factors different weights, differ on which factors are most salient, and differ in how to take the most salient factors into account. And we do all that in public.
#Democrats #DNC #Metaresearch #USPol #USPolitics
🧵
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1/ If you're following the debacle on the Democratic National Committee autopsy on the 2024 election, here's my #metascience take on the problem.
Why Kamala Harris lost in 2024 is an empirical question. It's a complicated empirical question with dozens, hundreds, or thousands of relevant factors. It's made even more complicated by the presence of background preferences and wishful thinking.
If we're not careful, it's a tangled mix of descriptive empirical questions (why did some previous Dem voters shift to the right) and normative questions (what should we do next time to prevent that). Here I'll bracket the normative questions and focus on the empirical ones.
When scientists address complicated empirical questions, we don't expect one researcher or team to identify all the relevant factors in one publication. We don't even expect the entire field to identify all relevant factors in one generation. We expect incremental advances. We expect many researchers to identify many factors over time, tussle over the empirical evidence for and against them, give different factors different weights, differ on which factors are most salient, and differ in how to take the most salient factors into account. And we do all that in public.
#Democrats #DNC #Metaresearch #USPol #USPolitics
🧵
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Feminist Metascience, Risk-Averse Peer Review, & Can Systems Change Theory Strengthen Metascience?
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Feminist Metascience, Risk-Averse Peer Review, & Can Systems Change Theory Strengthen Metascience?
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Feminist Metascience, Risk-Averse Peer Review, & Can Systems Change Theory Strengthen Metascience?
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Feminist Metascience, Risk-Averse Peer Review, & Can Systems Change Theory Strengthen Metascience?
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Feminist Metascience, Risk-Averse Peer Review, & Can Systems Change Theory Strengthen Metascience?
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New preprint: "A Framework for Reproducible AI-Assisted Research in the Social and Behavioral Sciences"
https://osf.io/preprints/psyarxiv/xdtqh_v1
#reproducibility #metascience #openscience -
New preprint: "A Framework for Reproducible AI-Assisted Research in the Social and Behavioral Sciences"
https://osf.io/preprints/psyarxiv/xdtqh_v1
#reproducibility #metascience #openscience -
New preprint: "A Framework for Reproducible AI-Assisted Research in the Social and Behavioral Sciences"
https://osf.io/preprints/psyarxiv/xdtqh_v1
#reproducibility #metascience #openscience -
New preprint: "A Framework for Reproducible AI-Assisted Research in the Social and Behavioral Sciences"
https://osf.io/preprints/psyarxiv/xdtqh_v1
#reproducibility #metascience #openscience -
New preprint: "A Framework for Reproducible AI-Assisted Research in the Social and Behavioral Sciences"
https://osf.io/preprints/psyarxiv/xdtqh_v1
#reproducibility #metascience #openscience -
#ScholComm and #metascience folks beware that there's now a second #FAIR acronym. The first was Findability, Accessibility, Interoperability, and Reusability. The new one is Fairness, Accountability, Integrity, and Responsibility. It's an "ethically-guided hybrid #peerreview system" mixing #AI and human expertise.
https://www.degruyterbrill.com/document/doi/10.1515/jpm-2025-0285/html -
#ScholComm and #metascience folks beware that there's now a second #FAIR acronym. The first was Findability, Accessibility, Interoperability, and Reusability. The new one is Fairness, Accountability, Integrity, and Responsibility. It's an "ethically-guided hybrid #peerreview system" mixing #AI and human expertise.
https://www.degruyterbrill.com/document/doi/10.1515/jpm-2025-0285/html -
#ScholComm and #metascience folks beware that there's now a second #FAIR acronym. The first was Findability, Accessibility, Interoperability, and Reusability. The new one is Fairness, Accountability, Integrity, and Responsibility. It's an "ethically-guided hybrid #peerreview system" mixing #AI and human expertise.
https://www.degruyterbrill.com/document/doi/10.1515/jpm-2025-0285/html -
#ScholComm and #metascience folks beware that there's now a second #FAIR acronym. The first was Findability, Accessibility, Interoperability, and Reusability. The new one is Fairness, Accountability, Integrity, and Responsibility. It's an "ethically-guided hybrid #peerreview system" mixing #AI and human expertise.
https://www.degruyterbrill.com/document/doi/10.1515/jpm-2025-0285/html -
#ScholComm and #metascience folks beware that there's now a second #FAIR acronym. The first was Findability, Accessibility, Interoperability, and Reusability. The new one is Fairness, Accountability, Integrity, and Responsibility. It's an "ethically-guided hybrid #peerreview system" mixing #AI and human expertise.
https://www.degruyterbrill.com/document/doi/10.1515/jpm-2025-0285/html -
Some recent #metascience work and news…
• Average replicability rates
• Theories don’t die!
• Is the replication crisis overblown?
• Postdoctoral Fellowships
• Partial replications
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Some recent #metascience work and news…
• Average replicability rates
• Theories don’t die!
• Is the replication crisis overblown?
• Postdoctoral Fellowships
• Partial replications
-
Some recent #metascience work and news…
• Average replicability rates
• Theories don’t die!
• Is the replication crisis overblown?
• Postdoctoral Fellowships
• Partial replications
-
Some recent #metascience work and news…
• Average replicability rates
• Theories don’t die!
• Is the replication crisis overblown?
• Postdoctoral Fellowships
• Partial replications
-
Some recent #metascience work and news…
• Average replicability rates
• Theories don’t die!
• Is the replication crisis overblown?
• Postdoctoral Fellowships
• Partial replications
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and if any one is wrong we can accept it.
In contrast, some big clinical trials maximize rigor at high cost.
A great science ecosystem has a mix of different approaches.
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How can research findings be made more durable over time?
A Nature analysis highlights key strategies to improve reproducibility, replicability, and robustness across the social and behavioural sciences.
🔗 https://www.nature.com/articles/d41586-026-00965-3
#OpenScience #Reproducibility #Replication #ResearchIntegrity #metascience
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How can research findings be made more durable over time?
A Nature analysis highlights key strategies to improve reproducibility, replicability, and robustness across the social and behavioural sciences.
🔗 https://www.nature.com/articles/d41586-026-00965-3
#OpenScience #Reproducibility #Replication #ResearchIntegrity #metascience
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Under the banner "The winding road to better science", we are joining forces with our metaresearch centre and are offering ourselves as hosts for potential MSCA postdoctoral fellows. If you are interested in developing a project on or across the boundaries of #metascience and #STS, reach out! 1/
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Under the banner "The winding road to better science", we are joining forces with our metaresearch centre and are offering ourselves as hosts for potential MSCA postdoctoral fellows. If you are interested in developing a project on or across the boundaries of #metascience and #STS, reach out! 1/
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Under the banner "The winding road to better science", we are joining forces with our metaresearch centre and are offering ourselves as hosts for potential MSCA postdoctoral fellows. If you are interested in developing a project on or across the boundaries of #metascience and #STS, reach out! 1/
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Under the banner "The winding road to better science", we are joining forces with our metaresearch centre and are offering ourselves as hosts for potential MSCA postdoctoral fellows. If you are interested in developing a project on or across the boundaries of #metascience and #STS, reach out! 1/
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Under the banner "The winding road to better science", we are joining forces with our metaresearch centre and are offering ourselves as hosts for potential MSCA postdoctoral fellows. If you are interested in developing a project on or across the boundaries of #metascience and #STS, reach out! 1/
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#metascience What if we could study all grant applications—not just the funded ones—without compromising privacy?
Introducing MIGA: a minimal standard for open funding data https://doi.org/10.31222/osf.io/9hguf_v1
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#metascience What if we could study all grant applications—not just the funded ones—without compromising privacy?
Introducing MIGA: a minimal standard for open funding data https://doi.org/10.31222/osf.io/9hguf_v1
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#metascience What if we could study all grant applications—not just the funded ones—without compromising privacy?
Introducing MIGA: a minimal standard for open funding data https://doi.org/10.31222/osf.io/9hguf_v1
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#metascience What if we could study all grant applications—not just the funded ones—without compromising privacy?
Introducing MIGA: a minimal standard for open funding data https://doi.org/10.31222/osf.io/9hguf_v1
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Helen Pearson: Beyond Belief
In this Plutopia podcast episode, journalist and author Helen Pearson discusses her book Beyond Belief, which traces the rise of evidence-based decision-making in medicine, government, education, conservation, and other fields, arguing that evidence-based practice is both more recent and more fragile than many people realize. Pearson explains how pioneers of evidence-based medicine challenged “eminence-based” authority and helped build systems like randomized trials and systematic reviews, while also emphasizing that evidence is only one part of good decision-making alongside human values, experience, and compassion. The conversation explores how misinformation, influencers, political polarization, and poor communication of scientific uncertainty have eroded trust, especially in the U.S. — but Pearson remains cautiously optimistic, stressing the need to help people ask better questions, synthesize bodies of evidence rather than rely on anecdotes or single studies, and communicate science through engaging stories in the media channels where people actually get information.
https://media.blubrry.com/plutopia_news_network/plutopia.io/wp-content/uploads/2026/04/Helen-Pearson.mp3Podcast: Play in new window | Download
Helen Pearson:
We have to understand where people are getting their information from. If science is failing, then it’s because other channels are providing better entertainment and — maybe we touched on this earlier — the idea that scientists need to be where people are. I teach a class in science communication and journalism, and I ask them where they’re getting information from. This is sort of top-level undergraduate students or MSc students. And when I last polled the class, it was an interesting mix actually. They were saying from academic papers and YouTube. Academic papers, I think the scientists have got covered, but YouTube — that’s where that’s where they need to be.
Related: Michael Marshall on Compassionate Skepticism
YouTube Video
#evidenceBased #metascience -
Helen Pearson: Beyond Belief
In this Plutopia podcast episode, journalist and author Helen Pearson discusses her book Beyond Belief, which traces the rise of evidence-based decision-making in medicine, government, education, conservation, and other fields, arguing that evidence-based practice is both more recent and more fragile than many people realize. Pearson explains how pioneers of evidence-based medicine challenged “eminence-based” authority and helped build systems like randomized trials and systematic reviews, while also emphasizing that evidence is only one part of good decision-making alongside human values, experience, and compassion. The conversation explores how misinformation, influencers, political polarization, and poor communication of scientific uncertainty have eroded trust, especially in the U.S. — but Pearson remains cautiously optimistic, stressing the need to help people ask better questions, synthesize bodies of evidence rather than rely on anecdotes or single studies, and communicate science through engaging stories in the media channels where people actually get information.
https://media.blubrry.com/plutopia_news_network/plutopia.io/wp-content/uploads/2026/04/Helen-Pearson.mp3Podcast: Play in new window | Download
Helen Pearson:
We have to understand where people are getting their information from. If science is failing, then it’s because other channels are providing better entertainment and — maybe we touched on this earlier — the idea that scientists need to be where people are. I teach a class in science communication and journalism, and I ask them where they’re getting information from. This is sort of top-level undergraduate students or MSc students. And when I last polled the class, it was an interesting mix actually. They were saying from academic papers and YouTube. Academic papers, I think the scientists have got covered, but YouTube — that’s where that’s where they need to be.
Related: Michael Marshall on Compassionate Skepticism
YouTube Video
#evidenceBased #metascience -
This week I'm taking a break from #MetaScience / #OpenScience and getting back into #SCIENCE!
I'm at the Rank Symposium on "21st Century Colour Vision" 👁️🧠🌈🤓
Got Colour Vision questions? AMA!
(If I don't know the answer I'll have lots of people to pass the question on to...)#Rank #RankSymposium #ColourVision #ColorVision #OpenResearch
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This week I'm taking a break from #MetaScience / #OpenScience and getting back into #SCIENCE!
I'm at the Rank Symposium on "21st Century Colour Vision" 👁️🧠🌈🤓
Got Colour Vision questions? AMA!
(If I don't know the answer I'll have lots of people to pass the question on to...)#Rank #RankSymposium #ColourVision #ColorVision #OpenResearch
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This week I'm taking a break from #MetaScience / #OpenScience and getting back into #SCIENCE!
I'm at the Rank Symposium on "21st Century Colour Vision" 👁️🧠🌈🤓
Got Colour Vision questions? AMA!
(If I don't know the answer I'll have lots of people to pass the question on to...)#Rank #RankSymposium #ColourVision #ColorVision #OpenResearch
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This week I'm taking a break from #MetaScience / #OpenScience and getting back into #SCIENCE!
I'm at the Rank Symposium on "21st Century Colour Vision" 👁️🧠🌈🤓
Got Colour Vision questions? AMA!
(If I don't know the answer I'll have lots of people to pass the question on to...)#Rank #RankSymposium #ColourVision #ColorVision #OpenResearch
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This week I'm taking a break from #MetaScience / #OpenScience and getting back into #SCIENCE!
I'm at the Rank Symposium on "21st Century Colour Vision" 👁️🧠🌈🤓
Got Colour Vision questions? AMA!
(If I don't know the answer I'll have lots of people to pass the question on to...)#Rank #RankSymposium #ColourVision #ColorVision #OpenResearch
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Is a 55% replication rate too low, too high, or just right? Some thoughts on Tyner et al.’s (2026) recent study.
https://markrubin.substack.com/p/is-a-55-replication-rate-too-low
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Is a 55% replication rate too low, too high, or just right? Some thoughts on Tyner et al.’s (2026) recent study.
https://markrubin.substack.com/p/is-a-55-replication-rate-too-low
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Is a 55% replication rate too low, too high, or just right? Some thoughts on Tyner et al.’s (2026) recent study.
https://markrubin.substack.com/p/is-a-55-replication-rate-too-low
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Is a 55% replication rate too low, too high, or just right? Some thoughts on Tyner et al.’s (2026) recent study.
https://markrubin.substack.com/p/is-a-55-replication-rate-too-low
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Is a 55% replication rate too low, too high, or just right? Some thoughts on Tyner et al.’s (2026) recent study.
https://markrubin.substack.com/p/is-a-55-replication-rate-too-low
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New work and events...
🔸 Workshop on the politics and finances of open science reform
🔸 Symposium: “Who critiques the critique? Toward a reflexive metascience”
🔸 Preprint encourages establishing phenomena before testing theories
🔸 Systematic review of questionable research practices
https://markrubin.substack.com/p/critical-metascience-roundup-b87