#replicability — Public Fediverse posts
Live and recent posts from across the Fediverse tagged #replicability, aggregated by home.social.
-
From 20-22 July, the 4th #ACM #Conference on Reproducibility and Replicability will take place in #Delft.
The conference welcomes contributions on methods, tools, case studies, and community efforts around #reproducibility and #replicability in #computational research.Deadlines: 10 March (abstracts)/17 March (papers)
https://acm-rep.github.io/2026/cfp/
Foto by ThisIsEngineering on unsplash
-
How Scrutiny and Iteration Made Behavioral Economics Better https://www.chicagobooth.edu/review/how-scrutiny-iteration-made-behavioral-economics-better
"However, direct #replicability should not be confused with #generalizability or universality. While the basic patterns of behavior documented in the original experiments reliably show up in subsequent replications, their magnitudes can vary substantially across contexts. Loss aversion might be stronger in some settings than in others. Understanding this variation has become a central focus of contemporary behavioral economics research. Rather than viewing such #heterogeneity as a challenge to the field’s foundations, researchers increasingly see it as a source of insight into the underlying psychological mechanisms driving behavioral anomalies."
#BehavioralEconomics -
How to describe #steganography methods in a comparable and unified way to aid #replicability?
We combined pre-existing methodology into a single framework. New pre-print + online tool prototype (will get improved soon) on our website: https://patterns.omi.uni-ulm.de/news/
Full version of the paper and the online tool will be presented at the ARES'25 CUING workshop in August.
#replicability #steganography #covertchannels #informationhiding #infosec #cybersecurity #security #research
-
New publication: Code-sharing policies are associated with increased #reproducibility potential of ecological findings, by @antica_c and others. #codesharing #replicability #reliability
https://doi.org/10.24072/pcjournal.541 -
🎉 Our method Anisotropic Specular Image-Based Lighting Based on BRDF Major Axis Sampling has received the Replicability Stamp!
🔍 Check it out here: https://www.replicabilitystamp.org/index.html#https-github-com-iota97-anisotropyeditor
🧑💻 Code & data: https://github.com/iota97/AnisotropyEditor#ComputerGraphics #Rendering #Replicability #OpenScience #BRDF
-
I’m part of the #EEGManyLabs project testing the #replicability of influential #EEG studies. We are using #PredictionMarkets as a tool in this effort and you are invited to take part, especially if you have some expertise in EEG research, no matter how little. See below for details.
You may well know about the success of “prediction markets” in forecasting the likelihood of replication (e.g., Dreber et al., PNAS 2015). We are delighted to announce that we have partnered with economists who led these seminal studies to test the wisdom of the EEG community.
From today (as we near the end of recruitment for this project - please see last calls below), we are opening a survey to ask you to vote on the likelihood of some hypotheses studied in the #EEGManyLabs project. Subsequently, you will be invited to bet on the likelihood of success through a stock market platform, where you will earn real money for you or a selected charity.
The success of this effort will become clear when we complete the full project in a few years time. But the results will immediately tell us about the degree of optimism/pessimism amongst our community.
So, please share this widely and place your bets now...
How can I sign up for the prediction markets? Registrations to participate in the prediction markets are administered via the sign-up form linked below. You must have experience of working with EEG (for example, through collecting and/or analysing EEG data, which may be evidenced by having published peer-reviewed articles or preprints with EEG or equivalent experience e.g. designing, collecting and analysing data from EEG experiments).
#neuroscience #psychology #replication #replicationcrisis #reproducibility #metascience
-
#TIL: die unterschiede zwischen #repeatability, #reproducibility und #replicability: https://www.acm.org/publications/policies/artifact-review-and-badging-current
[dank @benhermann's beitrag zum tag der forschungsdaten NRW von @fdm_nrw: https://fdm-nrw.coscine.de/#/TagDerForschungsdatenNRW] -
#TIL: die unterschiede zwischen #repeatability, #reproducibility und #replicability: https://www.acm.org/publications/policies/artifact-review-and-badging-current
[dank @benhermann's beitrag zum tag der forschungsdaten NRW von @fdm_nrw: https://fdm-nrw.coscine.de/#/TagDerForschungsdatenNRW] -
#TIL: die unterschiede zwischen #repeatability, #reproducibility und #replicability: https://www.acm.org/publications/policies/artifact-review-and-badging-current
[dank @benhermann's beitrag zum tag der forschungsdaten NRW von @fdm_nrw: https://fdm-nrw.coscine.de/#/TagDerForschungsdatenNRW] -
#TIL: die unterschiede zwischen #repeatability, #reproducibility und #replicability: https://www.acm.org/publications/policies/artifact-review-and-badging-current
[dank @benhermann's beitrag zum tag der forschungsdaten NRW von @fdm_nrw: https://fdm-nrw.coscine.de/#/TagDerForschungsdatenNRW] -
#TIL: die unterschiede zwischen #repeatability, #reproducibility und #replicability: https://www.acm.org/publications/policies/artifact-review-and-badging-current
[dank @benhermann's beitrag zum tag der forschungsdaten NRW von @fdm_nrw: https://fdm-nrw.coscine.de/#/TagDerForschungsdatenNRW] -
Will high school students' reflection test performance predict the reasoning preferences and habits it does in adults?
Rizek and Toplak report "patterns of correlations are generally consistent with what has been reported in adult samples" in a sample of over 300 9th through 12 graders from North America:
-
Interesting new study estimating the #replicability of published research in #psychology over the past 20 years.
The paper includes *nearly all papers* published in six top psychology #journals over last 2 decades.
https://www.pnas.org/doi/10.1073/pnas.2208863120
The researchers used a #MachineLearning model (#RandomForest & logistic regression ensemble) to estimate the replication likelihood of over 14,000 #articles from 2000-2019 in six subfields of psychology.
