#debiasing — Public Fediverse posts
Live and recent posts from across the Fediverse tagged #debiasing, aggregated by home.social.
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A 2021 paper in a pay-to-publish #Nature journal claimed #mindfulness tasks (notice 3 things around you or differences between 2 similar images) reduced some cognitive #biases: https://doi.org/10.1057/s41599-021-00712-1
The mindful #debiasing was undetected in a re-analysis and 2 replications: https://doi.org/10.1007/s12671-025-02575-y
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Does awareness of intuition's fallibility help people avoid faulty intuitions?
#Teaching students #DualProcessTheory didn't help them avoid faulty intuitions about #physics problems.
https://doi.org/10.1103/PhysRevPhysEducRes.21.010135
#edu #cogSci #bias #debiasing #psychology #epistemology #rationality
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More successful predictions of my #BoundedReflectivism & #EpistemicIdentity article from 2022?
From about 2017 or 2018, I reviewed evidence suggesting that reflective thinking often helps, but may even hinder our judgment depending on factors like whether we are reasoning based on shared identities and epistemic standards (https://doi.org/10.1111/meta.12534).
Years later Robb Willer et al. solicited ideas for debiasing political judgments. After years of testing 25 different interventions, their results are published in #Science: https://doi.org/10.1126/science.adh4764
They found that biased evaluations of politicized facts were impacted by both
- REFLECTION (on potential misperceptions of undemocratic actions) and
- shared IDENTITY cues (which could help *or* hinder!)#decisionScience #politics #psychology #philosophy #epistemology #metaphilosophy #JDM #debiasing #chatBot
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"Political #socialMedia ads labeled as from in-party sources and apparently non-partisan sources were trusted more than out-party sources.
So if you want to be sneaky just advertise under a name without any party connections"
That's a description from @mjbsp.bsky.social about an #openAccess paper in #PoliticalPsychology by @tomstafford et al.: https://doi.org/10.1111/pops.13034
#politics #marketing #persuasion #journalism #decisionScience #nonPartisanship #socialPsychology #cogSci #bias #debiasing
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This week's fifth and final post applies the reason-responsive #consequentialist view of rational inquiry to shed light on bounded #rationality, the Standard Picture, and the #epistemology of inquiry.
Thanks to #DavidThorstad for giving us a peak inside the book Inquiry under bounds (#OxfordUniversityPress 2024).
https://philosophyofbrains.com/2024/07/05/inquiry-under-bounds-part-5-applying-the-account.aspx
#philosophy #psychology #cogSci #decisionScience #economics #logic #philosophyOfScience #bias #debiasing
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Does data visualization help people overcome mathematical biases like base rate neglect?
Not necessarily. In fact, one experiment on master’s students found that “when base rate information [was] presented visually, participants answered significantly more biased than when information [was] presented textually.“
https://doi.org/10.23947/2334-8496-2024-12-1-119-132
#probability #stats #edu #dataViz #bias #debiasing #argumentMapping
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'High-Dimensional Inference for Generalized Linear Models with Hidden Confounding', by Jing Ouyang, Kean Ming Tan, Gongjun Xu.
http://jmlr.org/papers/v24/22-0834.html
#confounders #inferences #debiasing -
'High-Dimensional Inference for Generalized Linear Models with Hidden Confounding', by Jing Ouyang, Kean Ming Tan, Gongjun Xu.
http://jmlr.org/papers/v24/22-0834.html
#confounders #inferences #debiasing -
'High-Dimensional Inference for Generalized Linear Models with Hidden Confounding', by Jing Ouyang, Kean Ming Tan, Gongjun Xu.
http://jmlr.org/papers/v24/22-0834.html
#confounders #inferences #debiasing -
'High-Dimensional Inference for Generalized Linear Models with Hidden Confounding', by Jing Ouyang, Kean Ming Tan, Gongjun Xu.
http://jmlr.org/papers/v24/22-0834.html
#confounders #inferences #debiasing -
'High-Dimensional Inference for Generalized Linear Models with Hidden Confounding', by Jing Ouyang, Kean Ming Tan, Gongjun Xu.
http://jmlr.org/papers/v24/22-0834.html
#confounders #inferences #debiasing