Hu Chuan-Peng
@hcp4715.bsky.social
1.3K followers 1.8K following 190 posts
Self cognition | computational modelling | meta-science, open science, diversity| amateur climber. @School of Psychology, Nanjing Normal University
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hcp4715.bsky.social
🔍 Key insight? Barriers are real (resources, access, incentives) – but actionable solutions exist!

We propose a gradual engagement ladder 📈: Start small → build/lead communities.

💡 Remember: You can engage in community at any time! *(2/4)
Reposted by Hu Chuan-Peng
lmu-osc.bsky.social
Curious about creating a reproducible workflow for your research? 🔍 We provide several self-paced tutorials about tools that make your work more efficient, reproducible, and collaborative.
Self-Paced Tutorial of the Day: Introduction to R 📊 lmu-osc.github.io/introduction...
Welcome – Introduction to R
lmu-osc.github.io
Reposted by Hu Chuan-Peng
simine.com
My blog has moved! It’s now at sometimesimwrongblog.wordpress.com If you have links to posts in your syllabus, let me know if you have any trouble finding the corresponding post!
Reposted by Hu Chuan-Peng
thuyvytnguyen.bsky.social
Updates on my #Vietnam trip: I met with students at Vietnam National University who will help with my project looking at stress biomarkers 😊 While #psychology research in VN is still young, biology is quite research-active. The students will also use this data for their UG theses.
#AcademicSky
Lecturer presenting her research to a group of students Lecturer presenting her research to a group of students Two professors meeting with a group of students Group photo of professors and students
Reposted by Hu Chuan-Peng
rmcelreath.bsky.social
I guess because software allows it, ppl keep trying to estimate diversification rates on phylogenies. This is not in principle possible, because infinite combinations of diversification and extinction rates can explain almost any tree. Short, clear recent-ish paper: www.nature.com/articles/s41...
Reposted by Hu Chuan-Peng
thomasmmeyer.bsky.social
We're hiring! 📢

Senior Lecturer in ‘Quantitative Methods and the Political System of Austria’ for 23 hours per week

The position is to be filled from September 1, 2026, and is limited until August 31, 2030

Deadline: 27 October 2025

More details: jobs.univie.ac.at/job/Senior-L...
Senior Lecturer (Academic Teaching)
Senior Lecturer (Academic Teaching)
jobs.univie.ac.at
Reposted by Hu Chuan-Peng
matti.vuorre.com
100% this, especially with Wiley given their anti-preprint stance.
francescopoli.bsky.social
Why are we still sending our work to Wiley and other publishing companies so that they can profit from it? There's so many better options now, for example: psychopen.eu/journals/
Reposted by Hu Chuan-Peng
jayvanbavel.bsky.social
I'm excited to share the news that our climate change project won the @spspnews.bsky.social Robert Cialdini Prize for a "paper that uses field methods and demonstrates the relevance of social psychology to outside groups and communities"!

You can read it here: www.science.org/doi/10.1126/...
Reposted by Hu Chuan-Peng
plosbiology.org
Sleep is often only investigated from a single dimension. @bttyeo.bsky.social &co identify 5 sleep-biopsychosocial profiles that link self-reported #sleep patterns to variability in #health, #cognition & #lifestyle factors in 770 healthy young adults @plosbiology.org 🧪 plos.io/42tRXSc
Canonical correlation analysis reveals five sleep-biopsychosocial profiles (LCs). Scatter plots showing correlations between biopsychosocial and sleep canonical scores. Each dot represents a different participant. The inset shows the null distribution of canonical correlations obtained by permutation testing; note that the null distribution is not centered at zero. The dashed line indicates the actual canonical correlation computed for each LC. The distribution of sleep (top) and biopsychosocial (right) canonical scores is shown on rain cloud plots.
Reposted by Hu Chuan-Peng
leuventea.bsky.social
🫖 Yesterday at KU Leuven, 17 minds from Neuroscience, Social Humanities, Computer Science (+ more!) met online and in person to sip tea & rethink peer review. We tackled bias, transparency & reviewer pay.

Curious? Resources here: osf.io/4fyaq/files

#OpenScience #PeerReview #Reproducibility
Reposted by Hu Chuan-Peng
dingdingpeng.the100.ci
Some papers are really good because they make just one point, but they make it really clearly — such as “Statistical Control Requires Causal Justification”

journals.sagepub.com/doi/10.1177/...
Reposted by Hu Chuan-Peng
improvingpsych.org
Friendly reminder for those submitting manuscripts to PsyArXiv!

Upon submission, moderators will check the preprint (i.e., the PDF file) and the metadata (i.e., the submission form) to ensure it fulfills the guidelines. Make sure you follow them!

For details 👉 buff.ly/M3cRBW2
Reposted by Hu Chuan-Peng
helencbarron.bsky.social
** We have up to TWO funded PhD positions available in our lab!! Apply below to find new ways to enhance memory👇 Pls retweet **

Deadline: 2nd December

1. Cross-species closed-loopTMR: tinyurl.com/bddu4tp6

2. TUS and TMR in humans:
tinyurl.com/jjws5ctj

Happy to chat to interested applicants.
Enhancing memory using cross-species closed-loop Targeted Memory Reactivation | mrcbndu
tinyurl.com
Reposted by Hu Chuan-Peng
ericmshuman.bsky.social
I am hoping to recruit a Ph.D. student to join the SPARC (Social Psychology of Activism, Resistance, & Change) Lab at @UVAPsyc in Fall 2026! You can find more info about my research on my website (ericshuman.com), and the program here (psychology.as.virginia.edu/social-psych...).
Home
ericshuman.com
Reposted by Hu Chuan-Peng
brendanchng.bsky.social
3 days of #BigTeamScience brilliance starts tomorrow!!!

There's still time to be part of this virtual event, so hurry and register now (fees are optional, and yes this means you can attend for free too!) 👉 bigteamscienceconference.github.io/registration/
Reposted by Hu Chuan-Peng
olivia.science
New preprint 🌟 Psychology is core to cognitive science, and so it is vital we preserve it from harmful frames. @irisvanrooij.bsky.social & I use our psych and computer science expertise to analyse and craft:

Critical Artificial Intelligence Literacy for Psychologists. doi.org/10.31234/osf...

🧵 1/
Cover page of Guest, O., & van Rooij, I. (2025, October 4). Critical Artificial Intelligence Literacy for Psychologists. https://doi.org/10.31234/osf.io/dkrgj_v1 Table 1 Guest, O., & van Rooij, I. (2025, October 4). Critical Artificial Intelligence Literacy for Psychologists. https://doi.org/10.31234/osf.io/dkrgj_v1 Table 2 Guest, O., & van Rooij, I. (2025, October 4). Critical Artificial Intelligence Literacy for Psychologists. https://doi.org/10.31234/osf.io/dkrgj_v1
Reposted by Hu Chuan-Peng
irisvanrooij.bsky.social
Social psychologists can know better than anyone in psychology that we do not want to let QRPs ruin trust in our science, again.

“Ultimately, contemporary AI is research misconduct.”
olivia.science
New preprint 🌟 Psychology is core to cognitive science, and so it is vital we preserve it from harmful frames. @irisvanrooij.bsky.social & I use our psych and computer science expertise to analyse and craft:

Critical Artificial Intelligence Literacy for Psychologists. doi.org/10.31234/osf...

🧵 1/
Cover page of Guest, O., & van Rooij, I. (2025, October 4). Critical Artificial Intelligence Literacy for Psychologists. https://doi.org/10.31234/osf.io/dkrgj_v1 Table 1 Guest, O., & van Rooij, I. (2025, October 4). Critical Artificial Intelligence Literacy for Psychologists. https://doi.org/10.31234/osf.io/dkrgj_v1 Table 2 Guest, O., & van Rooij, I. (2025, October 4). Critical Artificial Intelligence Literacy for Psychologists. https://doi.org/10.31234/osf.io/dkrgj_v1
Reposted by Hu Chuan-Peng
olivia.science
Without Critical AI Literacy (CAIL) in psychology (doi.org/10.31234/osf...) we risk the following:

1️⃣ misunderstanding statistical models, thinking correlation is causation;

2️⃣ confusing statistical models and cognitive models, undermining theory;

3️⃣ going against stated open science norms.

4/
The three aforementioned related themes sketched out in this
section, will play out in the AI-social psychology relationships we
will examine — namely:
a. misunderstanding of the statistical modelswhich constitute contemporary AI, leading to inter alia thinking that
correlation implies causation (Guest, 2025; Guest & Martin, 2023, 2025a, 2025b; Guest, Scharfenberg, & van Rooij,
2025; Guest, Suarez, et al., 2025);
b. confusion between statistical versus cognitive models
when it comes to their completely non-overlapping roles
when mediating between theory and observations (Guest
& Martin, 2021; Morgan & Morrison, 1999; Morrison &
Morgan, 1999; van Rooij & Baggio, 2021);
c. anti-open science practices, such as closed source code,
stolen and opaque collection and use of data, obfuscated
conflicts of interest, lack of accountability for models’
architectures, i.e. statistical methods and input-output
mappings are not well documented (Barlas et al., 2021;
Birhane & McGann, 2024; Birhane et al., 2023; Crane,
2021; Gerdes, 2022; Guest & Martin, 2025b; Guest, Suarez,
et al., 2025; Liesenfeld & Dingemanse, 2024; Liesenfeld et
al., 2023; Mirowski, 2023; Ochigame, 2019; Thorne, 2009). Being able to detect and counteract all these three together comprises the bedrock of skills in research methods in a time when AI
is used uncritically (see Table 1). The inverse: not noticing these
are at play, or even promoting them, could be seen as engaging in
questionable research practises (QRPs; Brooker & Allum, 2024;
Neoh et al., 2023; Rubin, 2023). Therefore, in the context of critical AI literacy for social psychology, and indeed cognitive, neuro-,
and psychological sciences in general, the three points above serve
as totemic touchstones, as litmus tests for checking somebody’s
literacy in AI (Guest, 2024; Guest & Martin, 2021, 2025a, 2025b; Guest, Scharfenberg, & van Rooij, 2025; Guest, Suarez, et al.,
2025; Suarez et al., 2025; van Rooij & Baggio, 2021; van Rooij
& Guest, 2025; van Rooij et al., 2024b). To wit, if somebody is
able to minimally articulate these three related issues, how they
manifest, and why they matter to our science, we can rest easy
they know the basics of how to critically evaluate AI products in
science.
Reposted by Hu Chuan-Peng