@cnsyoung.com
Training and Education Manager at the Center for Open Science | Quala Lab Member | Former President of SIPS | Mixed Methods Researcher & Evaluator | Community Psychologist | pain in the you-know-what | she/her | 🇩🇪🇺🇸
🚀 NASA Summer Internship: Open Science Impact
This summer internship offers an opportunity to work with a NASA mentor on efforts to assess how open science practices accelerate discovery & broaden participation in science.
Deadline: Feb 27. Application portal: stemgateway.nasa.gov/s/course-off...
📎 AREN's Local Network Leads (LNLs) program supports #Africa based researchers by training open science leaders to establish and lead local communities of practice at their institutions.
Apply now for this virtual 9-month open science leadership training program! ⬇️
africanrn.org/announcement...
The distribution of questionnaire results
New preprint! 🎉
Led by @heeminkang.bsky.social, we found that a brief teaching intervention (20 min lecture + student activity) improved some aspects open science knowledge and attitudes in students taking an undergrad health psych course osf.io/preprints/ps...
Preprint (Updated): An Analysis of the Effects of Open Science Indicators on #Citations in the French Open Science Monitor arxiv.org/abs/2508.20747 #openscience #scholcomm #osi
Happy Love Data Week! 💘
Issue 32 of RDM Weekly is out!
➡️ Creating a Data Sharing Community @harvarddataverse.bsky.social
➡️ Affording Reusable Data @nature.com
➡️ README Checklist @christophscheuch.bsky.social
➡️ Project Management Tools
and more!
#rdmweekly
rdmweekly.substack.com/p/rdm-weekly...
New #RSOS paper: ‘Don’t hate the players, hate the game’: qualitative insights from education researchers on questionable and open research practices. Read more: doi.org/10.1098/rsos... @mattmakel.bsky.social @sarahcaroleo.bsky.social @jesse-fleming.bsky.social @bryancook.bsky.social
📢 Applications are open for the 2026 Modern Meta-Analysis Research Institute (MMARI).
This 5-day workshop funded by the US National Science Foundation (NSF) is tailored for early-career education researchers with little to no prior meta-analysis experience.
Apply by 3/15: www.meta-analysis-re...
Love Data Week branded flyer, with an invitation to "try out our dataset review workflow!" and PREreview's logo underneath.
PREreview joins #LoveData26 celebration with a strong commitment to encouraging open peer review of diverse research outputs, including datasets.
📊 Try out our modular review workflow for datasets here: prereview.org/review-a-dat...
Learn more: bit.ly/dataset-work...
@lovedataweek.bsky.social
Text of the post is in an image with the logos of: - Love Data Week (red heart made of flying pixels for the O) - LMU Munich (green square) - LMU Open Science Center (LMU green open book) - University Library (the letters UB in grey and blue) The text is in the center of a gradient of red circles matching the Love Data Week logo.
Celebrating Love Data Week, we presented an introduction to Open Data & Research Data Management at LMU Munich, highlighting practical resources and real-world data stewardship experiences.
📽️ Recording & slides: osf.io/ytc7m/
Contributions: @lmu.de Research Funding Unit, Library, and SFB 1369.
Join us for the LOVE REPLICATIONS WEEK from March 2 - 6 with talks on reproductions, replications, how to find them, how to conduct them, how to have them conducted on your study, where to publish them, and much more!
LLMs generated several types of misleading and incorrect information. In two cases, LLMs provided initially correct responses but added new and incorrect responses after the users added additional details. In two other cases, LLMs did not provide a broad response but narrowly expanded on a single term within the user’s message (‘pre-eclampsia‘ and ‘Saudi Arabia’) that was not central to the scenario. LLMs also made errors in contextual understanding by, for example, recommending calling a partial US phone number and, in the same interaction, recommending calling ‘Triple Zero’, the Australian emergency number. Comparing across scenarios, we also noticed inconsistency in how LLMs responded to semantically similar inputs. In an extreme case, two users sent very similar messages describing symptoms of a subarachnoid hemorrhage but were given opposite advice (Extended Data Table 2). One user was told to lie down in a dark room, and the other user was given the correct recommendation to seek emergency care. Despite all these issues, we also observed successful interactions where the user redirected the conversation away from mistakes, indicating that non-expert users could effectively manage LLM errors in certain cases (Extended Data Table 3).
LLMs generated several types of misleading and incorrect information. In two cases, LLMs provided initially correct responses but added new and incorrect responses after the users added additional details. In two other cases, LLMs did not provide a broad response but narrowly expanded on a single term within the user’s message (‘pre-eclampsia‘ and ‘Saudi Arabia’) that was not central to the scenario. LLMs also made errors in contextual understanding by, for example, recommending calling a partial US phone number and, in the same interaction, recommending calling ‘Triple Zero’, the Australian emergency number. Comparing across scenarios, we also noticed inconsistency in how LLMs responded to semantically similar inputs. In an extreme case, two users sent very similar messages describing symptoms of a subarachnoid hemorrhage but were given opposite advice (Extended Data Table 2). One user was told to lie down in a dark room, and the other user was given the correct recommendation to seek emergency care. Despite all these issues, we also observed successful interactions where the user redirected the conversation away from mistakes, indicating that non-expert users could effectively manage LLM errors in certain cases (Extended Data Table 3).
When chatbots are given complete information on medical conditions, they typically spit out correct diagnoses and recommendations.
Actual patients, however, often describe their conditions with incomplete or irrelevant information and the chatbots cannot handle it.
www.nature.com/articles/s41...
sigh
The FORRT Replication Database has received a massive overhaul (FReD 2.0): We double-coded and validated all data from scratch and extended it in the course of a one-year-partnership with the @cos.io. We just switched to a faster interface thanks to @lukaswallrich.bsky.social’s wizardry.
🚀 Making Replications Count Hackathon - in-person 🚀
3 days. 4 open tools. 1 goal: make replication studies impossible to ignore.
📆 4-6 May 2026 | Münster, Germany
✈️ Travel & accommodation covered (UKRI-funded)
Apply by 16 March ➡️ indico.uni-muenster.de/e/marco2
🧵👇 What we will build?
Every time birthright citizenship comes up, I think about my dissertation on anti-immigrant attitudes and the feedback I got from the (now openly) maple MAGA grad student who said that "no one would seriously think like this" lol
This should be the biggest story in the country right now. The sitting US President was extorting state lawmakers from his own party by threatening to withhold public money if they didn’t gerrymander for him.
I don’t know how else to say it…
“AI-Generated Homogeneity” - new cartoon and post marketoonist.com/2024/11/ai-g...
“Homogeneity is ultimately at odds with distinctiveness. As with all tools, it’s all in how you use them.”
#marketing #ai #cartoon #marketoon
Super exciting to see COS committing to putting TOP into practice in its own roles as a publisher, funder, and research performing organization. I'm particularly looking forward to seeing the implementation for the research team - so much great metascience coming out of this group.
Turning abstract policy into real-world practice is challenging, and sometimes messy. In the coming months, COS will highlight how we and other in the research community are putting the TOP Guidelines into action in real research settings.
💡 Learn more in our blog post:
-- Bias Bias --
“Ultimately, views about the nature of bias can themselves become a bias in research on biases.”
Gerd Gigerenzer considers “Two Kinds of Bias”
🧵
The package formerly known as papercheck has changed its name to metacheck! We're checking more than just papers, with functions to assess OSF projects, github repos, and AsPredicted pre-registrations, with more being developed all the time.
scienceverse.github.io/metacheck/
If you're looking for examples of how to organize a data sharing repository, what documentation to include, how to name files, or how to organize data files, the FIDO (fictitious intervention for demonstration only) project on OSF provides some examples.
osf.io/59gte/overview
Israel is de-registering major nongovernmental aid groups from helping people in the Palestinian territories, according to several officials with humanitarian organizations. n.pr/42R8gJ2
Who Owns Our Knowledge? We asked thought leaders around the world how the #OAweek theme resonates with their work. Thanks to Angela Holzer & Michaela Bilic-Merdes from the German Research Foundation for sharing their insights. Learn more in our profile here: www.openaccessweek.org/theme-profil...
I'm so sick of discourse from supposed allies about where trans people went wrong.
Where we "went wrong" is that billionaires spent unimaginably large sums to attack us repeatedly and major media outlets have spent a decade piling on.
Register for Don't Use This Code's free Open Science Skills virtual training! Learn to:
- Use tools like GitHub, Python & Zenodo
- Make research accessible, transparent & reproducible
- Understand concepts like FAIR & CARE
- Draft Open Science & Data Management plans
🔗: www.opensciencetraining.org
