![\"\"](\"https://substackcdn.com/image/fetch/$s_!Vg0V!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F138868d9-f7b9-4c16-a78f-08012db6d137_1764x1250.png\")
Jenni Adams, and colleagues put together a zine on feminist open science, including some quotes from Elizabeth Bennett's (2021) article: \"Open Science From a Qualitative, Feminist Perspective.\"
My favourite quote from Bennett (2021) is:
From which position(s) is this [open science] framework speaking? Where is it located in a hierarchy of research power and epistemological dominance?
Adams, J., Needham, L., Barnes, M., Givans, S., He, S., Sadler, R., Smithson, D., & X, A. (2026). Fragments of rebellion (a zine about feminism and open research). Knowledge Commons. https://doi.org/10.17613/7eeq1-4yb53
![\"\"](\"https://substackcdn.com/image/fetch/$s_!JBZu!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F2d10b5cf-d206-48ff-b2f0-5ab3718f3213_935x8.png\")
Batool Almarzouq (2026) considered how the open science movement's promise to return science to the public is not being realised with respect to researchers from the Global South.
The movement behind Open Science emerged with noble aims and genuine intentions but has evolved into a flawed reality. The goal of open science is not openness itself; it's about redistributing power in knowledge production\u2014challenging the extractive systems that enrich the Global North at the expense of the Global South. Real change requires actively divesting from and delinking with the economic engines that Open Science systematically ignores or even relies upon. To fail in this is to betray everything the movement claims to stand for.
Almarzouq, B. (2026). Rethinking open science through dependency theory. Political Economy of Science, 27(2). https://magazine.scienceforthepeople.org/vol27-2-political-economy-of-science/rethinking-open-science/
Helen Longino (2026) recently made a similar point:
In spite of conceptual commitment to the openness of science, disadvantaged regions have less access (as contributors to or readers of) international publications, less access to networks of communication, fewer material resources with which to conduct research, and less input to the international scientific research agenda. Furthermore, their economic and political weakness leaves them vulnerable to extractive practices, whether of natural resources or of local knowledge.
These international imbalances between the highly resourced (dare we say over-resourced?) and the under-resourced are the context in which openness of science would have to be implemented.
Longino, H. E. (2026): Knowledge and politics: Reflections on challenges to open science. Social Epistemology. https://doi.org/10.1080/02691728.2026.2669576
![\"\"](\"https://substackcdn.com/image/fetch/$s_!CFBM!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F2d1077fd-c0ac-42e3-a2d2-72f50e1c86fe_935x8.png\")
Raffaela Kunz (2026)
traces the evolution of open science from a grassroots movement for knowledge democratization into a policy-driven and increasingly contested governance framework. [She] then examines how constitutional law should respond to the diminishing autonomy of science, arguing that traditional legal protections centered on individual academic freedom are inadequate to address systemic encroachments.
![\"\"](\"https://substackcdn.com/image/fetch/$s_!Uw4R!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fdfddc787-fadd-40c2-b3c0-30cad5da3088_975x682.png\")
Paralleling some of Almarzouq's (2026) points about open science in an unequal world, Kunz argues that:
What began as a bottom-up movement rooted in the ideals of knowledge democratization has evolved into a policy-driven framework increasingly shaped by broader political and economic agendas. In this process, open science\u2014more broadly understood as open scholarship\u2014has not only lost some of its critical edge, but has also come to reflect, and at times reinforce, the very dynamics it initially sought to resist.
Open science is increasingly losing its liberating and democratizing potential, as it becomes entangled with the interconnected and mutually reinforcing logics of commercialization, political instrumentalization, and media-driven visibility of science. Rather than challenging the dominance of commercial publishers and reinforcing the public nature of knowledge, open science policies have often sustained or even deepened existing market structures, increasing academia's dependence on private infrastructures.
The original promise of open science\u2014to enhance accessibility, foster collaboration, and strengthen scientific autonomy\u2014risks being sidelined, diluted, or co-opted by powerful institutional and corporate actors.
Kunz, R. (2026). Between democratization and instrumentalization: A constitutional perspective on open science. International Journal of Constitutional Law. https://doi.org/10.1093/icon/moag057
![\"\"](\"https://substackcdn.com/image/fetch/$s_!7CDG!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Ffc0ba12e-4968-4830-adae-d4e52183c753_935x8.png\")
In a new preprint, (2026) argues that we should \"stop treating metascientific heuristics as quality filters in AI review\":
AI-implemented checks for reproducibility, robustness, preregistration, claim scope, and other intended proxies for scientific credibility can extend human reviewers' capabilities. However, treating metascientific heuristics\u2013whose theoretical grounding remains contested or incomplete\u2013as necessary and sufficient signals for filtering out bad science is counterproductive to scientific progress. The emerging literature blurs the line between integrity filtering, based on necessary but insufficient signals of validity like reproducibility of stated results or lack of fake citations, and epistemic filtering, which uses machine-detectable signals to judge scientific quality. Drawing on critical metascience, we show that commonly proposed signals of research quality are insufficiently justified as general indicators of scientific value.
![\"\"](\"https://substackcdn.com/image/fetch/$s_!g31J!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F0d6cb771-fe16-403b-8c4c-dd27a6fba05e_1419x394.png\")
Hullman wrote a Substack post about her new preprint here:
![\"\"](\"https://substackcdn.com/image/fetch/$s_!le2O!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F43f99e2f-fbd2-40ad-ae3f-8fb50727d17f_1200x1200.jpeg\")
Hullman, J. (2026). Stop treating metascientific heuristics as quality filters in AI review. https://users.eecs.northwestern.edu/~jhullman/AI_metascience_position.pdf
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We had a great symposium at the General Meeting of the European Association of Social Psychology yesterday titled: \"Who critiques the critique? Toward a reflexive metascience.\"
I began by asking \"what is critical metascience and why is it important?\" I argued that critical metascience's \"external criticism\" can help to highlight collective biases that occur within mainstream metascience. A copy of my slides can be found here.
![\"\"](\"https://substackcdn.com/image/fetch/$s_!BX8M!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F1511d074-a6c3-41cf-9538-84a5de4b700f_1121x1130.jpeg\"){kind=spacer}
Rizqy Zein and Mario Gollwitzer then considered \"the role of context in explaining effect size heterogeneity in replication studies.\" They distinguished between \"conceptually relevant\" and \"conceptually irrelevant\" variables and found evidence that \"conceptually relevant context characteristics explain effect heterogeneity in the effects found by Shnabel and Nadler (2008).\" Hence, \"context does matter!\" A copy of their slides can be found here.
![\"\"](\"https://substackcdn.com/image/fetch/$s_!daNf!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F466e0611-3ac5-4b0a-8461-9805ab7d0a8b_3660x2745.jpeg\")
Finally, Fabrice Gabarrot asked \"Why do we need critical meta-science? From normalizing to problematizing the replication crisis.\" He argued that the three crises in psychology (early 1900s, 1960s-70s, & 2010s) produced the same \"immune response\" of redefining \"rigor\" and excluding non-congruent work. He distinguished between \"normative problematization\" (identify a malfunction, propose a procedural fix, reconduct the frame) and \"reflexive problematization\" (interrogate the frame itself). He argued that critical metascience can assist with the reflexive approach. A copy of his slides can be found here.
![\"\"](\"https://substackcdn.com/image/fetch/$s_!0vcR!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F1745d474-eadc-4110-a14b-36ab95df23a8_3068x2802.jpeg\")
F. Gabarrot & M. Rubin (Convenors) (2026, July 1), Who critiques the critique? Toward a reflexive metascience. Annual Meeting of the European Association of Social Psychology, Strasbourg, France.
![\"\"](\"https://substackcdn.com/image/fetch/$s_!rsqn!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fe405460c-8d31-4634-b084-468d6c06a2ad_935x8.webp\")
Related to my EASP presentation, I published a new article today that asks: \"What is critical metascience and why is it important?\"
I define critical metascience as a multidisciplinary research area that takes a step back to question some of metascience's commonly accepted assumptions, methods, problems, and solutions \u2026. In the current article, I aim to raise the profile of this research area and offer a rationale for viewing it as a distinct field of multidisciplinary inquiry.
![\"\"](\"https://substackcdn.com/image/fetch/$s_!-tZJ!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F0a46a340-5ba6-4721-98ee-6e324879389d_1280x510.jpeg\")
In my article, I:
define critical metascience;
explain why it's important;
address some potential concerns about it;
consider some emerging themes in the area; and
evaluate its potential relationships with metascience.
I conclude by reflecting on Popper's (1976) point that \"the objectivity of science is \u2026 [the result] of the friendly-hostile division of labour among scientists\" (p. 95). I argue that:
Critical metascience can play an important part in Popper's \"friendly-hostile division of labour\" by offering a special type of external criticism that exposes and challenges potential biases and dogma in metascience in order to improve its objectivity and approach.
Rubin, M. (2026). What is critical metascience and why is it important? Frontiers in Psychology, 17:1860740. https://doi.org/10.3389/fpsyg.2026.1860740
![\"\"](\"https://substackcdn.com/image/fetch/$s_!ryOv!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fefb7690f-1076-48b0-a819-707482a5775d_935x8.png\")
![\"\"](\"https://substackcdn.com/image/fetch/$s_!vEC3!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fef8fccaf-7cee-401c-979f-dbe1a4527b92_2283x621.png\")
and colleagues (2016) published a comment on the Open Science Collaboration's (OSC; 2015) \"Estimating the reproducibility of psychological science.\" They concluded that:
Metascience is not exempt from the rules of science. OSC used a benchmark that did not take into account the multiple sources of error in their data, used a relatively low-powered design that demonstrably underestimates the true rate of replication, and permitted considerable infidelities that almost certainly biased their replication studies toward failure. As a result, OSC seriously underestimated the reproducibility of psychological science.
Consistent with Gilbert et al.'s (2016) view, reviews of more recent well-powered, high quality replication studies have found much higher replication rates than the OSC's original estimate of 36%. For example, Nosek et el.'s (2022) review of 307 replication studies found a replication rate of 64%, Cobey et al.'s (2023) review of 116 replication studies found a replication rate of 71%, and Tyner et al.'s (2026) test of 274 claims found a replication rate of 55%. Based on these more recent estimates, the observed replication rate appears to be around 63% rather than 36%.
Is a 63% replication rate grounds for a \"crisis\"? As I've discussed recently, it depends on what you expect the replication rate to be. Glibert et al. also raised concerns about the \"correct benchmark\" in their follow-up article, arguing against a purely statistical interpretation based on random sampling error per se:
The correct benchmark must recognize all genuine sources of variability and cannot be limited to the fiction that the only way in which the replications differed from the originals was that they drew different subjects from the identical population.
A key challenge for future work which claims to have found \"low\" replication rates is to explain and justify an \"acceptable,\" \"optimal,\" or \"expected\" replication rate (see also Rubin, 2023).
Gilbert, D. T., King, G., Pettigrew, S., & Wilson, T. D. (2016). Comment on \"Estimating the reproducibility of psychological science\". Science, 351(6277), 1037-1037. https://doi.org/10.1126/science.aad7243
![\"\"](\"https://substackcdn.com/image/fetch/$s_!QRuO!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F864e527e-11a3-4cc1-8f4d-85fe9f0d6198_935x8.png\")
Through user experience research (UXR) initiatives that take into account our diverse membership and community, we can have a continuous, deeper understanding of the role of metadata in our members' workflows, and ensure that our work continues to meet our community's needs. Your support is the key to this process, and will positively impact the wider community - and if you'd like to start today, you can take part in our latest initiative: help us improve our Events page by sharing your thoughts on the page's feedback form.
\nHi, everyone! I'm Leandro Contreras, UX Researcher here at Crossref, since February 2026. In previous roles, I helped to design, build and manage digital products and workflows for universities and academic publishers, and now I'm dedicated to bridging the gap between our community's needs and the tools we build together.
\nAt Crossref, we're committed to collecting diverse community input, and ensuring our system is representative and useful for everyone that interacts with it. In this blog post, I'd like to introduce you to how we're kickstarting a more systematic approach to user research processes at Crossref, and invite you to take part in a new research initiative. First, let's quickly revise some key concepts:
\nUser experience (UX) is the exploration of how we, as humans, interact with products and services: whether that's a physical tool or, in our case, the invisible systems holding our metadata, or the visible interfaces that support our community - for example, our Participation Reports.
\nGood user experience can positively affect people's day-to-day lives, produce quality results, and champion inclusion: we are more likely to return to a product or a service if it's tailor-made for us, for our advantages and shortcomings.
\nUser experience research (UXR) is the methodical study of users of a product, service or system, using methods to learn about their behaviours, needs, and preferences. While user experience is the design of the experience, UXR is the evidence-based study used to inform those designs and prove they actually work.
\nIn practice, user experience researchers gather this evidence through a variety of methods that seek to capture quantitative and qualitative data. But what are these methods? And how do they apply in the context of an organisation like Crossref, with a growing membership building the research nexus with rich metadata using many different technologies?
\nTo understand the role and the impact of metadata across our vast community, we are currently mixing qualitative and quantitative research methods to help us get the right answers:
\nIn 2026, we've already put these methods to work:
\nLooking ahead, we'll continue setting up usability testing sessions, open quick feedback channels on our website, and investigate the impact of research integrity across our membership through surveys. However, these initiatives are only as effective as the community behind them! When you engage in our UXR initiatives, you actively shape current and future Crossref experiences, ensuring they fit your needs.
\nIf you are curious about participating, we've just launched a new feedback form on our Events page to detect new improvement opportunities, and we invite you to be part of it. This is a great opportunity to see how our initiatives work in practice, so we hope you'll jump in!
\n![\"Crossref](\"https://www.crossref.org/images/blog/2026/event-page-survey.png\")
\n
\n
\nOver time, you will see the impact of your participation come to life in future improvements to our tools and services through future project updates on our blog, and in the community forum as well. We welcome everyone to join the conversation there. If you have any further questions, suggestions, or collaboration ideas, you can also get in touch via email.
Launching new UX research initiatives at Crossref has been a wonderful way to get to know our community on a deeper level. I'm looking forward to bringing you closer to more initiatives in the future, and learning more from your feedback!
","doi":"https://doi.org/10.64000/je02r-h4q75","guid":"https://doi.org/10.64000/je02r-h4q75","image":"https://www.crossref.org/images/blog/2026/event-page-survey.png","language":"en","license":"https://creativecommons.org/licenses/by/4.0/legalcode","published_at":1782950400,"rid":"ntp8j-ctq03","summary":"Through user experience research (UXR) initiatives that take into account our diverse membership and community, we can have a continuous, deeper understanding of the role of metadata in our members' workflows, and ensure that our work continues to meet our community's needs.","tags":["Crossref","UX Research"],"title":"Take part in UX Research at Crossref","updated_at":1783009813,"url":"https://www.crossref.org/blog/take-part-in-ux-research-at-crossref/","version":"v1"}},{"document":{"authors":[{"contributor_roles":[],"family":"LaZerte","given":"Steffi","url":"https://orcid.org/0000-0002-7690-8360"}],"blog":{"authors":[{"name":"The rOpenSci Team"}],"community_id":"19c501a7-647b-4a11-9f5e-cf400817cce3","created":1780876800,"current_feed_url":null,"description":"Open Tools and R Packages for Open Science","favicon":"https://rogue-scholar.org/api/communities/19c501a7-647b-4a11-9f5e-cf400817cce3/logo","feed_format":"application/feed+json","feed_url":"https://ropensci.org/blog/index.json","filter":null,"generator":"Other","home_page_url":"https://ropensci.org/blog","issn":null,"language":"eng","license":"https://creativecommons.org/licenses/by/4.0/legalcode","prefix":"10.59350","relative_url":null,"secure":true,"slug":"ropensci","status":"active","subfield":"1710","title":"rOpenSci - open tools for open science","updated":1782995896,"use_api":null},"blog_name":"rOpenSci - open tools for open science","blog_slug":"ropensci","content_html":"I recently had the opportunity to learn what the term \"Nerd Sniping\" meant.Ma\u00eblle pointed out a conversation on the rOpenSci Slack about something called Vale, meant for text linting.I'd seen the comment, but honestly hadn't really understood what it was all about until Ma\u00eblle asked if I thought it'd be useful for editing the blog\u2026
\u2026time passes\u2026
About three days later, I've hardly finished any of the blog post reviews I was planning to do.I've been sucked down a rabbit hole of Vale setup, custom rules, and overrides.
It turns out that \"Nerd Sniping\" refers to the practice of throwing problems at nerds that distract them from what they were doing.
![\"xkcd](\"https://ropensci.org/blog/2026/07/02/editor-tools/nerd_sniping.png\")
That being said, it was a glorious hole to fall down!It was just too bad that Ma\u00eblle sniped me two more times by asking me about my spell check setup in Positron and then by asking if Panache would help with translations.
I was pretty slow at my editorial duties that week!But I did come out of the dive with a great editorial setup which will definitely save me time in future.
I've edited a lot of posts on the rOpenSci blog.I take pride in helping writers get their ideas across with clarity, while not losing their own style.I'm an opinionated editor, so I also try hard to ensure that writers understand when my suggestions are just my opinion, and when I think there are mistakes in style or content that really do need to be fixed.I am also fussy about the details, about being consistent with capitalizations, about keeping ideas logically ordered, and about making sure that readers without the same background might still understand the gist of the post1.
As such, my post reviews can get a bit lengthy and it's not unreasonable for me to have 20-30 comments on a standard post.That's not too problematic, but if I had to complain it might be about the technical edits, like fixing the capitalization of 'rOpenSci'2, ensuring headings are in sentence case, and that links to ropensci.org pages are relative.These aren't complicated fixes, but if you have to remember to keep an eye out for them, and then create a GitHub PR review suggestion for each fix, it can become a tad tedious.
Ma\u00eblle's timely sniping helped me finalize my collection of tools to help streamline editorial tasks.
All of these tools can be installed and used in different ways.They are also powerful with many different possible customizations and configurations.Here, I'll share with you how I use these tools as extensions in Positron to help make it easier to write and edit posts for the rOpenSci blog.Hopefully this inspires you to explore how you might set them up to support your workflows!Further, if you're interested in setting up your own tools, perhaps you want to check out this blog post on \"All the Ways to Programmatically Edit or Parse R Markdown / Quarto Documents\".
For each tool, you'll want to install the Positron extension, and then set up your configuration.Configurations can usually be specified at three different levels:
![\"\"](\"https://substackcdn.com/image/fetch/$s_!UcKA!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Ffe8b3fd8-bbbf-4853-8e7c-17f640876234_306x381.png\")
roweb3, for the rOpenSci blog).More specifically here are (some) of the locations/names for configuration files and links to their documentation sections for more details.
| Level | cSpell | Vale | Panache |
|---|---|---|---|
| User | Positron settings | .vale.ini in any parent dir. or global config | ~/.config/panache/config.toml |
| Project | .cspell.json | .vale.ini | .panache.toml |
| File | Inline Comments | Inline Comments | Inline Comments |
This means you can have different rules for different projects, and override them as needed.In the following examples, I'll show you how I do this for posts on the rOpenSci blog.
First is my spell checker, which probably doesn't need much explanation.However, it's nice to use a spell checker which also works on code.I use the Code Spell Checker (cSpell) extension by Street Side Software and installed the languages extensions individually:
Alternatively, you could also install the cSpell Bundled Dictionaries instead.
To configure this extension, I added two types of files: a project-level configuration file, and two dictionaries of words to consider 'correct'.
The project level configuration file, .cspell.json, lists languages to use for different files (to ensure index.es.md files go through the Spanish spellchecker, while index.pt.md files go through the Portuguese spellchecker, etc.).It also includes a list of globs for file paths we can ignore (I'm really not interested in spelling mistakes in the .git folder), as well as pointing to dictionaries.
These dictionaries are initially created by functions from my promoutils package, an R package for all my rOpenSci community workflows.wordlist_create() creates a wordlist based on rOpenSci packages and author names, so they don't trigger the spell check if they aren't recognized.wordlist_update() updates this list with new names as needed.
We keep these dictionaries in a .wordlists folder.Names are stored in the .wordlists/names.txt file, and we also have a .wordlists/words.txt file which stores words which are considered correct in the rOpenSci context (like 'usecases').
I should also note that I have a personal list of user words stored in my Positron user settings which lists words (like my name!)which I want to be considered correct across all projects.
When writing posts, we can also override the language settings within a post using a special comment.For example if we want to use English and Portuguese for a post we could add <--- cSpell: language en,pt--> to the document.
We can also include post-specific words to ignore, which is handy for acronyms.For example, if we wanted to ignore the acronym CSCW we could use <!--- cSpell: ignore CSCW ---> at the top of a post.
Spell check issues pop up as a warning in my text window, or as a list under \"Spell Checker Issues By File\" my lower window pane so I can review them, add them to word lists, or just mentally ignore them.
For linting text (checking the style and meaning of the words) I use the Vale VSCode extension by chrischinchilla5.Vale helps me check that the Blog Style rules are respected, and gives suggestions for alternative word choices to avoid common mistakes (such as words or expressions which might be derogatory).
To setup Vale I created a project-specific Vale configuration file .vale.ini6 in the roweb3 repository.I keep my personal .vale.ini file in a higher level folder that holds all my R projects.In addition to the Vale configuration file, I also created a Vale styles folder in roweb3/.vale-styles.This is where Vale rules are installed if we use predefined rules, and where I can put rOpenSci-specific rules for the blog.The first time you use Vale you'll want to run vale sync in the terminal to install the standard, non-custom, rules.I .gitignore all rules which are installed, but track and push custom rules.
Vale is where I've made the most customizations, especially with the rOpenSci Blog.
This is just the start!I imagine the more I use these rules the more fine tuning I'll do.
Vale problems are classified as messages, warnings, or errors, and are highlighted in the text window as a quick fix and listed in the Problems pane in my lower window.
I should also note that for all the rules I've disabled, there are a lot of opinionated rules left.We keep them as prompts to think about our writing, not because we must follow them!
![\"Vale's](\"https://ropensci.org/blog/2026/07/02/editor-tools/there_is.png\")
Vale's write-good rule doesn't want me to start a sentence with 'There is', but I'm going to anyway!
For formatting text, I use the Panache extension by jolars to format the (R)markdown files for the blog.This is probably the smallest amount of setup, as all we need is a minimal .panache.toml configuration file in the roweb3 repository.However, this file instructs Panache to do one super awesome thing for us, especially for translations of multilingual blog posts:
[format]wrap = \"sentence\"If you set up Positron to format on save, Panache automatically wraps text by sentence every time you save the file.This means that when a blog post is sent for a first pass translation using babeldown, the translation comes back pretty good.Alternatively, if the line breaks are in the middle of a sentence, the translation can become garbled as lines are treated as disjointed sections of text.
For my other work, I use wrap = \"reflow\", set in my user configuration file in ~/.config/panache/config.toml.
Finally, once I've got all the fiddly edits on a post's (R)md file ready to go, I use the GitHub Pull Requests extension to convert these edits to GitHub PR review suggestions.This is really handy if you find yourself making many small suggested changes to GitHub PRs.
To review blog posts, I fetch the PR with usethis::pr_fetch(), and then open the blog post (R)md file in Positron side by side with the html preview of the post in my web browser.
Then I review the html preview and make the edits directly in the (R)md file.When I'm done, I right click on the edited file name in the Source Control > Changes and select Create Pull Request Suggestions.
![](\"https://ropensci.org/blog/2026/07/02/editor-tools/suggestions.png\")
This converts my edits to GitHub PR review suggestions which I can then review in Positron, or as I prefer, in a web browser (and fix weird ones, such as suggestions which delete part of a section in one edit but add it back in the next; it's not always a perfect process).Once all the suggestions are converted, the extension asks me if I want to revert my changes (which I usually do).
A note of caution, I find this tool a bit confusing to use on a PR that has a lot of comments already.The comments it makes are sometimes hidden or split in odd ways and it's easy to accidentally create duplicates.In these situations it's sometimes easier just to make the suggestions in a browser as you might normally.
Each of these tools provides me a specific solution to a problem.There is some overlap among them; Vale could do spell checks, and Panache could do linting.However, I find that by using the tools separately I can achieve an especially detailed and customized setup that works really well with the rOpenSci blog in particular, and with my work in general.
By including the configuration files in the roweb3 repository, people who also use these tools will automatically use the configurations we've setup for the rOpenSci blog when they write a post.We also plan to add instructions for how to use these tools to the Blog Guide.This should give blog writers the option of using these tools if they would like to.
However, even if other writers don't use these tools, it's still very useful for me to see a list of potential problems to double check at the end of my review without having to remember to check for them manually.It means I can focus more on the review of the content rather than worry about whether it's Ropensci or rOpenSci \ud83d\ude04
Don't judge this post by these ideals, I said I'm a opinionated editor, writing is completely different \ud83d\ude09.\u00a0\u21a9\ufe0e
It's rOpenSci.Not Ropensci, not RopenSci and not ropenSci.\u00a0\u21a9\ufe0e
\"Linting\" with respect to text or prose means checking the style and meaning of the words.\u00a0\u21a9\ufe0e
I'm Canadian so generally follow Canadian spelling (a mix of British and American for those of you new to the complex world of English spelling differences).At rOpenSci, we generally just ask an author to pick one and stick to it.\u00a0\u21a9\ufe0e
There is also Vale by errata-ai, but this extension has been deprecated in favour of Vale VSCode.\u00a0\u21a9\ufe0e
If you get an error on startup, you may need to tell Vale where this is explicitly by modifying Projects' settings.json file to include \"vale.valeCLI.config\": \".vale.ini\"\u00a0\u21a9\ufe0e
For example, alex worries that the word \"Mexican\" might be used in a racist manner, but at rOpenSci, it's stated with pride and I don't want Vale to flag our community members for mentioning their nationality \ud83d\ude05\u00a0\u21a9\ufe0e
But awesomely, we can enforce this rule for English, but not Spanish posts!\u00a0\u21a9\ufe0e
Open Research soll der Standard f\u00fcr die Produktion, Vermittlung und Nachnutzung von Wissen in Berlin werden: Auf dieses strategische Ziel haben sich Vertreter*innen der Berliner Wissenschafts- und Kulturerbe-Einrichtungen in einem neuen Positionspapier geeinigt. Verfasst hat das Papier die Landesinitiative Open Research Berlin, der Prozess wurde durch das Open Research Office Berlin koordiniert. Hintergr\u00fcnde und Inhalt des neuen Papiers werden im Folgenden kurz erl\u00e4utert. Mit der Ver\u00f6ffentlichung startet eine \u00f6ffentliche Kommentierungsphase, so dass sich alle Interessierten einbringen und den Prozess mitgestalten k\u00f6nnen.
\n\nDie Landesinitiative Open Research Berlin ist ein Zusammenschluss von Berliner Wissenschafts- und Kulturerbe-Einrichtungen. Hervorgangen ist die Landesinitiative aus der 2014 vom Berliner Wissenschaftssenat einberufenen AG Open-Access-Strategie Berlin. Mit der Verabschiedung der\u00a0 Open-Access-Strategie Berlin (2015) durch das\u00a0 Berliner Abgeordnetenhaus wurde die Grundlage geschaffen, den offenen Zugang und eine umfassende Nutzbarkeit im Sinne von Open Access f\u00fcr Publikationen, Forschungsdaten und Kulturdaten zu etablieren. Ein weiterer wichtiger Schritt ist die Aufnahme von Open Research in das Berliner Hochschulgesetz (BerlHG): In Paragraph 41 werden Open Access und Open Science definiert und der Auftrag der Hochschulen beschrieben.
\n![\"\"](\"https://blogs.fu-berlin.de/open-research-berlin/files/2026/07/Positionspapier_Open-Research-Berlin_Seite_01-250x352.jpg\")
Nun geht die Landesinitiative Open Research Berlin \u2013 gut zehn Jahre nach der Open-Access-Strategie \u2013 den n\u00e4chsten Schritt: Im neuen Positionspapier zur Entwicklung von Open Research in Berlin (2026) wurden in einem partizipativen Prozess zahlreiche Vorschl\u00e4ge erarbeitet, wie die Aktivit\u00e4ten zur F\u00f6rderung von Open Access auf Open Research ausgeweitet und Koordination und Kooperation im Berliner Forschungsraum weiterentwickelt werden k\u00f6nnen.
\nGrund daf\u00fcr ist, dass Open Research Wissenschaft besser, wirksamer, gerechter und resilienter macht. Daf\u00fcr brauchen die Wissenschafts- und Kulturerbe-Einrichtungen gezielte Investitionen in Infrastruktur, Qualifizierung und Anreizsysteme. Die Prinzipien von Open Research \u2013 Transparenz, Partizipation, Fairness und Diversit\u00e4t \u2013 sind f\u00fcr demokratische Aushandlung, Meinungsbildung und das Gemeinwohl der Stadtgesellschaft entscheidend. Auch deshalb braucht das Land Berlin ein koordiniertes Vorgehen zusammen mit den Wissenschafts- und Kulturerbe-Einrichtungen.
\nEine nachfolgende, gemeinsame Open\u2011Research\u2011Strategie von Land und Hochschulen, wie sie in den Hochschulvertr\u00e4gen 2024\u20132028 vereinbart wurde, soll die Forschungspotenziale Berlins im Bereich Wissenschaft und Kulturerbe besser erschlie\u00dfen und die Standortvorteile st\u00e4rken. Das nun von der Landesinitiative ver\u00f6ffentlichte Positionspapier dient als Diskussionsgrundlage f\u00fcr die Ausarbeitung dieser gemeinsamen Strategie.
\nNeben der Open\u2011Access\u2011Strategie von 2015 st\u00fctzt sich die Landesinitiative f\u00fcr ihr Verst\u00e4ndnis von Open Research auf das Berliner Hochschulgesetz (2021) sowie auf die UNESCO\u2011Empfehlung zu Open Science (2021). Daraus ergibt sich unter anderem der Anspruch der Landesinitiative, die Bereiche Wissenschaft und Kultur gleichwertig zu adressieren und bei der Formulierung der strategischen Ma\u00dfnahmen gemeinsam zu ber\u00fccksichtigen (vgl. S. 4).
\nZur Entwicklung eines gemeinsamen Forschungsraums in Berlin sind die Prinzipien von Open Research von zentraler Bedeutung. Nach einer Analyse der derzeitigen Situation, Bedarfe und Potentiale f\u00fcr Open Research am Standort Berlin identifiziert die Landesinitiative drei Standortvorteile f\u00fcr Wissenschaft und Kultur (S.5-6):
\nOffene und kooperativ getragene Informationsinfrastrukturen sieht die Landesinitiative als wesentliche Voraussetzung daf\u00fcr, damit die Berliner Wissenschafts- und Kulturerbe-Einrichtungen ihre digitale Handlungsf\u00e4higkeit und Unabh\u00e4ngigkeit erhalten und st\u00e4rken k\u00f6nnen. Konkret fasst das Positionspapier den Handlungsbedarf in vier \u00fcbergreifenden Themen mit insgesamt neun Zielen zusammen. Jedes Thema enth\u00e4lt zwei bzw. drei Ziele:
\nThema 1: Kulturen der Offenheit
\n\"Verbesserte strukturelle Bedingungen gew\u00e4hrleisten die Anerkennung von Open Research.\"
Thema 2: Souver\u00e4ne Wissens\u00f6kosysteme
\n\"Die kooperative, selbstbestimmte und nachhaltige Gestaltung bedingt die St\u00e4rkung und Resilienz offener Informationsinfrastrukturen.\"
Thema 3: Faire Finanzierung
\n\"Eine transparente Finanzierung ber\u00fccksichtigt Prinzipien der Offenheit und Wissensgerechtigkeit.\"
Thema 4: Open Research Monitoring
\n\"Open Research wird in diversen Kontexten mit angemessenen Methoden begleitet, beobachtet und dokumentiert.\"
Die einzelnen Ziele werden jeweils in weniger Abs\u00e4tzen pr\u00e4gnant dargestellt und mit konkreten Vorschl\u00e4gen f\u00fcr geeignete Ma\u00dfnahmen konturiert. Das Thema Open Research ist \u00e4u\u00dferst facettenreich, ber\u00fchrt mindestens die Dom\u00e4nen Wissenschaft und Kultur und umspannt prinzipiell alle Zyklen des Forschungsprozesses. Aufgrund dieser Komplexit\u00e4t schl\u00e4gt die Landesinitiative in dem Positionspapier die Bildung von einrichtungs\u00fcbergreifenden Arbeitsgemeinschaften vor, die im weiteren Verlauf Ma\u00dfnahmen in einer Agenda konzipieren und bei der Umsetzung verfolgen.
\nFachgemeinschaften und die interessierte \u00d6ffentlichkeit erhalten die M\u00f6glichkeit, das Positionspapier zu begutachten, zu kommentieren und sich auf diese Weise jetzt und im weiteren Prozess einzubringen. Das Positionspapier wird daher unter anderem auf der Plattform PubPub ver\u00f6ffentlicht. Dort steht es allen Interessierten f\u00fcr ein Open Peer Review zur Verf\u00fcgung.
\nDie Landesinitiative Open Research Berlin ver\u00f6ffentlicht das Positionspapier in diesen zwei Versionen:
\nLandesinitiative Open Research Berlin (2026): Offenheit als Grundsatz. Positionspapier zur Entwicklung von Open Research in Berlin. Version zur \u00f6ffentlichen Kommentierung. https://doi.org/10.21428/986c5d43.0a4300d5\n\nalternativ zum DOI f\u00fchrt dieser Link zum PubPub: https://oabb.pubpub.org/pub/positionspapier-open-research-berlin/release/1\n
Landesinitiative Open Research Berlin (2026): Offenheit als Grundsatz. Positionspapier zur Entwicklung von Open Research in Berlin. http://dx.doi.org/10.17169/refubium-52664.\nZur Erl\u00e4uterung des bisherigen Konsultationsprozesses ver\u00f6ffentlicht das Open Research Office Berlin ein kurzes Addendum:
\nNeufend, Maike & Georg Fischer (2026): Konsultationsprozess f\u00fcr das Positionspapier zur Entwicklung von Open Research in Berlin. Open Research Office Berlin. https://oabb.pubpub.org/pub/open-research-strategie-konsultation/release/1.\nOpen Research Office Berlin (OROB) – Landeskoordinierungsstelle f\u00fcr offene Wissenschaft
\nc/o Freie Universit\u00e4t Berlin, Universit\u00e4tsbibliothek, Garystra\u00dfe 39, 14195 Berlin
E-Mail: team[at]open-research-berlin.de
\nWebsite: www.open-research-berlin.de
Zitierhinweis f\u00fcr diesen Blogpost:\n\nNeufend, M. (2026): Berliner Landesinitiative ver\u00f6ffentlicht Positionspapier zur Entwicklung von Open Research. Open Research Blog Berlin. https://doi.org/10.59350/095nq-pd042.","doi":"https://doi.org/10.59350/095nq-pd042","guid":"https://blogs.fu-berlin.de/open-research-berlin/?p=4167","image":"https://blogs.fu-berlin.de/open-research-berlin/files/2026/07/Positionspapier_Open-Research-Berlin_Seite_01-250x352.jpg","language":"de","license":"https://creativecommons.org/licenses/by/4.0/legalcode","published_at":1782950400,"rid":"sw2dq-p4m13","summary":"Open Research soll der Standard f\u00fcr die Produktion, Vermittlung und Nachnutzung von Wissen in Berlin werden: Auf dieses strategische Ziel haben sich Vertreter*innen der Berliner Wissenschafts- und Kulturerbe-Einrichtungen in einem neuen Positionspapier geeinigt. Verfasst hat das Papier die Landesinitiative Open Research Berlin, der Prozess wurde durch das Open Research Office Berlin koordiniert.","tags":["Aktuelles","Landesinitiative Open Research Berlin","Open-Access-Strategie Berlin","Open-Research-Strategie Berlin"],"title":"Berliner Landesinitiative ver\u00f6ffentlicht Positionspapier zur Entwicklung von Open Research","updated_at":1782998091,"url":"https://blogs.fu-berlin.de/open-research-berlin/2026/07/02/landesinitiative-open-research-berlin-positionspapier/","version":"v1"}},{"document":{"authors":[{"affiliation":[{"id":"https://ror.org/0153tk833","name":"University of Virginia"}],"contributor_roles":[],"family":"Turner","given":"Stephen D.","url":"https://orcid.org/0000-0001-9140-9028"}],"blog":{"authors":[{"name":"Stephen Turner"}],"community_id":"382941a7-2ffa-41df-8bbb-5f772188517f","created":1780876800,"current_feed_url":null,"description":"A practicing data scientist's take on AI, genomics, biosecurity, and the ways AI is reshaping how science gets done. Weekly updates from the field. Occasional notes on programming.","favicon":"https://rogue-scholar.org/api/communities/382941a7-2ffa-41df-8bbb-5f772188517f/logo","feed_format":"application/rss+xml","feed_url":"https://blog.stephenturner.us/feed","filter":null,"generator":"Substack","home_page_url":"https://blog.stephenturner.us","issn":null,"language":"eng","license":"https://creativecommons.org/licenses/by/4.0/legalcode","prefix":"10.59350","relative_url":null,"secure":true,"slug":"stephenturner","status":"active","subfield":"1311","title":"Paired Ends","updated":1782983063,"use_api":null},"blog_name":"Paired Ends","blog_slug":"stephenturner","content_html":"
It's a holiday week here in the US but not a quiet one. I'll be glamping at the lake tomorrow so this one's coming a day early. June 30 was a busy day for AI in science. OpenAI posted a genomics benchmark, Anthropic shipped Claude Science and brought Fable 5 back online, and I spent a good chunk of the day test driving Claude Science myself before starting my AI Dry July.
In any case, here are the five things that interested me the most this week.
OpenAI builds a genomics benchmark
RAND asks whether LLM agents can drive biological tools
David Brooks on who thrives once intelligence gets cheap
NIH's 235-word screen, and a list to check your abstract against
QED scores preprints and names the top 1%
OpenAI's Jeremiah Li and Andrew Ho posted GeneBench-Pro on bioRxiv, an expanded version of GeneBench. OpenAI also wrote a blog post about it.
![\"\"](\"https://substackcdn.com/image/fetch/$s_!jkqA!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fc5df3951-ad70-436c-be6d-8a48463e1e60_1152x431.png\")
Li, J. H. & Ho, A. J. GeneBench-Pro: Evaluating Multistage Statistical Reasoning in Genomics, Quantitative Biology, and Translational Biomedicine. 2026.06.29.735386 bioRxiv Preprint at https://doi.org/10.64898/2026.06.29.735386 (2026).
It's 129 problems across 10 domains with a genomics core. Each one hands an agent a short bit of context and a target quantity to estimate, then makes it work through a series of dependent decision points. These decision points are the kind of inferential forks where one plausible wrong turn can reshape everything that comes downstream. The point is to test whether a model can run a realistic multi-stage analysis end to end and not just answer multiple choice questions (though some multiple choice questions can be challenging!).
The scores: GPT-5.6 Sol Pro tops out at 31.5%, GPT-5.6 Sol at 28.7%, GPT-5.5 at 12%, and the best non-GPT model, Claude Opus 4.8, at 16%. OpenAI wrote a benchmark, ran its own models on it, and reported that they win. Worth saying plainly IMHO. In fairness, they released some problems publicly and gave many others to Artificial Analysis for independent scoring, which is more transparency than most self-graded benchmarks bother with.
There's lot's of buzz about GLM 5.2 lately, so I was a little surprised to see it rank so low compared to other models here.
![\"\"](\"https://substackcdn.com/image/fetch/$s_!kjLf!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F2f1f849a-5e95-4f29-8fd2-57919f6cf29f_2040x1444.png\")
Failure modes are interesting. The models often do most of the workflow correctly, then show what the authors call \"a consistent gap between noticing and acting\": they flag a diagnostic signal but don't carry its implication over to the decision it should change, so they pick the wrong estimator or stay on a plausible but wrong path.
That matches what I saw in my Claude Science test drive the same day. It collected the data and ran the analysis without much help, and a quick read through its code turned up several spots where it had assumed something I wouldn't have.
The timing was crowded. This dropped alongside Claude Science and the Fable 5 redeployment. If you use Fable 5, note the cost change: it's included for up to half your weekly usage through July 7, then it runs on metered usage credits after that.
Fable 5 will be included for up to 50% of weekly usage limits through July 7, after which it will be available via usage credits.
RAND's Center on AI, Security, and Technology (CAST) tested 7 frontier LLM agents on two questions: can they pick the right computational biology tool for a task, and can they operate one (report, PDF).
![\"\"](\"https://substackcdn.com/image/fetch/$s_!PmRp!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F84258bf6-a370-480c-87c2-1db050d2be04_1016x438.png\")
Lee, J. et al. Can LLM Agents Select and Engage with Biological Tools? An Initial Biosecurity Assessment. https://www.rand.org/pubs/research_reports/RRA4741-1.html (2026).
The case studies used EVEscape, which predicts immune escape, on influenza hemagglutinin and Lassa GPC, and ESM3, a protein design model, on GFP and influenza HA.
Asked to name the right tool for a stated function, the models did well, many around 80%. Put the same question inside a realistic biological workflow and accuracy fell across the board. Operating the tools was mixed and depended on the specific protein, and when the agents failed it was usually because they mishandled data or fumbled an autonomous step, not because they lacked the knowledge. Feeding an agent more biological detail didn't reliably help, and on the HA-targeted ESM3 task more information sometimes made things worse, which undercuts the tidy \"expertise plus AI equals uplift\" story.
And the closed-weight models refused a lot, especially on viral proteins and obvious dual-use requests, through either the model declining or a content filter catching it. Agents can already handle the front end of this work, that could lower the expertise barrier for a non-expert, and it deserves closer testing. This is an initial assessment on toy tasks, and they say so, so I'd strongly resist reading it as evidence that agents can build a functional biological weapon.
David Brooks, writing in The Atlantic, starts with the observation that AI hasn't handed anyone a 15-hour workweek.
The People Who Will Thrive in the AI Age: What will differentiate people is not how smart they are but their relationship to mental effort.
He cites ActivTrak data showing that when workers adopted AI their email and chat time more than doubled, their business software use rose 94%, and their focused, uninterrupted work fell 9%, plus a Berkeley Haas finding that people started pulling previously-outsourced tasks back in-house because AI made them easy.
My favorite line in the essay:
When intelligence is plentiful, volition is valuable.
He sorts people into three groups. Productive Passengers, low appetite for hard thinking, get more done and get hollowed out. Reluctant Optimizers mean to resist and get pulled in anyway. Mental Marathoners push back and use AI to widen their range rather than shrink it. Behind the hollowing-out worry he stacks a pile of studies: an MIT Media Lab result where brain connectivity dropped by half during ChatGPT-assisted tasks, a colonoscopy study where physicians' adenoma detection fell after the AI was taken away, and a Wharton experiment where people accepted a deliberately-wrong model's answers 80% of the time.
Some good practical advice at the end. Ask for hints instead of answers, write your own take on a blank page before you open the chat, and \"ask for thinkers, not thinking,\" meaning have the model summarize who has already worked on your problem so you can go read them. I started my AI Dry July this week, so I'll report back on whether a month of added friction does anything measurable for my gamma waves.
Max Kozlov at Nature reports that hundreds of NIH grant applications are stuck in a screen that runs after peer review. An algorithm checks each application's title, abstract, and summary sections against a list of disfavored terms, 235 of them as of February, including \"gender,\" \"climate change,\" \"racism,\" and \"fossil fuel.\" A hit flags the application, and the program officer is then told to renegotiate the language or drop the project.
This screen runs after two rounds of peer review and after the program officers and the institute director have already judged the work fundable. Then it enters a phase called Status 19, where NIH leaders and an HHS counselor can weigh in, with internal feedback that Nature obtained questioning whether a given study is worth funding because it looks \"likely to end up in a Congressional waste report.\" Most applications clear in two weeks, but a tenth of the renewals that reached this phase this fiscal year have sat for more than seven weeks, some indefinitely. NIH told Nature it keeps no banned-word list and doesn't base funding on specific words; the internal documents suggest flagged projects simply draw far more scrutiny.
I pulled the 235 terms out of the article into a searchable page, with the CSV on GitHub, so you can run your own grant proposal against it. You can also search/page through the flagged terms below.
QED Science ran its QED Score, an anonymized AI metric for a manuscript's originality and validity, across 57k bioRxiv preprints from May 2025 to April 2026 and named the top slice The 1%. Their whitepaper reports three validation studies: an AUC of 0.867 separating expert-labeled \"Limited\" papers from the rest on a 925-paper set, a Spearman \u03c1 of 0.63 between a preprint's score and the SJR of the journal it eventually landed in (scored with models whose knowledge cutoffs predated the corpus, to rule out contamination), and a blinded head-to-head where experts sided with the QED-favored paper in 75% of 60 decisive judgments.
I've been building my own peer-review skill in the open on the theory that most of these products are a frontier model wrapped in a good SKILL.md plus some connectors, and I'd rather that scaffolding be something the rest of us can see and fork.
A few other tabs I have open that I'll get to here soon.
created a refusal benchmark for biosecurity risk assessment (result, paper, blog). I wrote about refusal theater here a few weeks ago.
The Hitchhiker's Guide to Agentic AI: From Foundations to Systems
Autodata: An agentic data scientist to create high quality synthetic data
Paper mill cancer studies get double the number of citations as genuine papers
Lab-created 'SpudCell' marks 'stunning' step toward building life from scratch
Am 24. M\u00e4rz 2026 entschied das Bundesverfassungsgericht nach 12-j\u00e4hrigem Verfahrensgang, dass das Land Baden-W\u00fcrttemberg keine gesetzliche Zweitver\u00f6ffentlichungspflicht f\u00fcr wissenschaftliches Personal festlegen darf. Diese Entscheidung hat nicht nur unmittelbare Folgen f\u00fcr Hochschulsatzungen, die auf der Landesnorm beruhen. Sie wirft auch weitere, die Stellung von Open Access als vermeintliche Gegenspielerin des Urheberrechts betreffende Fragen auf. Hier werden die Hintergr\u00fcnde der Entscheidung, deren Inhalt und offene Fragen zusammengefasst.
\nDas Land Baden-W\u00fcrttemberg f\u00fchrte im Fr\u00fchjahr 2014 Paragraf 44 Absatz 6 Landeshochschulgesetz (LHG BW) ein. Dieser forderte Hochschulen auf, ihre Angeh\u00f6rigen zu der Zweitver\u00f6ffentlichung ihrer wissenschaftlichen Beitr\u00e4ge ein Jahr nach deren Erscheinen zu verpflichten. Die Idee des Landes zur Schaffung einer Zweitver\u00f6ffentlichungspflicht hat ihren Ursprung in Paragraf 38 Absatz 4 des Urheberrechtsgesetzes (UrhG). Dieser erlaubt es Urheberinnen eines wissenschaftlichen Beitrags unter gewissen Umst\u00e4nden, nach Ablauf von zw\u00f6lf Monaten diesen Beitrag in der Manuskriptversion \u00f6ffentlich zug\u00e4nglich zu machen, auch wenn dem urspr\u00fcnglichen Ver\u00f6ffentlichungsorgan das ausschlie\u00dfliche Nutzungsrecht \u00fcbertragen wurde. Das UrhG unterst\u00fctzt damit die Open Access-Bestrebungen in der Wissenschaft. Der Aufforderung der Regelung einer Zweitver\u00f6ffentlichungspflicht kam die Universit\u00e4t Konstanz in ihrer Satzung nach.
\nGegen die Regelungen in LHG BW und Satzung regte sich Widerstand bei einigen Professor*innen. Diese wendeten sich gegen die Satzung vor dem Verwaltungsgerichtshof. Sie beanstandeten einen unzul\u00e4ssigen Eingriff in das Grundrecht der Wissenschaftsfreiheit aus Artikel 5 Absatz 3 Grundgesetz durch die Zweitver\u00f6ffentlichungspflicht.
\nDagegen und f\u00fcr die Satzung und baden-w\u00fcrttembergische Norm argumentierte der Rechtsbeistand der Universit\u00e4t Konstanz: Diese habe keine Urheberrechte beschnitten, sondern lediglich f\u00fcr die ihnen Dienstverpflichteten die Aus\u00fcbung des Zweitver\u00f6ffentlichungsrechts aus dem Urheberrechtsgesetz geregelt. Es ginge bei der Norm nicht um die freie Zug\u00e4nglichkeit der urheberrechtlich gesch\u00fctzten Werke, sondern der darin enthaltenen gemeinfreien Information. Mit dieser Argumentation sah der Rechtsbeistand der Uni Konstanz keine Probleme durch eine Beschneidung der Gesetzgebungskompetenz des Bundes, da die Regelung nicht das Urheberrecht im eigentlichen Sinne betreffe.
\nDer Verwaltungsgerichtshof setzte das Verfahren aus und zur konkreten Normenkontrolle an das Bundesverfassungsgericht.
\nDer zweite Senat des Bundesverfassungsgerichts hatte dann die formelle Frage zu beantworten: Hatte das Land Baden-W\u00fcrttemberg \u00fcberhaupt die Gesetzgebungskompetenz zum Erlass einer Norm, die eine Zweitver\u00f6ffentlichungspflicht vorsieht?
\nDas Bundesverfassungsgericht entschied nun in seinem Beschluss: Nein, das Land Baden-W\u00fcrttemberg h\u00e4tte eine solche Norm nicht erlassen d\u00fcrfen, da die Regelung einer Zweitver\u00f6ffentlichungspflicht den Bereich des Urheberrechts betrifft, und somit ausschlie\u00dflich durch Bundesgesetz geregelt werden darf.
\nDas Gericht sieht in der baden-w\u00fcrttembergischen Norm \u2013 anders als der Verfahrensbeistand der Universit\u00e4t Konstanz \u2013 eine urheberrechtliche Regelung, weil die in Paragraf 44 Absatz 6 LHG BW geregelte Zweitver\u00f6ffentlichungspflicht die Aus\u00fcbung des urheberrechtlichen Zweitver\u00f6ffentlichungsrechts steuere und die durch das Zweitver\u00f6ffentlichungsrecht gegebene Entscheidungsfreiheit von Urheberinnen durch eine Pflicht ersetze.
\nDiese materielle Wirkung des Gesetzes war laut dem Gericht entscheidend f\u00fcr die Einordnung der baden-w\u00fcrttembergischen Norm als urheberrechtliche Norm.
\nOffen bleibt, ob die Norm unzul\u00e4ssig in das Grundrecht der Wissenschaftsfreiheit aus Artikel 5 Absatz 3 Grundgesetz eingreift. Dieses Grundrecht enth\u00e4lt auch die Publikationsfreiheit \u2013 also das Recht, die Rahmenbedingungen, wie Journal, Zeitpunkt und Verlag festzulegen und auch sich gegen eine Ver\u00f6ffentlichung der eigenen wissenschaftlichen Ergebnisse zu entscheiden. Zur Entscheidung dieser Frage kam das Bundesverfassungsgericht in seinem Beschluss nicht, die Pr\u00fcfung endete nach dem Ablehnen der formellen Verfassungsm\u00e4\u00dfigkeit.
\nAuch, welche Folgen die Verfassungswidrigkeit der baden-w\u00fcrttembergischen Norm f\u00fcr die Konstanzer Hochschulsatzung hat, hat das BVerfG nicht entschieden. Zwar sind Satzungen keine formellen Gesetze. Allerdings haben auch sie normative, also gesetzes\u00e4hnliche Wirkungen. Dar\u00fcber hinaus d\u00fcrfen Satzungen selbstverst\u00e4ndlich keine verfassungswidrigen Regelungen enthalten. In der Konsequenz wird die die Zweitver\u00f6ffentlichungspflicht betreffende Regelung in der Satzung ebenfalls wahrscheinlich nichtig sein.
\nDie Absage des Bundesverfassungsgerichts an eine landesrechtliche Regelung der urheberrechtlichen Ver\u00f6ffentlichung k\u00f6nnte zur Forderung verleiten, die Thematik bundesrechtlich zu regeln. Dies ist allerdings schwierig, da die Gesetzgebungskompetenz f\u00fcr dienstliche Vorgaben wissenschaftlicher Besch\u00e4ftigter gem\u00e4\u00df Artikel 70 Absatz 1 Grundgesetz bei den L\u00e4ndern liegt. Damit wird das generelle Regulierungsproblem in Bereichen, die die Wissenschaft und das Urheberrecht gleicherma\u00dfen betreffen, deutlich.
\nDie mutma\u00dflichen Folgen f\u00fcr die Konstanzer Satzung werfen auch die Frage auf, ob die Konsequenzen aus der Entscheidung des Bundesverfassungsgerichts auch auf Open Access Policies \u00fcbertragen werden m\u00fcssen. Hier m\u00f6glicherweise die vorsichtige Entwarnung: Open Access Policies werden voraussichtlich weiterhin mit dem Gesetz und der Verfassung vereinbar bleiben. Denn eine Policy ist in ihrer rechtlichen Verbindlichkeit von einer Satzung zu unterscheiden. Policies enthalten typischerweise \u2013 im Unterschied zu Satzungen \u2013 lediglich Empfehlungen, Richtlinien oder Standards. Sie sind also \u2013 vorbehaltlich eventueller Einzelf\u00e4lle \u2013 gerade nicht derartig rechtsverbindlich wie eine Satzung.
\nIn der Praxis kann es auch vorkommen, dass Open Access-Thematiken im Arbeitsvertrag geregelt werden. Hier bestehen zumindest keine Bedenken hinsichtlich der Kompetenz des Arbeitgebers, urheberrechtliche Sachverhalte arbeitsvertraglich zu regeln \u2013 dies ist g\u00e4ngige Praxis. Eine interessante und bisher nicht gekl\u00e4rte Frage ist allerdings, ob der Arbeitgeber eine Urheberin vertraglich zu einer Zweitver\u00f6ffentlichung im Open Access verpflichten kann. Hier ergibt sich das Potenzial eines Spannungsverh\u00e4ltnisses zwischen der arbeitsvertraglichen Regelung und dem Zweitver\u00f6ffentlichungsrecht aus Paragraf 38 Absatz 4 UrhG. Denn das Zweitver\u00f6ffentlichungsrecht der Urheberin darf nicht zu deren Nachteil abbedungen werden. Zwar stellt eine Zweitver\u00f6ffentlichungspflicht keine klassische negative Abweichung vom Zweitver\u00f6ffentlichungsrecht dar. Im Ergebnis entfaltet eine Zweitver\u00f6ffentlichungspflicht aber durchaus Wirkungen, die die Aus\u00fcbung des Zweitver\u00f6ffentlichungsrechts ber\u00fchren k\u00f6nnten. Ob diese und weitere Fragen zum Zweitver\u00f6ffentlichungsrecht zuk\u00fcnftig richterlich gekl\u00e4rt werden, bleibt abzuwarten.
\niRights.info\u00a0informiert und erkl\u00e4rt rund um das Thema \"Urheberrecht und Kreativit\u00e4t in der digitalen Welt\". Alle Texte erscheinen kostenlos und offen lizenziert.
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\nBesonders freuen wir uns \u00fcber einen regelm\u00e4\u00dfigen Beitrag, beispielsweise als monatlicher Dauerauftrag.\u00a0F\u00fcr Ihre Unterst\u00fctzung dankt Ihnen herzlich der\u00a0gemeinn\u00fctzige iRights e.V.!
\nDOI f\u00fcr diesen Text:\u00a0\u00b7 automatische DOI-Vergabe f\u00fcr Blogs \u00fcber The Rogue Scholar
\nThe post Bundesverfassungsgericht: Absage an Zweitver\u00f6ffentlichungspflicht? appeared first on iRights.info.
","doi":"https://doi.org/10.59350/ktwqk-0bj52","guid":"https://irights.info/?post_type=custom_artikel&p=32856","language":"de","license":"https://creativecommons.org/licenses/by/4.0/legalcode","published_at":1782950400,"rid":"hefb9-fv643","summary":"Am 24. M\u00e4rz 2026 entschied das Bundesverfassungsgericht nach 12-j\u00e4hrigem Verfahrensgang, dass das Land Baden-W\u00fcrttemberg keine gesetzliche Zweitver\u00f6ffentlichungspflicht f\u00fcr wissenschaftliches Personal festlegen darf. Diese Entscheidung hat nicht nur unmittelbare Folgen f\u00fcr Hochschulsatzungen, die auf der Landesnorm beruhen.","tags":["Allgemein","Urheberrecht","Wissenschaft"],"title":"Bundesverfassungsgericht: Absage an Zweitver\u00f6ffentlichungspflicht?","updated_at":1782978078,"url":"https://irights.info/artikel/bundesverfassungsgericht-absage-an-zweitveroeffentlichungspflicht/32856","version":"v1"}},{"document":{"authors":[{"contributor_roles":[],"family":"Wagen","given":"Corin","url":"https://orcid.org/0000-0003-3315-3524"}],"blog":{"authors":null,"community_id":"ee2393c0-2481-4a29-a7aa-0d1e0e423360","created":1693008000,"current_feed_url":null,"description":"My personal blog: chemistry, theology, metascience, and whatever else I'm thinking about.","favicon":"https://rogue-scholar.org/api/communities/ee2393c0-2481-4a29-a7aa-0d1e0e423360/logo","feed_format":"application/rss+xml","feed_url":"https://cwagen.substack.com/feed","filter":null,"generator":"Substack","home_page_url":"https://cwagen.substack.com","issn":null,"language":"eng","license":"https://creativecommons.org/licenses/by/4.0/legalcode","prefix":"10.59350","relative_url":null,"secure":true,"slug":"cwagen","status":"active","subfield":"1606","title":"Corin Wagen","updated":1782921020,"use_api":null},"blog_name":"Corin Wagen","blog_slug":"cwagen","content_html":"Something I've been thinking about recently is the information content of different biomolecules. While small molecules, peptides, antibodies, and oligonucleotides can all be valuable therapeutic assets in various contexts, they're strikingly different to synthesize, develop, and simulate. There are well-known reasons for many of these differences\u2014oligonucleotide synthesis can be highly automated, xenobiotic small-molecule metabolism proceeds through totally different pathways than peptide metabolism, and so on\u2014but at a high level I think many of these differences can be seen as downstream of the observation that small molecules have much higher information entropy per atom.
Information entropy, also known as Shannon entropy (after Claude Shannon), quantifies the amount of \"surprise\" associated with each new piece of data. A sequence like \"AAAAAAAAAAAAACAAAAA\" has low entropy, since almost every letter is A\u2014seeing another A gives us little new information, and so we can guess with pretty good odds that the next letter will be \"A.\" In contrast, a sequence like \"ACTAGGACATAAGACAGGCT\" has high entropy, since it seems that any position has four different possibilities. Since there are many possible sequences like this (just over a trillion for this length), each new letter conveys a lot of information about which particular sequence this is.
(This is a very brief introduction to Shannon entropy, and may be insufficient for those new to the topic\u2014you can find plenty of better ones on Google.)
For molecules, we can approximate the information content per atom as the base-2 logarithm of the number of possible molecules divided by the number of possible atoms. This definition lets us make some quick estimates for the per-atom entropy of different modalities:
There are 4 valid nucleotides, or two bits of entropy per nucleotide. If we approximate a nucleotide as having 20 heavy atoms, we find that an oligonucleotide contains 0.1 bits of entropy per heavy atom.
For proteins and other peptides, there are 20 valid amino acids, or 4.32 bits of entropy per residue. Assuming 8.3 heavy atoms per residue, this gives us a value of 0.52 bits of entropy per heavy atom.
Small molecules are a different story. The GDB-17 paper estimates that there are 166 billion druglike molecules with 17 or fewer heavy atoms, with the vast majority of these having 15\u201317 heavy atoms. This corresponds to 2.2 bits of entropy per heavy atom.
The small-molecule value quoted above may even be conservative: GDB-17 applies fairly conservative filters and doesn't include elements like S, P, B, and so on. If you take the oft-cited figure of 1060 possible drug-like molecules below 500 Da and approximate that as 35 heavy atoms, you arrive at a significantly larger value of 5.7 bits of entropy per heavy atom.
The markedly higher entropy of small molecules helps explain why small molecules are so tricky to synthesize. Fundamentally, any synthetic route must be specific and selective enough to disambiguate between virtually infinite numbers of potential products, which drives chemists to use complex and obscure reactions to achieve selectivity. Most approaches to simplifying small-molecule synthesis do so by vastly reducing the addressable space, enabling simple \"Lego brick\"\u2013style routes to be employed. While there are sure to be improvements in synthetic technology over the decades to come, I think that making arbitrary small molecules will continue to be a difficult and complex task for fundamental and unescapable reasons.
The high information content of small molecules also explains why they can be such effective drugs. The ability to pack so much information into a small number of atoms makes it possible to achieve impressive selectivity with a tiny molecule\u2014consider, e.g., the fact that you can have highly selective kinase inhibitors that are also small and non-polar enough to diffuse through the blood\u2013brain-barrier. This sort of thing just isn't possible with peptides!1
But the area where I've been thinking about this most is simulation and machine learning. It seems empirically true that it's much easier to predict or model protein\u2013protein binding than protein\u2013small molecule binding. While protein-binder design with models like BindCraft works well and metrics like ipSAE seem to correlate well with protein\u2013protein binding affinity, the analogous problems for small molecules still seem mostly unsolved (see e.g. Pat Walters' writing from last year).
I think that this is downstream of information content. While a 300-residue protein has just as much total information as any small molecule, the overall complexity of any individual region of intermolecular interactions is much lower. There are a relatively small number of chemically distinct groups in proteins\u2014indoles, imidazoles, amides, and so on\u2014and it's plausible that co-folding models or other biomolecular ML models can \"learn\" at a high level how these groups naturally interact with one another without needing to fundamentally understand the systems on the all-atom level. This means that learning to predict protein\u2013protein or protein\u2013oligonucleotide interactions is much easier than learning to predict protein\u2013small molecule interactions, perhaps many orders of magnitude easier.
In contrast, there are almost infinitely many such small-molecule functional groups\u2014pyridines, quinazolines, azaindoles, thiadiazoles, and so on\u2014each with different chemical properties and a different interaction profile with protein sidechains. This means that the data scarcity problem is much worse than it seems for small molecules, and makes me skeptical that purely ML-based approaches for predicting binding affinity will work in the medium term. (I may be wrong here!)
(How much data will it take to actually learn arbitrary interatomic interactions? It's hard to say for sure, but evidence from the neural-network-potential field suggests that it might take a lot. The OMol25 dataset comprises over 100 million DFT calculations with energy and per-atom force labels, so roughly 1\u201310 billion individual labels, and OMol25-trained models are the first models that seem to actually match the performance of physics-based methods on e.g. non-covalent interactions. While initiatives like OpenBind are promising and very valuable, I'm skeptical that even tens of thousands of new protein\u2013ligand complexes will be enough here.)2
I remain optimistic about the future of physics and physics-adjacent methods in small-molecule drug design for these reasons. Methods like quantum chemistry and FEP are able to avoid the training-data limitations of pure ML methods and show good generalizability for arbitrary small molecules. While I'm unbelievably excited about our new AI-powered scientific future, I think that the immense information content of small molecules puts fundamental limitations on what ML can accomplish, and means that (for better or worse) we're going to be stuck with physics for the foreseeable future.
Thanks to Ishaan Ganti and Ari Wagen for helpful discussions here.
Except for some peptides and other large molecules, which do diffuse through the blood\u2013brain barrier! Some of these seem to occur through active transport, but there's some mystery here still.
Note that there are many different potential forms of data, the shape of these problems is different, and there are other issues that make this comparison imperfect. I use this analogy simply to argue that we probably need a lot more data, not a little.
![\"On](\"https://pkp.sfu.ca/wp-content/uploads/2026/06/LTS-June-2026-WP-1024x576.jpg\")
We are pleased to announce the release of OJS, OMP, and OPS 3.5.0-5, which has now been officially designated as a Long-Term Support (LTS) release. This release reflects our commitment to stability, reliability, and readiness for the tens of thousands of journals, presses, and preprint servers around the world that depend on PKP software every day.
\nBy designating 3.5.0-5 as our LTS release, we are committing to its ongoing maintenance for an extended period. This means users can adopt this version knowing it will continue to receive bug fixes and security patches in the near term.
\nIf you are unsure which version your installation is running, or want to understand how the 3.5 branch fits into PKP's broader release cycle (including how LTS and Short-Term Support (STS) releases relate to each other and what \"end of life\" means in practice) our PKP Software Releases page provides a clear overview, including a version support timeline and guidance on choosing the right version for your context.
\nIf your installation is currently running an earlier version of the 3.5 branch, upgrading to 3.5.0-5 is straightforward and strongly encouraged.
\nThis update addresses a collection of bug fixes and stability improvements identified since the previous release, informed by reports from our global community of users, developers, and hosted clients. While this is a maintenance release rather than a feature release, the fixes it contains address real issues affecting real publishing workflows.
\nThe full list of resolved issues is documented in the release notes on GitHub. We encourage system administrators and developers to review these notes as part of their upgrade planning.
\n\n\nA note for hosted clients: If PKP Publishing Services hosts your journal, press, or preprint server, contact us if you'd like to discuss the upgrade schedule for your installation.
\n
Running an up-to-date version of OJS, OMP, or OPS means your platform benefits from the latest bug fixes, remains compatible with third-party integrations and indexing services, and continues to meet the standards that authors, reviewers, and readers expect from a trustworthy publishing environment.
\nWe recognize that upgrades require planning, testing, and coordination, particularly for institutions managing multiple journals or operating with limited technical support. If you are currently running an older, unsupported version of OJS, OMP, or OPS, we encourage you to check the PKP Software Releases page to understand your version's support status and end-of-life date. Unsupported versions no longer receive bug fixes, security patches, forum assistance from PKP staff, or updates to documentation and translations. Our documentation, community forum, and hosting and support services are all available to assist you through the upgrade process.
\nCheck out PKP's News Blog post on \"Why upgrading is key to participating in open scholarly infrastructure\" for more reasons to upgrade.
\nDownloads for OJS, OMP, and OPS 3.5.0-5 are available now:
\n\nIf you are on a version earlier than 3.3, you must upgrade to 3.3 before you can upgrade to 3.5. Before upgrading, please review the upgrade guide in our documentation and ensure you have a complete backup of your database and files. There is also an upgrading checklist and step-by-step demonstration on how to upgrade to 3.5 for systems administrators, now available on PKP's YouTube channel, thanks to our collaboration with Crossref.
\nIf you encounter any issues during or after upgrading, please search the community forum. You may find that others have already worked through the same situation. Or you can open a new thread for support from the PKP community and team.
\nReleases like this one are made possible in large part by the community members who take the time to report bugs, submit pull requests, and test fixes in their own environments. We are grateful for the ongoing contributions of developers, librarians, journal managers, and institutional partners from around the world who help make PKP software better for everyone.
\nIf you would like to become more involved in PKP's development and testing processes, we invite you to explore how to contribute.
\nThe post OJS, OMP, and OPS 3.5.0-5 LTS is now Available appeared first on Public Knowledge Project.
","doi":"https://doi.org/10.59350/zfq4j-hgs92","guid":"https://pkp.sfu.ca/?p=19247","image":"https://pkp.sfu.ca/wp-content/uploads/2026/06/LTS-June-2026-WP-1024x576.jpg","language":"en","license":"https://creativecommons.org/licenses/by/4.0/legalcode","published_at":1782864000,"rid":"0e7za-4sm90","summary":"We are pleased to announce the release of OJS, OMP, and OPS 3.5.0-5, which has now been officially designated as a Long-Term Support (LTS) release. This release reflects our commitment [\u2026] The post OJS, OMP, and OPS 3.5.0-5 LTS is now Available appeared first on Public Knowledge Project.","tags":["News","News For Developers","News For Hosted Clients","3.5","Long-Term Support (LTS)"],"title":"OJS, OMP, and OPS 3.5.0-5 LTS is now Available","updated_at":1782919475,"url":"https://pkp.sfu.ca/2026/07/01/3-5-0-5-lts-release/","version":"v1"}},{"document":{"authors":[{"contributor_roles":[],"name":"Atarraya"}],"blog":{"authors":null,"community_id":"f17066f5-0dbf-48d0-a413-b22a79861a94","created":1723852800,"current_feed_url":null,"description":"Nuestras historias","favicon":"https://rogue-scholar.org/api/communities/f17066f5-0dbf-48d0-a413-b22a79861a94/logo","feed_format":"application/atom+xml","feed_url":"https://blogatarraya.com/feed/atom/","filter":null,"generator":"Other","home_page_url":"https://blogatarraya.com","issn":null,"language":"spa","license":"https://creativecommons.org/licenses/by/4.0/legalcode","prefix":"10.59350","relative_url":null,"secure":true,"slug":"atarraya","status":"active","subfield":"1202","title":"BLOG ATARRAYA","updated":1782923021,"use_api":true},"blog_name":"BLOG ATARRAYA","blog_slug":"atarraya","content_html":"","doi":"https://doi.org/10.59350/qgm9m-jth86","guid":"https://blogatarraya.com/?p=7184","language":"es","license":"https://creativecommons.org/licenses/by/4.0/legalcode","published_at":1782864000,"rid":"fn809-j3f67","tags":["Arte, Cultura E Historia","Artes Visuales","Im\u00e1genes, Cartograf\u00edas Y Otros","N\u00famero 31","Qufti"],"title":"Qufti (Parte I)","updated_at":1782908642,"url":"https://blogatarraya.com/2026/07/01/qufti-parte-i/","version":"v1"}}],"items":[{"authors":[{"contributor_roles":[],"family":"Rubin","given":"Mark"}],"blog":{"authors":[{"name":"Mark Rubin"}],"community_id":"3bd0dcf5-7d43-47f1-b260-87d9f30bdcd6","created":1681948800,"current_feed_url":null,"description":"Critical metascience takes a step back to question some common assumptions, approaches, problems, and solutions in metascience.","favicon":"https://rogue-scholar.org/api/communities/3bd0dcf5-7d43-47f1-b260-87d9f30bdcd6/logo","feed_format":"application/rss+xml","feed_url":"https://markrubin.substack.com/feed","filter":null,"generator":"Substack","home_page_url":"https://markrubin.substack.com","issn":null,"language":"eng","license":"https://creativecommons.org/licenses/by/4.0/legalcode","prefix":"10.59350","relative_url":null,"secure":true,"slug":"markrubin","status":"active","subfield":"1207","title":"Critical Metascience","updated":1783011017,"use_api":null},"blog_name":"Critical Metascience","blog_slug":"markrubin","content_html":"Jenni Adams, and colleagues put together a zine on feminist open science, including some quotes from Elizabeth Bennett's (2021) article: \"Open Science From a Qualitative, Feminist Perspective.\"
My favourite quote from Bennett (2021) is:
From which position(s) is this [open science] framework speaking? Where is it located in a hierarchy of research power and epistemological dominance?
Adams, J., Needham, L., Barnes, M., Givans, S., He, S., Sadler, R., Smithson, D., & X, A. (2026). Fragments of rebellion (a zine about feminism and open research). Knowledge Commons. https://doi.org/10.17613/7eeq1-4yb53
Batool Almarzouq (2026) considered how the open science movement's promise to return science to the public is not being realised with respect to researchers from the Global South.
The movement behind Open Science emerged with noble aims and genuine intentions but has evolved into a flawed reality. The goal of open science is not openness itself; it's about redistributing power in knowledge production\u2014challenging the extractive systems that enrich the Global North at the expense of the Global South. Real change requires actively divesting from and delinking with the economic engines that Open Science systematically ignores or even relies upon. To fail in this is to betray everything the movement claims to stand for.
Almarzouq, B. (2026). Rethinking open science through dependency theory. Political Economy of Science, 27(2). https://magazine.scienceforthepeople.org/vol27-2-political-economy-of-science/rethinking-open-science/
Helen Longino (2026) recently made a similar point:
In spite of conceptual commitment to the openness of science, disadvantaged regions have less access (as contributors to or readers of) international publications, less access to networks of communication, fewer material resources with which to conduct research, and less input to the international scientific research agenda. Furthermore, their economic and political weakness leaves them vulnerable to extractive practices, whether of natural resources or of local knowledge.
These international imbalances between the highly resourced (dare we say over-resourced?) and the under-resourced are the context in which openness of science would have to be implemented.
Longino, H. E. (2026): Knowledge and politics: Reflections on challenges to open science. Social Epistemology. https://doi.org/10.1080/02691728.2026.2669576
Raffaela Kunz (2026)
traces the evolution of open science from a grassroots movement for knowledge democratization into a policy-driven and increasingly contested governance framework. [She] then examines how constitutional law should respond to the diminishing autonomy of science, arguing that traditional legal protections centered on individual academic freedom are inadequate to address systemic encroachments.
Paralleling some of Almarzouq's (2026) points about open science in an unequal world, Kunz argues that:
What began as a bottom-up movement rooted in the ideals of knowledge democratization has evolved into a policy-driven framework increasingly shaped by broader political and economic agendas. In this process, open science\u2014more broadly understood as open scholarship\u2014has not only lost some of its critical edge, but has also come to reflect, and at times reinforce, the very dynamics it initially sought to resist.
Open science is increasingly losing its liberating and democratizing potential, as it becomes entangled with the interconnected and mutually reinforcing logics of commercialization, political instrumentalization, and media-driven visibility of science. Rather than challenging the dominance of commercial publishers and reinforcing the public nature of knowledge, open science policies have often sustained or even deepened existing market structures, increasing academia's dependence on private infrastructures.
The original promise of open science\u2014to enhance accessibility, foster collaboration, and strengthen scientific autonomy\u2014risks being sidelined, diluted, or co-opted by powerful institutional and corporate actors.
Kunz, R. (2026). Between democratization and instrumentalization: A constitutional perspective on open science. International Journal of Constitutional Law. https://doi.org/10.1093/icon/moag057
In a new preprint, (2026) argues that we should \"stop treating metascientific heuristics as quality filters in AI review\":
AI-implemented checks for reproducibility, robustness, preregistration, claim scope, and other intended proxies for scientific credibility can extend human reviewers' capabilities. However, treating metascientific heuristics\u2013whose theoretical grounding remains contested or incomplete\u2013as necessary and sufficient signals for filtering out bad science is counterproductive to scientific progress. The emerging literature blurs the line between integrity filtering, based on necessary but insufficient signals of validity like reproducibility of stated results or lack of fake citations, and epistemic filtering, which uses machine-detectable signals to judge scientific quality. Drawing on critical metascience, we show that commonly proposed signals of research quality are insufficiently justified as general indicators of scientific value.
Hullman wrote a Substack post about her new preprint here:
Hullman, J. (2026). Stop treating metascientific heuristics as quality filters in AI review. https://users.eecs.northwestern.edu/~jhullman/AI_metascience_position.pdf
We had a great symposium at the General Meeting of the European Association of Social Psychology yesterday titled: \"Who critiques the critique? Toward a reflexive metascience.\"
I began by asking \"what is critical metascience and why is it important?\" I argued that critical metascience's \"external criticism\" can help to highlight collective biases that occur within mainstream metascience. A copy of my slides can be found here.
Rizqy Zein and Mario Gollwitzer then considered \"the role of context in explaining effect size heterogeneity in replication studies.\" They distinguished between \"conceptually relevant\" and \"conceptually irrelevant\" variables and found evidence that \"conceptually relevant context characteristics explain effect heterogeneity in the effects found by Shnabel and Nadler (2008).\" Hence, \"context does matter!\" A copy of their slides can be found here.
Finally, Fabrice Gabarrot asked \"Why do we need critical meta-science? From normalizing to problematizing the replication crisis.\" He argued that the three crises in psychology (early 1900s, 1960s-70s, & 2010s) produced the same \"immune response\" of redefining \"rigor\" and excluding non-congruent work. He distinguished between \"normative problematization\" (identify a malfunction, propose a procedural fix, reconduct the frame) and \"reflexive problematization\" (interrogate the frame itself). He argued that critical metascience can assist with the reflexive approach. A copy of his slides can be found here.
F. Gabarrot & M. Rubin (Convenors) (2026, July 1), Who critiques the critique? Toward a reflexive metascience. Annual Meeting of the European Association of Social Psychology, Strasbourg, France.
Related to my EASP presentation, I published a new article today that asks: \"What is critical metascience and why is it important?\"
I define critical metascience as a multidisciplinary research area that takes a step back to question some of metascience's commonly accepted assumptions, methods, problems, and solutions \u2026. In the current article, I aim to raise the profile of this research area and offer a rationale for viewing it as a distinct field of multidisciplinary inquiry.
In my article, I:
define critical metascience;
explain why it's important;
address some potential concerns about it;
consider some emerging themes in the area; and
evaluate its potential relationships with metascience.
I conclude by reflecting on Popper's (1976) point that \"the objectivity of science is \u2026 [the result] of the friendly-hostile division of labour among scientists\" (p. 95). I argue that:
Critical metascience can play an important part in Popper's \"friendly-hostile division of labour\" by offering a special type of external criticism that exposes and challenges potential biases and dogma in metascience in order to improve its objectivity and approach.
Rubin, M. (2026). What is critical metascience and why is it important? Frontiers in Psychology, 17:1860740. https://doi.org/10.3389/fpsyg.2026.1860740
and colleagues (2016) published a comment on the Open Science Collaboration's (OSC; 2015) \"Estimating the reproducibility of psychological science.\" They concluded that:
Metascience is not exempt from the rules of science. OSC used a benchmark that did not take into account the multiple sources of error in their data, used a relatively low-powered design that demonstrably underestimates the true rate of replication, and permitted considerable infidelities that almost certainly biased their replication studies toward failure. As a result, OSC seriously underestimated the reproducibility of psychological science.
Consistent with Gilbert et al.'s (2016) view, reviews of more recent well-powered, high quality replication studies have found much higher replication rates than the OSC's original estimate of 36%. For example, Nosek et el.'s (2022) review of 307 replication studies found a replication rate of 64%, Cobey et al.'s (2023) review of 116 replication studies found a replication rate of 71%, and Tyner et al.'s (2026) test of 274 claims found a replication rate of 55%. Based on these more recent estimates, the observed replication rate appears to be around 63% rather than 36%.
Is a 63% replication rate grounds for a \"crisis\"? As I've discussed recently, it depends on what you expect the replication rate to be. Glibert et al. also raised concerns about the \"correct benchmark\" in their follow-up article, arguing against a purely statistical interpretation based on random sampling error per se:
The correct benchmark must recognize all genuine sources of variability and cannot be limited to the fiction that the only way in which the replications differed from the originals was that they drew different subjects from the identical population.
A key challenge for future work which claims to have found \"low\" replication rates is to explain and justify an \"acceptable,\" \"optimal,\" or \"expected\" replication rate (see also Rubin, 2023).
Gilbert, D. T., King, G., Pettigrew, S., & Wilson, T. D. (2016). Comment on \"Estimating the reproducibility of psychological science\". Science, 351(6277), 1037-1037. https://doi.org/10.1126/science.aad7243
Through user experience research (UXR) initiatives that take into account our diverse membership and community, we can have a continuous, deeper understanding of the role of metadata in our members' workflows, and ensure that our work continues to meet our community's needs. Your support is the key to this process, and will positively impact the wider community - and if you'd like to start today, you can take part in our latest initiative: help us improve our Events page by sharing your thoughts on the page's feedback form.
\nHi, everyone! I'm Leandro Contreras, UX Researcher here at Crossref, since February 2026. In previous roles, I helped to design, build and manage digital products and workflows for universities and academic publishers, and now I'm dedicated to bridging the gap between our community's needs and the tools we build together.
\nAt Crossref, we're committed to collecting diverse community input, and ensuring our system is representative and useful for everyone that interacts with it. In this blog post, I'd like to introduce you to how we're kickstarting a more systematic approach to user research processes at Crossref, and invite you to take part in a new research initiative. First, let's quickly revise some key concepts:
\nUser experience (UX) is the exploration of how we, as humans, interact with products and services: whether that's a physical tool or, in our case, the invisible systems holding our metadata, or the visible interfaces that support our community - for example, our Participation Reports.
\nGood user experience can positively affect people's day-to-day lives, produce quality results, and champion inclusion: we are more likely to return to a product or a service if it's tailor-made for us, for our advantages and shortcomings.
\nUser experience research (UXR) is the methodical study of users of a product, service or system, using methods to learn about their behaviours, needs, and preferences. While user experience is the design of the experience, UXR is the evidence-based study used to inform those designs and prove they actually work.
\nIn practice, user experience researchers gather this evidence through a variety of methods that seek to capture quantitative and qualitative data. But what are these methods? And how do they apply in the context of an organisation like Crossref, with a growing membership building the research nexus with rich metadata using many different technologies?
\nTo understand the role and the impact of metadata across our vast community, we are currently mixing qualitative and quantitative research methods to help us get the right answers:
\nIn 2026, we've already put these methods to work:
\nLooking ahead, we'll continue setting up usability testing sessions, open quick feedback channels on our website, and investigate the impact of research integrity across our membership through surveys. However, these initiatives are only as effective as the community behind them! When you engage in our UXR initiatives, you actively shape current and future Crossref experiences, ensuring they fit your needs.
\nIf you are curious about participating, we've just launched a new feedback form on our Events page to detect new improvement opportunities, and we invite you to be part of it. This is a great opportunity to see how our initiatives work in practice, so we hope you'll jump in!
\n\n
\n
\nOver time, you will see the impact of your participation come to life in future improvements to our tools and services through future project updates on our blog, and in the community forum as well. We welcome everyone to join the conversation there. If you have any further questions, suggestions, or collaboration ideas, you can also get in touch via email.
Launching new UX research initiatives at Crossref has been a wonderful way to get to know our community on a deeper level. I'm looking forward to bringing you closer to more initiatives in the future, and learning more from your feedback!
","doi":"https://doi.org/10.64000/je02r-h4q75","guid":"https://doi.org/10.64000/je02r-h4q75","image":"https://www.crossref.org/images/blog/2026/event-page-survey.png","language":"en","license":"https://creativecommons.org/licenses/by/4.0/legalcode","published_at":1782950400,"rid":"ntp8j-ctq03","summary":"Through user experience research (UXR) initiatives that take into account our diverse membership and community, we can have a continuous, deeper understanding of the role of metadata in our members' workflows, and ensure that our work continues to meet our community's needs.","tags":["Crossref","UX Research"],"title":"Take part in UX Research at Crossref","updated_at":1783009813,"url":"https://www.crossref.org/blog/take-part-in-ux-research-at-crossref/","version":"v1"},{"authors":[{"contributor_roles":[],"family":"LaZerte","given":"Steffi","url":"https://orcid.org/0000-0002-7690-8360"}],"blog":{"authors":[{"name":"The rOpenSci Team"}],"community_id":"19c501a7-647b-4a11-9f5e-cf400817cce3","created":1780876800,"current_feed_url":null,"description":"Open Tools and R Packages for Open Science","favicon":"https://rogue-scholar.org/api/communities/19c501a7-647b-4a11-9f5e-cf400817cce3/logo","feed_format":"application/feed+json","feed_url":"https://ropensci.org/blog/index.json","filter":null,"generator":"Other","home_page_url":"https://ropensci.org/blog","issn":null,"language":"eng","license":"https://creativecommons.org/licenses/by/4.0/legalcode","prefix":"10.59350","relative_url":null,"secure":true,"slug":"ropensci","status":"active","subfield":"1710","title":"rOpenSci - open tools for open science","updated":1782995896,"use_api":null},"blog_name":"rOpenSci - open tools for open science","blog_slug":"ropensci","content_html":"I recently had the opportunity to learn what the term \"Nerd Sniping\" meant.Ma\u00eblle pointed out a conversation on the rOpenSci Slack about something called Vale, meant for text linting.I'd seen the comment, but honestly hadn't really understood what it was all about until Ma\u00eblle asked if I thought it'd be useful for editing the blog\u2026
\u2026time passes\u2026
About three days later, I've hardly finished any of the blog post reviews I was planning to do.I've been sucked down a rabbit hole of Vale setup, custom rules, and overrides.
It turns out that \"Nerd Sniping\" refers to the practice of throwing problems at nerds that distract them from what they were doing.
That being said, it was a glorious hole to fall down!It was just too bad that Ma\u00eblle sniped me two more times by asking me about my spell check setup in Positron and then by asking if Panache would help with translations.
I was pretty slow at my editorial duties that week!But I did come out of the dive with a great editorial setup which will definitely save me time in future.
I've edited a lot of posts on the rOpenSci blog.I take pride in helping writers get their ideas across with clarity, while not losing their own style.I'm an opinionated editor, so I also try hard to ensure that writers understand when my suggestions are just my opinion, and when I think there are mistakes in style or content that really do need to be fixed.I am also fussy about the details, about being consistent with capitalizations, about keeping ideas logically ordered, and about making sure that readers without the same background might still understand the gist of the post1.
As such, my post reviews can get a bit lengthy and it's not unreasonable for me to have 20-30 comments on a standard post.That's not too problematic, but if I had to complain it might be about the technical edits, like fixing the capitalization of 'rOpenSci'2, ensuring headings are in sentence case, and that links to ropensci.org pages are relative.These aren't complicated fixes, but if you have to remember to keep an eye out for them, and then create a GitHub PR review suggestion for each fix, it can become a tad tedious.
Ma\u00eblle's timely sniping helped me finalize my collection of tools to help streamline editorial tasks.
All of these tools can be installed and used in different ways.They are also powerful with many different possible customizations and configurations.Here, I'll share with you how I use these tools as extensions in Positron to help make it easier to write and edit posts for the rOpenSci blog.Hopefully this inspires you to explore how you might set them up to support your workflows!Further, if you're interested in setting up your own tools, perhaps you want to check out this blog post on \"All the Ways to Programmatically Edit or Parse R Markdown / Quarto Documents\".
For each tool, you'll want to install the Positron extension, and then set up your configuration.Configurations can usually be specified at three different levels:
roweb3, for the rOpenSci blog).More specifically here are (some) of the locations/names for configuration files and links to their documentation sections for more details.
| Level | cSpell | Vale | Panache |
|---|---|---|---|
| User | Positron settings | .vale.ini in any parent dir. or global config | ~/.config/panache/config.toml |
| Project | .cspell.json | .vale.ini | .panache.toml |
| File | Inline Comments | Inline Comments | Inline Comments |
This means you can have different rules for different projects, and override them as needed.In the following examples, I'll show you how I do this for posts on the rOpenSci blog.
First is my spell checker, which probably doesn't need much explanation.However, it's nice to use a spell checker which also works on code.I use the Code Spell Checker (cSpell) extension by Street Side Software and installed the languages extensions individually:
Alternatively, you could also install the cSpell Bundled Dictionaries instead.
To configure this extension, I added two types of files: a project-level configuration file, and two dictionaries of words to consider 'correct'.
The project level configuration file, .cspell.json, lists languages to use for different files (to ensure index.es.md files go through the Spanish spellchecker, while index.pt.md files go through the Portuguese spellchecker, etc.).It also includes a list of globs for file paths we can ignore (I'm really not interested in spelling mistakes in the .git folder), as well as pointing to dictionaries.
These dictionaries are initially created by functions from my promoutils package, an R package for all my rOpenSci community workflows.wordlist_create() creates a wordlist based on rOpenSci packages and author names, so they don't trigger the spell check if they aren't recognized.wordlist_update() updates this list with new names as needed.
We keep these dictionaries in a .wordlists folder.Names are stored in the .wordlists/names.txt file, and we also have a .wordlists/words.txt file which stores words which are considered correct in the rOpenSci context (like 'usecases').
I should also note that I have a personal list of user words stored in my Positron user settings which lists words (like my name!)which I want to be considered correct across all projects.
When writing posts, we can also override the language settings within a post using a special comment.For example if we want to use English and Portuguese for a post we could add <--- cSpell: language en,pt--> to the document.
We can also include post-specific words to ignore, which is handy for acronyms.For example, if we wanted to ignore the acronym CSCW we could use <!--- cSpell: ignore CSCW ---> at the top of a post.
Spell check issues pop up as a warning in my text window, or as a list under \"Spell Checker Issues By File\" my lower window pane so I can review them, add them to word lists, or just mentally ignore them.
For linting text (checking the style and meaning of the words) I use the Vale VSCode extension by chrischinchilla5.Vale helps me check that the Blog Style rules are respected, and gives suggestions for alternative word choices to avoid common mistakes (such as words or expressions which might be derogatory).
To setup Vale I created a project-specific Vale configuration file .vale.ini6 in the roweb3 repository.I keep my personal .vale.ini file in a higher level folder that holds all my R projects.In addition to the Vale configuration file, I also created a Vale styles folder in roweb3/.vale-styles.This is where Vale rules are installed if we use predefined rules, and where I can put rOpenSci-specific rules for the blog.The first time you use Vale you'll want to run vale sync in the terminal to install the standard, non-custom, rules.I .gitignore all rules which are installed, but track and push custom rules.
Vale is where I've made the most customizations, especially with the rOpenSci Blog.
This is just the start!I imagine the more I use these rules the more fine tuning I'll do.
Vale problems are classified as messages, warnings, or errors, and are highlighted in the text window as a quick fix and listed in the Problems pane in my lower window.
I should also note that for all the rules I've disabled, there are a lot of opinionated rules left.We keep them as prompts to think about our writing, not because we must follow them!
Vale's write-good rule doesn't want me to start a sentence with 'There is', but I'm going to anyway!
For formatting text, I use the Panache extension by jolars to format the (R)markdown files for the blog.This is probably the smallest amount of setup, as all we need is a minimal .panache.toml configuration file in the roweb3 repository.However, this file instructs Panache to do one super awesome thing for us, especially for translations of multilingual blog posts:
[format]wrap = \"sentence\"If you set up Positron to format on save, Panache automatically wraps text by sentence every time you save the file.This means that when a blog post is sent for a first pass translation using babeldown, the translation comes back pretty good.Alternatively, if the line breaks are in the middle of a sentence, the translation can become garbled as lines are treated as disjointed sections of text.
For my other work, I use wrap = \"reflow\", set in my user configuration file in ~/.config/panache/config.toml.
Finally, once I've got all the fiddly edits on a post's (R)md file ready to go, I use the GitHub Pull Requests extension to convert these edits to GitHub PR review suggestions.This is really handy if you find yourself making many small suggested changes to GitHub PRs.
To review blog posts, I fetch the PR with usethis::pr_fetch(), and then open the blog post (R)md file in Positron side by side with the html preview of the post in my web browser.
Then I review the html preview and make the edits directly in the (R)md file.When I'm done, I right click on the edited file name in the Source Control > Changes and select Create Pull Request Suggestions.
This converts my edits to GitHub PR review suggestions which I can then review in Positron, or as I prefer, in a web browser (and fix weird ones, such as suggestions which delete part of a section in one edit but add it back in the next; it's not always a perfect process).Once all the suggestions are converted, the extension asks me if I want to revert my changes (which I usually do).
A note of caution, I find this tool a bit confusing to use on a PR that has a lot of comments already.The comments it makes are sometimes hidden or split in odd ways and it's easy to accidentally create duplicates.In these situations it's sometimes easier just to make the suggestions in a browser as you might normally.
Each of these tools provides me a specific solution to a problem.There is some overlap among them; Vale could do spell checks, and Panache could do linting.However, I find that by using the tools separately I can achieve an especially detailed and customized setup that works really well with the rOpenSci blog in particular, and with my work in general.
By including the configuration files in the roweb3 repository, people who also use these tools will automatically use the configurations we've setup for the rOpenSci blog when they write a post.We also plan to add instructions for how to use these tools to the Blog Guide.This should give blog writers the option of using these tools if they would like to.
However, even if other writers don't use these tools, it's still very useful for me to see a list of potential problems to double check at the end of my review without having to remember to check for them manually.It means I can focus more on the review of the content rather than worry about whether it's Ropensci or rOpenSci \ud83d\ude04
Don't judge this post by these ideals, I said I'm a opinionated editor, writing is completely different \ud83d\ude09.\u00a0\u21a9\ufe0e
It's rOpenSci.Not Ropensci, not RopenSci and not ropenSci.\u00a0\u21a9\ufe0e
\"Linting\" with respect to text or prose means checking the style and meaning of the words.\u00a0\u21a9\ufe0e
I'm Canadian so generally follow Canadian spelling (a mix of British and American for those of you new to the complex world of English spelling differences).At rOpenSci, we generally just ask an author to pick one and stick to it.\u00a0\u21a9\ufe0e
There is also Vale by errata-ai, but this extension has been deprecated in favour of Vale VSCode.\u00a0\u21a9\ufe0e
If you get an error on startup, you may need to tell Vale where this is explicitly by modifying Projects' settings.json file to include \"vale.valeCLI.config\": \".vale.ini\"\u00a0\u21a9\ufe0e
For example, alex worries that the word \"Mexican\" might be used in a racist manner, but at rOpenSci, it's stated with pride and I don't want Vale to flag our community members for mentioning their nationality \ud83d\ude05\u00a0\u21a9\ufe0e
But awesomely, we can enforce this rule for English, but not Spanish posts!\u00a0\u21a9\ufe0e
Open Research soll der Standard f\u00fcr die Produktion, Vermittlung und Nachnutzung von Wissen in Berlin werden: Auf dieses strategische Ziel haben sich Vertreter*innen der Berliner Wissenschafts- und Kulturerbe-Einrichtungen in einem neuen Positionspapier geeinigt. Verfasst hat das Papier die Landesinitiative Open Research Berlin, der Prozess wurde durch das Open Research Office Berlin koordiniert. Hintergr\u00fcnde und Inhalt des neuen Papiers werden im Folgenden kurz erl\u00e4utert. Mit der Ver\u00f6ffentlichung startet eine \u00f6ffentliche Kommentierungsphase, so dass sich alle Interessierten einbringen und den Prozess mitgestalten k\u00f6nnen.
\n\nDie Landesinitiative Open Research Berlin ist ein Zusammenschluss von Berliner Wissenschafts- und Kulturerbe-Einrichtungen. Hervorgangen ist die Landesinitiative aus der 2014 vom Berliner Wissenschaftssenat einberufenen AG Open-Access-Strategie Berlin. Mit der Verabschiedung der\u00a0 Open-Access-Strategie Berlin (2015) durch das\u00a0 Berliner Abgeordnetenhaus wurde die Grundlage geschaffen, den offenen Zugang und eine umfassende Nutzbarkeit im Sinne von Open Access f\u00fcr Publikationen, Forschungsdaten und Kulturdaten zu etablieren. Ein weiterer wichtiger Schritt ist die Aufnahme von Open Research in das Berliner Hochschulgesetz (BerlHG): In Paragraph 41 werden Open Access und Open Science definiert und der Auftrag der Hochschulen beschrieben.
\nNun geht die Landesinitiative Open Research Berlin \u2013 gut zehn Jahre nach der Open-Access-Strategie \u2013 den n\u00e4chsten Schritt: Im neuen Positionspapier zur Entwicklung von Open Research in Berlin (2026) wurden in einem partizipativen Prozess zahlreiche Vorschl\u00e4ge erarbeitet, wie die Aktivit\u00e4ten zur F\u00f6rderung von Open Access auf Open Research ausgeweitet und Koordination und Kooperation im Berliner Forschungsraum weiterentwickelt werden k\u00f6nnen.
\nGrund daf\u00fcr ist, dass Open Research Wissenschaft besser, wirksamer, gerechter und resilienter macht. Daf\u00fcr brauchen die Wissenschafts- und Kulturerbe-Einrichtungen gezielte Investitionen in Infrastruktur, Qualifizierung und Anreizsysteme. Die Prinzipien von Open Research \u2013 Transparenz, Partizipation, Fairness und Diversit\u00e4t \u2013 sind f\u00fcr demokratische Aushandlung, Meinungsbildung und das Gemeinwohl der Stadtgesellschaft entscheidend. Auch deshalb braucht das Land Berlin ein koordiniertes Vorgehen zusammen mit den Wissenschafts- und Kulturerbe-Einrichtungen.
\nEine nachfolgende, gemeinsame Open\u2011Research\u2011Strategie von Land und Hochschulen, wie sie in den Hochschulvertr\u00e4gen 2024\u20132028 vereinbart wurde, soll die Forschungspotenziale Berlins im Bereich Wissenschaft und Kulturerbe besser erschlie\u00dfen und die Standortvorteile st\u00e4rken. Das nun von der Landesinitiative ver\u00f6ffentlichte Positionspapier dient als Diskussionsgrundlage f\u00fcr die Ausarbeitung dieser gemeinsamen Strategie.
\nNeben der Open\u2011Access\u2011Strategie von 2015 st\u00fctzt sich die Landesinitiative f\u00fcr ihr Verst\u00e4ndnis von Open Research auf das Berliner Hochschulgesetz (2021) sowie auf die UNESCO\u2011Empfehlung zu Open Science (2021). Daraus ergibt sich unter anderem der Anspruch der Landesinitiative, die Bereiche Wissenschaft und Kultur gleichwertig zu adressieren und bei der Formulierung der strategischen Ma\u00dfnahmen gemeinsam zu ber\u00fccksichtigen (vgl. S. 4).
\nZur Entwicklung eines gemeinsamen Forschungsraums in Berlin sind die Prinzipien von Open Research von zentraler Bedeutung. Nach einer Analyse der derzeitigen Situation, Bedarfe und Potentiale f\u00fcr Open Research am Standort Berlin identifiziert die Landesinitiative drei Standortvorteile f\u00fcr Wissenschaft und Kultur (S.5-6):
\nOffene und kooperativ getragene Informationsinfrastrukturen sieht die Landesinitiative als wesentliche Voraussetzung daf\u00fcr, damit die Berliner Wissenschafts- und Kulturerbe-Einrichtungen ihre digitale Handlungsf\u00e4higkeit und Unabh\u00e4ngigkeit erhalten und st\u00e4rken k\u00f6nnen. Konkret fasst das Positionspapier den Handlungsbedarf in vier \u00fcbergreifenden Themen mit insgesamt neun Zielen zusammen. Jedes Thema enth\u00e4lt zwei bzw. drei Ziele:
\nThema 1: Kulturen der Offenheit
\n\"Verbesserte strukturelle Bedingungen gew\u00e4hrleisten die Anerkennung von Open Research.\"
Thema 2: Souver\u00e4ne Wissens\u00f6kosysteme
\n\"Die kooperative, selbstbestimmte und nachhaltige Gestaltung bedingt die St\u00e4rkung und Resilienz offener Informationsinfrastrukturen.\"
Thema 3: Faire Finanzierung
\n\"Eine transparente Finanzierung ber\u00fccksichtigt Prinzipien der Offenheit und Wissensgerechtigkeit.\"
Thema 4: Open Research Monitoring
\n\"Open Research wird in diversen Kontexten mit angemessenen Methoden begleitet, beobachtet und dokumentiert.\"
Die einzelnen Ziele werden jeweils in weniger Abs\u00e4tzen pr\u00e4gnant dargestellt und mit konkreten Vorschl\u00e4gen f\u00fcr geeignete Ma\u00dfnahmen konturiert. Das Thema Open Research ist \u00e4u\u00dferst facettenreich, ber\u00fchrt mindestens die Dom\u00e4nen Wissenschaft und Kultur und umspannt prinzipiell alle Zyklen des Forschungsprozesses. Aufgrund dieser Komplexit\u00e4t schl\u00e4gt die Landesinitiative in dem Positionspapier die Bildung von einrichtungs\u00fcbergreifenden Arbeitsgemeinschaften vor, die im weiteren Verlauf Ma\u00dfnahmen in einer Agenda konzipieren und bei der Umsetzung verfolgen.
\nFachgemeinschaften und die interessierte \u00d6ffentlichkeit erhalten die M\u00f6glichkeit, das Positionspapier zu begutachten, zu kommentieren und sich auf diese Weise jetzt und im weiteren Prozess einzubringen. Das Positionspapier wird daher unter anderem auf der Plattform PubPub ver\u00f6ffentlicht. Dort steht es allen Interessierten f\u00fcr ein Open Peer Review zur Verf\u00fcgung.
\nDie Landesinitiative Open Research Berlin ver\u00f6ffentlicht das Positionspapier in diesen zwei Versionen:
\nLandesinitiative Open Research Berlin (2026): Offenheit als Grundsatz. Positionspapier zur Entwicklung von Open Research in Berlin. Version zur \u00f6ffentlichen Kommentierung. https://doi.org/10.21428/986c5d43.0a4300d5\n\nalternativ zum DOI f\u00fchrt dieser Link zum PubPub: https://oabb.pubpub.org/pub/positionspapier-open-research-berlin/release/1\n
Landesinitiative Open Research Berlin (2026): Offenheit als Grundsatz. Positionspapier zur Entwicklung von Open Research in Berlin. http://dx.doi.org/10.17169/refubium-52664.\nZur Erl\u00e4uterung des bisherigen Konsultationsprozesses ver\u00f6ffentlicht das Open Research Office Berlin ein kurzes Addendum:
\nNeufend, Maike & Georg Fischer (2026): Konsultationsprozess f\u00fcr das Positionspapier zur Entwicklung von Open Research in Berlin. Open Research Office Berlin. https://oabb.pubpub.org/pub/open-research-strategie-konsultation/release/1.\nOpen Research Office Berlin (OROB) – Landeskoordinierungsstelle f\u00fcr offene Wissenschaft
\nc/o Freie Universit\u00e4t Berlin, Universit\u00e4tsbibliothek, Garystra\u00dfe 39, 14195 Berlin
E-Mail: team[at]open-research-berlin.de
\nWebsite: www.open-research-berlin.de
Zitierhinweis f\u00fcr diesen Blogpost:\n\nNeufend, M. (2026): Berliner Landesinitiative ver\u00f6ffentlicht Positionspapier zur Entwicklung von Open Research. Open Research Blog Berlin. https://doi.org/10.59350/095nq-pd042.","doi":"https://doi.org/10.59350/095nq-pd042","guid":"https://blogs.fu-berlin.de/open-research-berlin/?p=4167","image":"https://blogs.fu-berlin.de/open-research-berlin/files/2026/07/Positionspapier_Open-Research-Berlin_Seite_01-250x352.jpg","language":"de","license":"https://creativecommons.org/licenses/by/4.0/legalcode","published_at":1782950400,"rid":"sw2dq-p4m13","summary":"Open Research soll der Standard f\u00fcr die Produktion, Vermittlung und Nachnutzung von Wissen in Berlin werden: Auf dieses strategische Ziel haben sich Vertreter*innen der Berliner Wissenschafts- und Kulturerbe-Einrichtungen in einem neuen Positionspapier geeinigt. Verfasst hat das Papier die Landesinitiative Open Research Berlin, der Prozess wurde durch das Open Research Office Berlin koordiniert.","tags":["Aktuelles","Landesinitiative Open Research Berlin","Open-Access-Strategie Berlin","Open-Research-Strategie Berlin"],"title":"Berliner Landesinitiative ver\u00f6ffentlicht Positionspapier zur Entwicklung von Open Research","updated_at":1782998091,"url":"https://blogs.fu-berlin.de/open-research-berlin/2026/07/02/landesinitiative-open-research-berlin-positionspapier/","version":"v1"},{"authors":[{"affiliation":[{"id":"https://ror.org/0153tk833","name":"University of Virginia"}],"contributor_roles":[],"family":"Turner","given":"Stephen D.","url":"https://orcid.org/0000-0001-9140-9028"}],"blog":{"authors":[{"name":"Stephen Turner"}],"community_id":"382941a7-2ffa-41df-8bbb-5f772188517f","created":1780876800,"current_feed_url":null,"description":"A practicing data scientist's take on AI, genomics, biosecurity, and the ways AI is reshaping how science gets done. Weekly updates from the field. Occasional notes on programming.","favicon":"https://rogue-scholar.org/api/communities/382941a7-2ffa-41df-8bbb-5f772188517f/logo","feed_format":"application/rss+xml","feed_url":"https://blog.stephenturner.us/feed","filter":null,"generator":"Substack","home_page_url":"https://blog.stephenturner.us","issn":null,"language":"eng","license":"https://creativecommons.org/licenses/by/4.0/legalcode","prefix":"10.59350","relative_url":null,"secure":true,"slug":"stephenturner","status":"active","subfield":"1311","title":"Paired Ends","updated":1782983063,"use_api":null},"blog_name":"Paired Ends","blog_slug":"stephenturner","content_html":"
It's a holiday week here in the US but not a quiet one. I'll be glamping at the lake tomorrow so this one's coming a day early. June 30 was a busy day for AI in science. OpenAI posted a genomics benchmark, Anthropic shipped Claude Science and brought Fable 5 back online, and I spent a good chunk of the day test driving Claude Science myself before starting my AI Dry July.
In any case, here are the five things that interested me the most this week.
OpenAI builds a genomics benchmark
RAND asks whether LLM agents can drive biological tools
David Brooks on who thrives once intelligence gets cheap
NIH's 235-word screen, and a list to check your abstract against
QED scores preprints and names the top 1%
OpenAI's Jeremiah Li and Andrew Ho posted GeneBench-Pro on bioRxiv, an expanded version of GeneBench. OpenAI also wrote a blog post about it.
Li, J. H. & Ho, A. J. GeneBench-Pro: Evaluating Multistage Statistical Reasoning in Genomics, Quantitative Biology, and Translational Biomedicine. 2026.06.29.735386 bioRxiv Preprint at https://doi.org/10.64898/2026.06.29.735386 (2026).
It's 129 problems across 10 domains with a genomics core. Each one hands an agent a short bit of context and a target quantity to estimate, then makes it work through a series of dependent decision points. These decision points are the kind of inferential forks where one plausible wrong turn can reshape everything that comes downstream. The point is to test whether a model can run a realistic multi-stage analysis end to end and not just answer multiple choice questions (though some multiple choice questions can be challenging!).
The scores: GPT-5.6 Sol Pro tops out at 31.5%, GPT-5.6 Sol at 28.7%, GPT-5.5 at 12%, and the best non-GPT model, Claude Opus 4.8, at 16%. OpenAI wrote a benchmark, ran its own models on it, and reported that they win. Worth saying plainly IMHO. In fairness, they released some problems publicly and gave many others to Artificial Analysis for independent scoring, which is more transparency than most self-graded benchmarks bother with.
There's lot's of buzz about GLM 5.2 lately, so I was a little surprised to see it rank so low compared to other models here.
Failure modes are interesting. The models often do most of the workflow correctly, then show what the authors call \"a consistent gap between noticing and acting\": they flag a diagnostic signal but don't carry its implication over to the decision it should change, so they pick the wrong estimator or stay on a plausible but wrong path.
That matches what I saw in my Claude Science test drive the same day. It collected the data and ran the analysis without much help, and a quick read through its code turned up several spots where it had assumed something I wouldn't have.
The timing was crowded. This dropped alongside Claude Science and the Fable 5 redeployment. If you use Fable 5, note the cost change: it's included for up to half your weekly usage through July 7, then it runs on metered usage credits after that.
Fable 5 will be included for up to 50% of weekly usage limits through July 7, after which it will be available via usage credits.
RAND's Center on AI, Security, and Technology (CAST) tested 7 frontier LLM agents on two questions: can they pick the right computational biology tool for a task, and can they operate one (report, PDF).
Lee, J. et al. Can LLM Agents Select and Engage with Biological Tools? An Initial Biosecurity Assessment. https://www.rand.org/pubs/research_reports/RRA4741-1.html (2026).
The case studies used EVEscape, which predicts immune escape, on influenza hemagglutinin and Lassa GPC, and ESM3, a protein design model, on GFP and influenza HA.
Asked to name the right tool for a stated function, the models did well, many around 80%. Put the same question inside a realistic biological workflow and accuracy fell across the board. Operating the tools was mixed and depended on the specific protein, and when the agents failed it was usually because they mishandled data or fumbled an autonomous step, not because they lacked the knowledge. Feeding an agent more biological detail didn't reliably help, and on the HA-targeted ESM3 task more information sometimes made things worse, which undercuts the tidy \"expertise plus AI equals uplift\" story.
And the closed-weight models refused a lot, especially on viral proteins and obvious dual-use requests, through either the model declining or a content filter catching it. Agents can already handle the front end of this work, that could lower the expertise barrier for a non-expert, and it deserves closer testing. This is an initial assessment on toy tasks, and they say so, so I'd strongly resist reading it as evidence that agents can build a functional biological weapon.
David Brooks, writing in The Atlantic, starts with the observation that AI hasn't handed anyone a 15-hour workweek.
The People Who Will Thrive in the AI Age: What will differentiate people is not how smart they are but their relationship to mental effort.
He cites ActivTrak data showing that when workers adopted AI their email and chat time more than doubled, their business software use rose 94%, and their focused, uninterrupted work fell 9%, plus a Berkeley Haas finding that people started pulling previously-outsourced tasks back in-house because AI made them easy.
My favorite line in the essay:
When intelligence is plentiful, volition is valuable.
He sorts people into three groups. Productive Passengers, low appetite for hard thinking, get more done and get hollowed out. Reluctant Optimizers mean to resist and get pulled in anyway. Mental Marathoners push back and use AI to widen their range rather than shrink it. Behind the hollowing-out worry he stacks a pile of studies: an MIT Media Lab result where brain connectivity dropped by half during ChatGPT-assisted tasks, a colonoscopy study where physicians' adenoma detection fell after the AI was taken away, and a Wharton experiment where people accepted a deliberately-wrong model's answers 80% of the time.
Some good practical advice at the end. Ask for hints instead of answers, write your own take on a blank page before you open the chat, and \"ask for thinkers, not thinking,\" meaning have the model summarize who has already worked on your problem so you can go read them. I started my AI Dry July this week, so I'll report back on whether a month of added friction does anything measurable for my gamma waves.
Max Kozlov at Nature reports that hundreds of NIH grant applications are stuck in a screen that runs after peer review. An algorithm checks each application's title, abstract, and summary sections against a list of disfavored terms, 235 of them as of February, including \"gender,\" \"climate change,\" \"racism,\" and \"fossil fuel.\" A hit flags the application, and the program officer is then told to renegotiate the language or drop the project.
This screen runs after two rounds of peer review and after the program officers and the institute director have already judged the work fundable. Then it enters a phase called Status 19, where NIH leaders and an HHS counselor can weigh in, with internal feedback that Nature obtained questioning whether a given study is worth funding because it looks \"likely to end up in a Congressional waste report.\" Most applications clear in two weeks, but a tenth of the renewals that reached this phase this fiscal year have sat for more than seven weeks, some indefinitely. NIH told Nature it keeps no banned-word list and doesn't base funding on specific words; the internal documents suggest flagged projects simply draw far more scrutiny.
I pulled the 235 terms out of the article into a searchable page, with the CSV on GitHub, so you can run your own grant proposal against it. You can also search/page through the flagged terms below.
QED Science ran its QED Score, an anonymized AI metric for a manuscript's originality and validity, across 57k bioRxiv preprints from May 2025 to April 2026 and named the top slice The 1%. Their whitepaper reports three validation studies: an AUC of 0.867 separating expert-labeled \"Limited\" papers from the rest on a 925-paper set, a Spearman \u03c1 of 0.63 between a preprint's score and the SJR of the journal it eventually landed in (scored with models whose knowledge cutoffs predated the corpus, to rule out contamination), and a blinded head-to-head where experts sided with the QED-favored paper in 75% of 60 decisive judgments.
I've been building my own peer-review skill in the open on the theory that most of these products are a frontier model wrapped in a good SKILL.md plus some connectors, and I'd rather that scaffolding be something the rest of us can see and fork.
A few other tabs I have open that I'll get to here soon.
created a refusal benchmark for biosecurity risk assessment (result, paper, blog). I wrote about refusal theater here a few weeks ago.
The Hitchhiker's Guide to Agentic AI: From Foundations to Systems
Autodata: An agentic data scientist to create high quality synthetic data
Paper mill cancer studies get double the number of citations as genuine papers
Lab-created 'SpudCell' marks 'stunning' step toward building life from scratch
Am 24. M\u00e4rz 2026 entschied das Bundesverfassungsgericht nach 12-j\u00e4hrigem Verfahrensgang, dass das Land Baden-W\u00fcrttemberg keine gesetzliche Zweitver\u00f6ffentlichungspflicht f\u00fcr wissenschaftliches Personal festlegen darf. Diese Entscheidung hat nicht nur unmittelbare Folgen f\u00fcr Hochschulsatzungen, die auf der Landesnorm beruhen. Sie wirft auch weitere, die Stellung von Open Access als vermeintliche Gegenspielerin des Urheberrechts betreffende Fragen auf. Hier werden die Hintergr\u00fcnde der Entscheidung, deren Inhalt und offene Fragen zusammengefasst.
\nDas Land Baden-W\u00fcrttemberg f\u00fchrte im Fr\u00fchjahr 2014 Paragraf 44 Absatz 6 Landeshochschulgesetz (LHG BW) ein. Dieser forderte Hochschulen auf, ihre Angeh\u00f6rigen zu der Zweitver\u00f6ffentlichung ihrer wissenschaftlichen Beitr\u00e4ge ein Jahr nach deren Erscheinen zu verpflichten. Die Idee des Landes zur Schaffung einer Zweitver\u00f6ffentlichungspflicht hat ihren Ursprung in Paragraf 38 Absatz 4 des Urheberrechtsgesetzes (UrhG). Dieser erlaubt es Urheberinnen eines wissenschaftlichen Beitrags unter gewissen Umst\u00e4nden, nach Ablauf von zw\u00f6lf Monaten diesen Beitrag in der Manuskriptversion \u00f6ffentlich zug\u00e4nglich zu machen, auch wenn dem urspr\u00fcnglichen Ver\u00f6ffentlichungsorgan das ausschlie\u00dfliche Nutzungsrecht \u00fcbertragen wurde. Das UrhG unterst\u00fctzt damit die Open Access-Bestrebungen in der Wissenschaft. Der Aufforderung der Regelung einer Zweitver\u00f6ffentlichungspflicht kam die Universit\u00e4t Konstanz in ihrer Satzung nach.
\nGegen die Regelungen in LHG BW und Satzung regte sich Widerstand bei einigen Professor*innen. Diese wendeten sich gegen die Satzung vor dem Verwaltungsgerichtshof. Sie beanstandeten einen unzul\u00e4ssigen Eingriff in das Grundrecht der Wissenschaftsfreiheit aus Artikel 5 Absatz 3 Grundgesetz durch die Zweitver\u00f6ffentlichungspflicht.
\nDagegen und f\u00fcr die Satzung und baden-w\u00fcrttembergische Norm argumentierte der Rechtsbeistand der Universit\u00e4t Konstanz: Diese habe keine Urheberrechte beschnitten, sondern lediglich f\u00fcr die ihnen Dienstverpflichteten die Aus\u00fcbung des Zweitver\u00f6ffentlichungsrechts aus dem Urheberrechtsgesetz geregelt. Es ginge bei der Norm nicht um die freie Zug\u00e4nglichkeit der urheberrechtlich gesch\u00fctzten Werke, sondern der darin enthaltenen gemeinfreien Information. Mit dieser Argumentation sah der Rechtsbeistand der Uni Konstanz keine Probleme durch eine Beschneidung der Gesetzgebungskompetenz des Bundes, da die Regelung nicht das Urheberrecht im eigentlichen Sinne betreffe.
\nDer Verwaltungsgerichtshof setzte das Verfahren aus und zur konkreten Normenkontrolle an das Bundesverfassungsgericht.
\nDer zweite Senat des Bundesverfassungsgerichts hatte dann die formelle Frage zu beantworten: Hatte das Land Baden-W\u00fcrttemberg \u00fcberhaupt die Gesetzgebungskompetenz zum Erlass einer Norm, die eine Zweitver\u00f6ffentlichungspflicht vorsieht?
\nDas Bundesverfassungsgericht entschied nun in seinem Beschluss: Nein, das Land Baden-W\u00fcrttemberg h\u00e4tte eine solche Norm nicht erlassen d\u00fcrfen, da die Regelung einer Zweitver\u00f6ffentlichungspflicht den Bereich des Urheberrechts betrifft, und somit ausschlie\u00dflich durch Bundesgesetz geregelt werden darf.
\nDas Gericht sieht in der baden-w\u00fcrttembergischen Norm \u2013 anders als der Verfahrensbeistand der Universit\u00e4t Konstanz \u2013 eine urheberrechtliche Regelung, weil die in Paragraf 44 Absatz 6 LHG BW geregelte Zweitver\u00f6ffentlichungspflicht die Aus\u00fcbung des urheberrechtlichen Zweitver\u00f6ffentlichungsrechts steuere und die durch das Zweitver\u00f6ffentlichungsrecht gegebene Entscheidungsfreiheit von Urheberinnen durch eine Pflicht ersetze.
\nDiese materielle Wirkung des Gesetzes war laut dem Gericht entscheidend f\u00fcr die Einordnung der baden-w\u00fcrttembergischen Norm als urheberrechtliche Norm.
\nOffen bleibt, ob die Norm unzul\u00e4ssig in das Grundrecht der Wissenschaftsfreiheit aus Artikel 5 Absatz 3 Grundgesetz eingreift. Dieses Grundrecht enth\u00e4lt auch die Publikationsfreiheit \u2013 also das Recht, die Rahmenbedingungen, wie Journal, Zeitpunkt und Verlag festzulegen und auch sich gegen eine Ver\u00f6ffentlichung der eigenen wissenschaftlichen Ergebnisse zu entscheiden. Zur Entscheidung dieser Frage kam das Bundesverfassungsgericht in seinem Beschluss nicht, die Pr\u00fcfung endete nach dem Ablehnen der formellen Verfassungsm\u00e4\u00dfigkeit.
\nAuch, welche Folgen die Verfassungswidrigkeit der baden-w\u00fcrttembergischen Norm f\u00fcr die Konstanzer Hochschulsatzung hat, hat das BVerfG nicht entschieden. Zwar sind Satzungen keine formellen Gesetze. Allerdings haben auch sie normative, also gesetzes\u00e4hnliche Wirkungen. Dar\u00fcber hinaus d\u00fcrfen Satzungen selbstverst\u00e4ndlich keine verfassungswidrigen Regelungen enthalten. In der Konsequenz wird die die Zweitver\u00f6ffentlichungspflicht betreffende Regelung in der Satzung ebenfalls wahrscheinlich nichtig sein.
\nDie Absage des Bundesverfassungsgerichts an eine landesrechtliche Regelung der urheberrechtlichen Ver\u00f6ffentlichung k\u00f6nnte zur Forderung verleiten, die Thematik bundesrechtlich zu regeln. Dies ist allerdings schwierig, da die Gesetzgebungskompetenz f\u00fcr dienstliche Vorgaben wissenschaftlicher Besch\u00e4ftigter gem\u00e4\u00df Artikel 70 Absatz 1 Grundgesetz bei den L\u00e4ndern liegt. Damit wird das generelle Regulierungsproblem in Bereichen, die die Wissenschaft und das Urheberrecht gleicherma\u00dfen betreffen, deutlich.
\nDie mutma\u00dflichen Folgen f\u00fcr die Konstanzer Satzung werfen auch die Frage auf, ob die Konsequenzen aus der Entscheidung des Bundesverfassungsgerichts auch auf Open Access Policies \u00fcbertragen werden m\u00fcssen. Hier m\u00f6glicherweise die vorsichtige Entwarnung: Open Access Policies werden voraussichtlich weiterhin mit dem Gesetz und der Verfassung vereinbar bleiben. Denn eine Policy ist in ihrer rechtlichen Verbindlichkeit von einer Satzung zu unterscheiden. Policies enthalten typischerweise \u2013 im Unterschied zu Satzungen \u2013 lediglich Empfehlungen, Richtlinien oder Standards. Sie sind also \u2013 vorbehaltlich eventueller Einzelf\u00e4lle \u2013 gerade nicht derartig rechtsverbindlich wie eine Satzung.
\nIn der Praxis kann es auch vorkommen, dass Open Access-Thematiken im Arbeitsvertrag geregelt werden. Hier bestehen zumindest keine Bedenken hinsichtlich der Kompetenz des Arbeitgebers, urheberrechtliche Sachverhalte arbeitsvertraglich zu regeln \u2013 dies ist g\u00e4ngige Praxis. Eine interessante und bisher nicht gekl\u00e4rte Frage ist allerdings, ob der Arbeitgeber eine Urheberin vertraglich zu einer Zweitver\u00f6ffentlichung im Open Access verpflichten kann. Hier ergibt sich das Potenzial eines Spannungsverh\u00e4ltnisses zwischen der arbeitsvertraglichen Regelung und dem Zweitver\u00f6ffentlichungsrecht aus Paragraf 38 Absatz 4 UrhG. Denn das Zweitver\u00f6ffentlichungsrecht der Urheberin darf nicht zu deren Nachteil abbedungen werden. Zwar stellt eine Zweitver\u00f6ffentlichungspflicht keine klassische negative Abweichung vom Zweitver\u00f6ffentlichungsrecht dar. Im Ergebnis entfaltet eine Zweitver\u00f6ffentlichungspflicht aber durchaus Wirkungen, die die Aus\u00fcbung des Zweitver\u00f6ffentlichungsrechts ber\u00fchren k\u00f6nnten. Ob diese und weitere Fragen zum Zweitver\u00f6ffentlichungsrecht zuk\u00fcnftig richterlich gekl\u00e4rt werden, bleibt abzuwarten.
\niRights.info\u00a0informiert und erkl\u00e4rt rund um das Thema \"Urheberrecht und Kreativit\u00e4t in der digitalen Welt\". Alle Texte erscheinen kostenlos und offen lizenziert.
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\nThe post Bundesverfassungsgericht: Absage an Zweitver\u00f6ffentlichungspflicht? appeared first on iRights.info.
","doi":"https://doi.org/10.59350/ktwqk-0bj52","guid":"https://irights.info/?post_type=custom_artikel&p=32856","language":"de","license":"https://creativecommons.org/licenses/by/4.0/legalcode","published_at":1782950400,"rid":"hefb9-fv643","summary":"Am 24. M\u00e4rz 2026 entschied das Bundesverfassungsgericht nach 12-j\u00e4hrigem Verfahrensgang, dass das Land Baden-W\u00fcrttemberg keine gesetzliche Zweitver\u00f6ffentlichungspflicht f\u00fcr wissenschaftliches Personal festlegen darf. Diese Entscheidung hat nicht nur unmittelbare Folgen f\u00fcr Hochschulsatzungen, die auf der Landesnorm beruhen.","tags":["Allgemein","Urheberrecht","Wissenschaft"],"title":"Bundesverfassungsgericht: Absage an Zweitver\u00f6ffentlichungspflicht?","updated_at":1782978078,"url":"https://irights.info/artikel/bundesverfassungsgericht-absage-an-zweitveroeffentlichungspflicht/32856","version":"v1"},{"authors":[{"contributor_roles":[],"family":"Wagen","given":"Corin","url":"https://orcid.org/0000-0003-3315-3524"}],"blog":{"authors":null,"community_id":"ee2393c0-2481-4a29-a7aa-0d1e0e423360","created":1693008000,"current_feed_url":null,"description":"My personal blog: chemistry, theology, metascience, and whatever else I'm thinking about.","favicon":"https://rogue-scholar.org/api/communities/ee2393c0-2481-4a29-a7aa-0d1e0e423360/logo","feed_format":"application/rss+xml","feed_url":"https://cwagen.substack.com/feed","filter":null,"generator":"Substack","home_page_url":"https://cwagen.substack.com","issn":null,"language":"eng","license":"https://creativecommons.org/licenses/by/4.0/legalcode","prefix":"10.59350","relative_url":null,"secure":true,"slug":"cwagen","status":"active","subfield":"1606","title":"Corin Wagen","updated":1782921020,"use_api":null},"blog_name":"Corin Wagen","blog_slug":"cwagen","content_html":"Something I've been thinking about recently is the information content of different biomolecules. While small molecules, peptides, antibodies, and oligonucleotides can all be valuable therapeutic assets in various contexts, they're strikingly different to synthesize, develop, and simulate. There are well-known reasons for many of these differences\u2014oligonucleotide synthesis can be highly automated, xenobiotic small-molecule metabolism proceeds through totally different pathways than peptide metabolism, and so on\u2014but at a high level I think many of these differences can be seen as downstream of the observation that small molecules have much higher information entropy per atom.
Information entropy, also known as Shannon entropy (after Claude Shannon), quantifies the amount of \"surprise\" associated with each new piece of data. A sequence like \"AAAAAAAAAAAAACAAAAA\" has low entropy, since almost every letter is A\u2014seeing another A gives us little new information, and so we can guess with pretty good odds that the next letter will be \"A.\" In contrast, a sequence like \"ACTAGGACATAAGACAGGCT\" has high entropy, since it seems that any position has four different possibilities. Since there are many possible sequences like this (just over a trillion for this length), each new letter conveys a lot of information about which particular sequence this is.
(This is a very brief introduction to Shannon entropy, and may be insufficient for those new to the topic\u2014you can find plenty of better ones on Google.)
For molecules, we can approximate the information content per atom as the base-2 logarithm of the number of possible molecules divided by the number of possible atoms. This definition lets us make some quick estimates for the per-atom entropy of different modalities:
There are 4 valid nucleotides, or two bits of entropy per nucleotide. If we approximate a nucleotide as having 20 heavy atoms, we find that an oligonucleotide contains 0.1 bits of entropy per heavy atom.
For proteins and other peptides, there are 20 valid amino acids, or 4.32 bits of entropy per residue. Assuming 8.3 heavy atoms per residue, this gives us a value of 0.52 bits of entropy per heavy atom.
Small molecules are a different story. The GDB-17 paper estimates that there are 166 billion druglike molecules with 17 or fewer heavy atoms, with the vast majority of these having 15\u201317 heavy atoms. This corresponds to 2.2 bits of entropy per heavy atom.
The small-molecule value quoted above may even be conservative: GDB-17 applies fairly conservative filters and doesn't include elements like S, P, B, and so on. If you take the oft-cited figure of 1060 possible drug-like molecules below 500 Da and approximate that as 35 heavy atoms, you arrive at a significantly larger value of 5.7 bits of entropy per heavy atom.
The markedly higher entropy of small molecules helps explain why small molecules are so tricky to synthesize. Fundamentally, any synthetic route must be specific and selective enough to disambiguate between virtually infinite numbers of potential products, which drives chemists to use complex and obscure reactions to achieve selectivity. Most approaches to simplifying small-molecule synthesis do so by vastly reducing the addressable space, enabling simple \"Lego brick\"\u2013style routes to be employed. While there are sure to be improvements in synthetic technology over the decades to come, I think that making arbitrary small molecules will continue to be a difficult and complex task for fundamental and unescapable reasons.
The high information content of small molecules also explains why they can be such effective drugs. The ability to pack so much information into a small number of atoms makes it possible to achieve impressive selectivity with a tiny molecule\u2014consider, e.g., the fact that you can have highly selective kinase inhibitors that are also small and non-polar enough to diffuse through the blood\u2013brain-barrier. This sort of thing just isn't possible with peptides!1
But the area where I've been thinking about this most is simulation and machine learning. It seems empirically true that it's much easier to predict or model protein\u2013protein binding than protein\u2013small molecule binding. While protein-binder design with models like BindCraft works well and metrics like ipSAE seem to correlate well with protein\u2013protein binding affinity, the analogous problems for small molecules still seem mostly unsolved (see e.g. Pat Walters' writing from last year).
I think that this is downstream of information content. While a 300-residue protein has just as much total information as any small molecule, the overall complexity of any individual region of intermolecular interactions is much lower. There are a relatively small number of chemically distinct groups in proteins\u2014indoles, imidazoles, amides, and so on\u2014and it's plausible that co-folding models or other biomolecular ML models can \"learn\" at a high level how these groups naturally interact with one another without needing to fundamentally understand the systems on the all-atom level. This means that learning to predict protein\u2013protein or protein\u2013oligonucleotide interactions is much easier than learning to predict protein\u2013small molecule interactions, perhaps many orders of magnitude easier.
In contrast, there are almost infinitely many such small-molecule functional groups\u2014pyridines, quinazolines, azaindoles, thiadiazoles, and so on\u2014each with different chemical properties and a different interaction profile with protein sidechains. This means that the data scarcity problem is much worse than it seems for small molecules, and makes me skeptical that purely ML-based approaches for predicting binding affinity will work in the medium term. (I may be wrong here!)
(How much data will it take to actually learn arbitrary interatomic interactions? It's hard to say for sure, but evidence from the neural-network-potential field suggests that it might take a lot. The OMol25 dataset comprises over 100 million DFT calculations with energy and per-atom force labels, so roughly 1\u201310 billion individual labels, and OMol25-trained models are the first models that seem to actually match the performance of physics-based methods on e.g. non-covalent interactions. While initiatives like OpenBind are promising and very valuable, I'm skeptical that even tens of thousands of new protein\u2013ligand complexes will be enough here.)2
I remain optimistic about the future of physics and physics-adjacent methods in small-molecule drug design for these reasons. Methods like quantum chemistry and FEP are able to avoid the training-data limitations of pure ML methods and show good generalizability for arbitrary small molecules. While I'm unbelievably excited about our new AI-powered scientific future, I think that the immense information content of small molecules puts fundamental limitations on what ML can accomplish, and means that (for better or worse) we're going to be stuck with physics for the foreseeable future.
Thanks to Ishaan Ganti and Ari Wagen for helpful discussions here.
Except for some peptides and other large molecules, which do diffuse through the blood\u2013brain barrier! Some of these seem to occur through active transport, but there's some mystery here still.
Note that there are many different potential forms of data, the shape of these problems is different, and there are other issues that make this comparison imperfect. I use this analogy simply to argue that we probably need a lot more data, not a little.
We are pleased to announce the release of OJS, OMP, and OPS 3.5.0-5, which has now been officially designated as a Long-Term Support (LTS) release. This release reflects our commitment to stability, reliability, and readiness for the tens of thousands of journals, presses, and preprint servers around the world that depend on PKP software every day.
\nBy designating 3.5.0-5 as our LTS release, we are committing to its ongoing maintenance for an extended period. This means users can adopt this version knowing it will continue to receive bug fixes and security patches in the near term.
\nIf you are unsure which version your installation is running, or want to understand how the 3.5 branch fits into PKP's broader release cycle (including how LTS and Short-Term Support (STS) releases relate to each other and what \"end of life\" means in practice) our PKP Software Releases page provides a clear overview, including a version support timeline and guidance on choosing the right version for your context.
\nIf your installation is currently running an earlier version of the 3.5 branch, upgrading to 3.5.0-5 is straightforward and strongly encouraged.
\nThis update addresses a collection of bug fixes and stability improvements identified since the previous release, informed by reports from our global community of users, developers, and hosted clients. While this is a maintenance release rather than a feature release, the fixes it contains address real issues affecting real publishing workflows.
\nThe full list of resolved issues is documented in the release notes on GitHub. We encourage system administrators and developers to review these notes as part of their upgrade planning.
\n\n\nA note for hosted clients: If PKP Publishing Services hosts your journal, press, or preprint server, contact us if you'd like to discuss the upgrade schedule for your installation.
\n
Running an up-to-date version of OJS, OMP, or OPS means your platform benefits from the latest bug fixes, remains compatible with third-party integrations and indexing services, and continues to meet the standards that authors, reviewers, and readers expect from a trustworthy publishing environment.
\nWe recognize that upgrades require planning, testing, and coordination, particularly for institutions managing multiple journals or operating with limited technical support. If you are currently running an older, unsupported version of OJS, OMP, or OPS, we encourage you to check the PKP Software Releases page to understand your version's support status and end-of-life date. Unsupported versions no longer receive bug fixes, security patches, forum assistance from PKP staff, or updates to documentation and translations. Our documentation, community forum, and hosting and support services are all available to assist you through the upgrade process.
\nCheck out PKP's News Blog post on \"Why upgrading is key to participating in open scholarly infrastructure\" for more reasons to upgrade.
\nDownloads for OJS, OMP, and OPS 3.5.0-5 are available now:
\n\nIf you are on a version earlier than 3.3, you must upgrade to 3.3 before you can upgrade to 3.5. Before upgrading, please review the upgrade guide in our documentation and ensure you have a complete backup of your database and files. There is also an upgrading checklist and step-by-step demonstration on how to upgrade to 3.5 for systems administrators, now available on PKP's YouTube channel, thanks to our collaboration with Crossref.
\nIf you encounter any issues during or after upgrading, please search the community forum. You may find that others have already worked through the same situation. Or you can open a new thread for support from the PKP community and team.
\nReleases like this one are made possible in large part by the community members who take the time to report bugs, submit pull requests, and test fixes in their own environments. We are grateful for the ongoing contributions of developers, librarians, journal managers, and institutional partners from around the world who help make PKP software better for everyone.
\nIf you would like to become more involved in PKP's development and testing processes, we invite you to explore how to contribute.
\nThe post OJS, OMP, and OPS 3.5.0-5 LTS is now Available appeared first on Public Knowledge Project.
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