From PubPub, the MIT open source platform:

The community is still working on the processes, workflows, standards, and values that will support this emergent form of publishing. But that shouldn’t stop anyone who wants to explore these models from starting now. With PubPub, anyone can publish and distribute meaningful, impactful reviews with appropriate metadata that can be picked up by aggregators in about an hour — at no cost and with no technical expertise required.

The post is a detailed guide to how the platform—which we use for mediastudies.press—can be used as a review layer on top of other preprints services, a la PREReview and eLife's Sciety.

MIT Technology Review, on the challenges to reproducibility in AI research:

According to the 2020 State of AI report, [...] only 15% of AI studies share their code. Industry researchers are bigger offenders than those affiliated with universities. In particular, the report calls out OpenAI and DeepMind for keeping code under wraps. Then there’s the growing gulf between the haves and have-nots when it comes to the two pillars of AI, data and hardware. Data is often proprietary, such as the information Facebook collects on its users, or sensitive, as in the case of personal medical records. And tech giants carry out more and more research on enormous, expensive clusters of computers that few universities or smaller companies have the resources to access.

All that private data, though, is the symptom, not the disease. To call AI research a revolving door between industry and academia is to abuse the metaphor: Most researchers have a foot in both worlds. The result is a predictable clash between a race for winner-take-all profits and the norms of science. The evolution of OpenAI—from nonprofit to secretive money-grubber—is a fractal version of what's unfolding. Data transparency won't fix that.

The Daily Beast:

The reporter at the center of the collapse of one of the New York Times’ biggest reporting projects is moving to a new beat. Rukmini Callimachi, formerly one of the paper’s highest-profile reporters on ISIS and extremism in the Middle East, has been re-assigned to cover higher education, multiple people familiar with the matter confirmed to The Daily Beast.

Kicked upstairs.

From SPARC Europe's summary of a recent gathering to discuss and inform the coming Plan S for books:

With almost 75 attendees, this workshop focused on business models for OA books and brought together experts from the field before ending with a document sprint. The sprint allowed the community to engage online by reacting to cases made by the presenters and providing other additions.

From the summary, it's clear that a number of speakers—including Martin Eve, Agata Morka, and Koen Vermeir—warned against mimicking Plan S's de facto crowning of APCs as the main OA funding model. One facet that wasn't much raised, it seems, is the ripple effect on the rest of the world of any Plan S for books. The existing, article-level Plan S, because of its early movement and major funder buy-in, has (perhaps already) cast the die on APCs/read-and-publish not just for Europe, but for the rest of the world too.

From the UK-based open monograph project COPIM:

Available on Github at https://github.com/BirkbeckCTP/otf-signup, features of the system include order tracking, billing management, notification of new sign ups, and access control for backlist packages of books.

The open source code—developed for the CEU Press initiative to use back-catalogue access membership to fund current OA publishing—should be adaptable to any consortiable funding model. Can't wait to dive in.

Sam Moore, in a LSE Impact post on research and the commons:

Simply put, policymakers should reorient their focus away from mere open access to the outputs of scientific research and instead nurture the commons across the research lifecycle. It would mean less of a winner-takes-all strategy to research funding – away from huge grants dictated by bogus ideas of ‘excellence’ – and more of one that encourages small, careful, collaborative research by and between diverse groups of scientists. This could be facilitated through basic research income, grant lotteries and other non-competitive methods, with the outputs from each grant owned in common by scientists across the globe.

The idea of a basic research income (presumably analogized from basic income schemes)—paired with a grant lottery, for example—is a mind-bending departure from the conventional reward systems that (in theory) link distinction with funding. Moore elevates cooperative knowledge-making over the norm of universal access—"communism" in Merton's original, perhaps infelicitous term.