Open Infrastructure Matters: Supporting Scholar-Led and Community-Driven Services to Advance Open Access
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Twenty years ago, open access emerged out of a crisis within scholarly communications. Back then, it was about solving the issue of cost as a barrier to accessing scholarly content, due to the increasing concentration of commercial publishing. Today, another crisis is relying on open access to remove barriers to creating and consuming scholarship. This time, however, our sights are set on increasing public access as a means to solve a global pandemic.
 While open scholarship requires information to be freely available, it costs money to create and sustain high quality books and articles, discovery services that provide access to them, and software that enables their creation. We have seen this in discussions and developments surrounding open access business models, including article processing changes (APCs), open access funds, and “subscribe-to-open.” Where such infrastructures do not generate commercial profits, they require financial support from the communities they serve, including authors, publishers, libraries, funders, scholarly institutions and other stakeholders, to make open access a reality. As we set up national networks, mandates, and other initiatives to support and promote open access, we must not forget another critical element: open infrastructure. In the open access context, “infrastructure” -- the "structures and facilities" -- refers to the scholarly communication resources and services, including software, that we depend upon to enable the scientific and scholarly community to collect, store, organise, access, share, and assess research. Open infrastructure provides the foundation for keeping costs down and quality high, ensuring community-driven development. But who funds open infrastructure? And how do we create a sustainable future for the services that many of us have come to rely on?
 This 20 minute session will examine three open infrastructure case studies: OpenCitations, OAPEN/DOAB, and the Public Knowledge Project. These three initiatives are currently being promoted by the Global Sustainability Coalition for Open Science Services (SCOSS), a network of influential organisations committed to helping secure open access infrastructure well into the future. Our panel of services will explore how the current round of SCOSS-supported projects are ensuring a sustainable future for open access scholarly publishing, and will discuss the essential role that governments, libraries, publishers and others are playing - and need to play - in making this a reality. Following the growth of open access publishing, scholar-led and community-driven open infrastructure and innovations have supported and facilitated the vital (and now urgent) need for open knowledge. What does the next twenty years look like for these services? And how can we work together to ensure open access isn’t just a response to crises, but rather the “new normal”?
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.064 | 0.178 |
| Open science | 0.027 | 0.064 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it