The Open Landscape Environment as The Expanse
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
Building on the 2019 ACRL/SPARC Forum on Collective Reinvestment in Open Infrastructure, this program will explore how libraries can make different commitments to fund content created by open infrastructures. Library collections increasingly promote and reflect such open content and many have chosen to contribute to funding those products. There is not one formula or roadmap to underwrite the publishing and distribution costs of these open resources. There are many variables and considerations as some open content corresponds to serials and others are books or monographs. Open access content is increasingly found in nearly all subject areas, as scholarly publishing models have evolved. Open access does not come without a price to create, maintain and preserve the outputs. Libraries are reconsidering whether they want to commit so much to purchase materials or subscription-based products, when it is unclear what the anticipated use of any materials will be over time. Planning and opportunities for new and more flexible decisions concerning adjustments to and expenditures of the materials budget are under exploration by libraries. There are many options to invest in creating more content to be released as open access. Such options include contributing financially from the Library collections or materials budget to subsidizing or covering APCs, engaging in a more “library as publisher” model hosting journals, publishing books, creating OERs, and offsetting other expenses that ultimately drive a more intensive open infrastructure. Library leaders and partners will share their ideas about trying different approaches to contribute to more open publishing initiatives and explore whether efforts in deploying current book and serial costs to offset opportunities to build a wider and more open infrastructure is on the horizon. This analysis should incorporate the costs of analytical tools necessary to the use of such content in today’s research. Questions will be solicited ahead of time to reflect audience’s interest in such a rethinking of the library collections budget. Please email Julia Gelfand at with your questions.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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