Giving It Away: Sharing and the Future of Scholarly Communication
Bibliographic record
Abstract
Debates about open-access scholarly publishing often focus on the costs of scholarship, whether costs incurred by publishers in producing books and journals or costs faced by libraries in acquiring those publications. Taking those costs as the centre of such discussions often results in an impasse, as the financial realities of publishing—particularly within disciplines that are less well-funded than STEM fields (science, technology, engineering and mathematics)—seem to present an insurmountable obstacle to greater openness. What if, however, we were to refocus the discussion on values rather than costs? How might such a shift in focus lead us to think differently about the motives and benefits involved in scholarly communication, and how might this lead us to recognize the generosity that keeps the engine running?
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.033 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.017 | 0.059 |
| Scholarly communication | 0.052 | 0.064 |
| Open science | 0.003 | 0.019 |
| Research integrity | 0.012 | 0.010 |
| Insufficient payload (model declined to judge) | 0.021 | 0.003 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".