Achieving global open access: the need for scientific, epistemic and participatory openness
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
Achieving Global Open Access explores some of the key conditions that are necessary to deliver global Open Access (OA) that is effective and equitable. \n \nOften assumed to be a self-evident good, OA has been subject to growing criticism for perpetuating global inequities and epistemic injustices. It has been seen as imposing exploitative business and publishing models and as exacerbating exclusionary research evaluation cultures and practices. Pinfield engages with these issues, recognising that the global OA debate is now not just about publishing business models and academic reward structures, but also about what constitutes valid and valuable knowledge, how we know, and who gets to say. The book argues that, for OA to deliver its potential, it first needs to be associated with ‘epistemic openness’, a wider and more inclusive understanding of what constitutes valid and valuable knowledge. It also needs to be accompanied by ‘participatory openness’, enabling contributions to knowledge from more diverse communities. Interacting with relevant theory and current practice, the book discusses the challenges in implementing these different forms of openness, the relationships between them, and their limits. \n \nAchieving Global Open Access is essential reading for academics and students engaged in the study of Library and Information Science, Open Access and Publishing. It will also be valuable and interesting to library and publishing professionals around the world.
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.080 | 0.009 |
| Open science | 0.021 | 0.074 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.113 | 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