Exploring Networks of Scholar-Led Publishing Initiatives with a Social Network Analysis of the Radical Open Access Collective
Bibliographic record
Abstract
What role do networks play during the digital transformation of the scholarly publishing system? This article depicts sociospatial practices and its strategic relevance for stakeholders being involved within the Open Access community. The aim is to explore networks of scholar-led publishing initiatives and to facilitate an extended understanding of the scholarly publishing system in transition by thinking it through with sociospatial theory from a Lefebvrian perspective. As a case study, the Radical Open Access Collective (ROAC) with more than 70 members is explored in a mixed methods research design. The focus of the qualitatively-driven research is the Collective’s sociospatial strategies e.g. networking and multiscalar activities. A systematic literature research and interviews with experts in the field of scholar-led publishing provide the main data set, being triangulated with desk-based research on the ROAC. The results show networking processes on three different levels building on a social network analysis. Moreover, this article contributes to a deeper understanding of a network of scholar-led publishers indicating key sociospatial strategies considering dialectics of scalability. Concluding, this study emphasises the importance of sociospatial strategies for non-profit publishing initiatives in order to create a knowledge commons around open and equitable infrastructures.
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How this classification was reachedexpand
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 | 0.009 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.025 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.113 | 0.475 |
| Open science | 0.006 | 0.004 |
| Research integrity | 0.000 | 0.003 |
| 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 itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".