Varieties of diffusion in academic publishing: How status and legitimacy influence growth trajectories of new innovations
Bibliographic record
Abstract
Abstract Open Access (OA) publishing has progressed from an initial fringe idea to a still‐growing, major component of modern academic communication. The proliferation of OA publishing presents a context to examine how new innovations and institutions develop. Based on analyses of 1,296,304 articles published in 83 OA journals, we analyze changes in the institutional status, gender, age, citedness, and geographical locations of authors over time. Generally, OA journals tended towards core‐to‐periphery diffusion patterns. Specifically, journal authors tended to decrease in high‐status institutional affiliations, male and highly cited authors over time. Despite these general tendencies, there was substantial variation in the diffusion patterns of OA journals. Some journals exhibited no significant demographic changes, and a few exhibited periphery‐to‐core diffusion patterns. We find that although both highly and less‐legitimate journals generally exhibit core‐to‐periphery diffusion patterns, there are still demographic differences between such journals. Institutional and cultural legitimacy—or lack thereof—affects the social and intellectual diffusion of new OA journals.
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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 | 0.008 | 0.065 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".