Bibliographic record
Abstract
As we continue to celebrate IRRODL's remarkable journey, this issue exemplifies our journal's enduring commitment to advancing open and distributed learning through rigorous scholarship and global collaboration.Detailed in "Twenty-five years of innovation and knowledge sharing: the legacy and future of the international review of research in open and distributed learning," which opened our first 2025 issue, since founding in 2000 as a diamond open access journal, free to both readers and authors, IRRODL has remained steadfast in publishing high-quality research while maintaining international diversity in authorship, readership, and editorial contributions.Our accessibility and innovation have resulted in over 13.5 million downloads and 4 million unique visitors since 2011, with high citation rates and steady impact factor growth reinforcing our advocacy for diamond open access and inclusive scholarship.With authors from 31 countries contributing to recent volumes (2023-2024), we maintain strong North American and UK representation, while 64.3% of our readers come from the Global South, demonstrating our international relevance.This global reach reflects IRRODL's position as the most cited Canadian education journal and our ranking among the top 20 educational technology journals worldwide.
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 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 | 0.006 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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; a candidate call from one teacher head, 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".