The oligopoly’s shift to open access publishing
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
This study estimates fees paid for gold and hybrid open access articles in journals published by the oligopoly of academic publishers, which acknowledge funding from the Canadian Tri-Agency. It employs bibliometric methods using data from Web of Science, Unpaywall, open datasets of article processing charges list prices as well as historical fees retrieved via the Internet Archive Wayback Machine for journals published by Elsevier, Springer-Nature, Wiley, Sage and Taylor & Francis to estimate article processing charges for open access articles published between 2015 and 2018 that acknowledge funding from the Canadian Federal funding agencies CIHR, NSERC, and SSHRC, as well as grants jointly administered by the Tri-Agency. During the four-year period analyzed, a total of 6,892 gold and 4,097 hybrid articles that acknowledge Tri-Agency funding were identified, for which the total list prices amount to $US 27.6 million.
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.
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | Scholarly communicationOpen science Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Not applicable | low |
| gpt | Scholarly communicationOpen science Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Other design | low |
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 | 0.027 | 0.397 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.008 | 0.067 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.187 | 0.044 |
| Open science | 0.049 | 0.040 |
| 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 it