The Oligopoly's Shift to Open Access. How For-Profit Publishers Benefit from Article Processing Charges
Bibliographic record
Abstract
This study aims to estimate the total amount of article processing charges (APCs) paid to publish open access (OA) in journals controlled by the large commercial publishers Elsevier, Sage, Springer-Nature, Taylor & Francis and Wiley, the so-called oligopoly of academic publishing. Since the early 2010s, these five academic publishers control more than half of peer-reviewed journal articles indexed in the Web of Science (WoS), expanding their market power through acquisitions and mergers. While traditionally their business model focused on charging subscriptions to read articles, they have now shifted to OA, charging authors fees for publishing. These APCs often amount to several thousand dollars, excluding many from publishing on economic grounds. This study computes an estimate of the total amounts of APCs paid to oligopoly publishers between 2015 and 2018, using publication data from WoS, OA status from Unpaywall and annual APC prices from open datasets and historical fees retrieved via the Internet Archive Wayback Machine. We estimate that globally authors paid the oligopoly of academic publishers $1.06 billion in publication fees in the 4-year period analyzed. Of the 505,903 OA articles analyzed, 60.9% were published in gold OA journals, 8.6% in diamond (gold with APC=$0) and 30.5% in hybrid journals. Revenue from gold OA amounted to $612.5 million, while $448.3 million was obtained for publishing OA in hybrid journals, for which publishers already charge subscription fees. Among the five publishers, Springer-Nature made the largest revenue from OA ($589.7 million), followed by Elsevier ($221.4 million), Wiley ($114.3 million), Taylor & Francis ($76.8 million) and Sage ($31.6 million). With Elsevier and Wiley making the majority of APC revenue from hybrid fees and others focusing on gold, different OA strategies could be observed between publishers.
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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 | 0.003 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".