Article Processing Charge Hyperinflation and Price Insensitivity: An Open Access Sequel to the Serials Crisis
Bibliographic record
Abstract
Open access publishing has frequently been proposed as a solution to the serials crisis, which involved unsustainable budgetary pressures on libraries due to hyperinflation of subscription costs. The majority of open access articles are published in a minority of journals that levy article processing charges (APCs) paid by authors or their institutions upon acceptance. Increases in APCs is proceeding at a rate three times that which would be expected if APCs were indexed according to inflation. As increasingly ambitious funder mandates are proposed, such as Plan S, it is important to evaluate whether authors show signs of price sensitivity in journal selection by avoiding journals that introduce or increase their APCs. Examining journals that introduced an APC 4-5 years after launch or when flipping from a subscription model to immediate open access model showed no evidence that APC introduction reduced article volumes. Multilevel modelling of APC sensitivity across 319 journals published by the four largest APC-funded dedicated commercial open access publishers (BMC, Frontiers, MDPI, and Hindawi) revealed that from 2012 to 2018 higher APCs were actually associated with increased article volumes. These findings indicate that APC hyperinflation is not suppressed through market competition and author choice. Instead, demand for scholarly journal publications may be more similar to demand for necessities, or even prestige goods, which will support APC hyperinflation to the detriment of researchers, institutions, and funders.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.015 | 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".