Gold Open Access Publishing in Mega-Journals: Developing Countries Pay the Price of Western Premium Academic Output
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
Open access publishing (OAP) makes research output freely available, and several national governments have now made OAP mandatory for all publicly funded research. Gold OAP is a common form of OAP where the author pays an article processing charge (APC) to make the article freely available to readers. However, gold OAP is a cause for concern because it drives a redistribution of valuable research money to support open access papers in ‘mega-journals’ with more permissive acceptance criteria. We present a data-driven evaluation of the financial ramifications of gold OAP and provide evidence that gold OAP in mega-journals is biased toward Western industrialized countries. From 2011 to 2015, the period of our data collection, countries with developing economies had a disproportionately greater share of articles published in the lower-tier mega-journals and thus paid article APCs that cross-subsidize publications in the top-tier journals of the same publisher. Conversely, scientists from Western developed countries had a disproportionately greater share of articles published in those same top-tier journals. The global inequity of the cross-subsidizing APC model was demonstrated across five different mega-journals, showing that the issue is a common problem. We need to develop stringent and fair criteria that address the global financial implications of OAP, as publication fees should reflect the real cost of publishing and be transparent for authors.
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.
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 | 0.253 | 0.536 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.041 | 0.050 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.728 | 0.555 |
| Open science | 0.071 | 0.017 |
| Research integrity | 0.001 | 0.008 |
| 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