The Changing Medical Publishing Industry: Economics, Expansion, and Equity
Bibliographic record
Abstract
Medical journal publishing has changed dramatically over the past decade. The shift from print to electronic distribution altered the industry's economic model. This was followed by open access mandates from funding organizations and the subsequent imposition of article processing charges on authors. The medical publishing industry is large and while there is variation across journals, it is overall highly profitable. As journals have moved to digital dissemination, advertising revenues decreased and publishers shifted some of the losses onto authors by way of article processing charges. The number of open access journals has increased substantially in recent years. The open access model presents an equity paradox; while it liberates scientific knowledge for the consumer, it presents barriers to those who produce research. This emerging "pay-to-publish" system offers advantages to authors who work in countries and at institutes with more resources. Finally, the medical publishing industry represents an unusual business model; the people who provide both the content and the external peer review receive no payment from the publisher, who generates revenue from the content. The very unusual economic model of this industry makes it vulnerable to disruptive change. The economic model of medical publishing is rapidly evolving and this will lead to disruption of the industry. These changes will accelerate dissemination of science and may lead to a shift away from lower-impact journals towards pre-print servers.
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 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 | 0.020 | 0.072 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.018 | 0.005 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.022 | 0.018 |
| Insufficient payload (model declined to judge) | 0.015 | 0.005 |
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".