Subscription-based and open access dermatology journals: the publication model dilemma
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
Medical journalism and the dissemination of peer-reviewed research serve to promote and protect the integrity of scholarship. We evaluated the publication models of dermatology journals to provide a snapshot of the current state of publishing. A total of 106 actively-publishing dermatology journals were identified using the SCImago Journal Rankings (SJR) citation database. Journals were classified by publication model (subscription-based and open-access), publishing company, publisher type (commercial, professional society, and university), MEDLINE-indexing status, and SJR indicator. Of these, 65 (61.32%) dermatology journals were subscription-based and 41 (38.68%) were open-access. In addition, 59 (55.66%) journals were indexed in MEDLINE and most were subscription-based (N=51) and published by commercial entities (N=54). MEDLINE-indexing status was significantly different across publisher types (P<0.001), access-types (P<0.001), and the top four publishers (P=0.016). Distribution of SJR indicator was significantly different across publisher types (P<0.001) and access-types (all journals, P=0.001; indexed journals only, P=0.046). More than 91% of MEDLINE-indexed titles were published by commercial entities, and among them, four companies controlled the vast majority. Discontinuation of access to any one of the top publishers in dermatology can significantly and disproportionately impact education and scholarship.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.005 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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