Impact of Transformative Agreements on Publication Patterns
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
"Transformative agreements" are agreements made between publishers and institutions that were intended to transform the traditional subscription-based scholarly publishing system to open access. Some publishers and institutions have argued that these are the best option, yet, they are increasingly being called into question. Not only does the transition remain incomplete, they create negative effects on researchers without access to an agreement or funding to pay an article processing charge. This research project sought to address the question of whether transformative agreements increase the number of open access publications. In April 2022, we retrieved 370 transformative agreements from the ESAC Transformative Agreement Registry, of which 72 met our inclusion criteria. At that time, agreements in the ESAC Registry were heavily weighted towards Europe. We retrieved publications from the Web of Science Core Collection, and screened these to ensure that they were authored by researchers at participating institutions and published in hybrid open access journals covered by the agreement. Using the Unpaywall API, we determined the open access status of each item. Through this process, we identified 156,053 publications that met inclusion criteria. In this article, we examine changes in publication patterns at an aggregate level and per agreement.
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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.008 |
| Open science | 0.003 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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