Proportion of Open Access Peer-Reviewed Papers at the European and World Levels—2004-2011
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
This report re-assesses the Open Access (OA) availability of scholarly publications during the 2004 to 2011 period, for 22 fields of knowledge, as well as for the European Research Area countries, Brazil, Canada, Japan, and the US. Using a strategy to increase the number of free articles retrieved (that is, which aims to increasing recall), led to close to a doubling of the proportion of OA estimated by teams lead by Björk1 and by Harnad2. The present report shows that the tipping point for OA (more than 50% of the papers available for free) has been reached in several countries, including Brazil, Switzerland, the Netherlands, the US, as well as in biomedical research, biology, and mathematics and statistics. Between 2004 and 2011, the average annual rate of increase of OA availability was relatively limited, with a compound growth rate of 2% per year. In addition to having year-on-year growth, there is an upward translation of the whole availability curve over time. This is due to an increasing number of authors making their manuscripts available for the current year but also for previous years. There are also transient effects that have to be considered when measuring OA availability, including temporary promotional OA offered by publishers and variations in websites' availability. All in all, more than 50% of the papers could be found for free in November/December 2012 (pilot phase of this study) and in March/April 2013 (1st full measurement stage) but somewhat less so at either time period. This shows that measuring phenomena on the Internet requires particular attention to detail and constant questioning on the meaning of the results. Green OA appears to be moving slowly, whereas gold and hybrid OA (such as pay-per-article for OA release) appear to be driving in the fast lane. This impression will require further investigation. Efforts should be made to characterise these changes, and to distinguish what percentage of growth comes from green self-archiving and what comes from other forms of hybrid OA. The fact that the open access tipping point has likely been reached is an important finding for the whole publishing industry. This industry is likely to be undergoing revolutionary change, and at a pace much faster than anticipated, in large part because previous measures of OA availability proved to be misleading. This means that aggressive publishers are likely to gain much in the redesigned landscape, whereas those attached to the old ways are likely to suffer and to lose market share. An important question is whether the switch to a more atomistic, fine-grained market with millions of researchers as buyers will reduce, augment or leave unchanged the negotiating power of publishers.
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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 | 0.011 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.008 | 0.022 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.146 | 0.092 |
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