Evolution of Open Access Policies and Availability, 1996–2013
Bibliographic record
Abstract
This is a summary document which is the last report of a series produced by Science-Metrix as part of the European Commission Contract RTD-B6-PP-2011-2—Study to develop a set of indicators to measure open access: Archambault, E. et al. (2014). Proportion of Open Access Papers Published in Peer-Reviewed Journals at the European and World Levels—1996–2013. Deliverable D.1.8. (2014 Update). Version 11b. https://zenodo.org/doi/10.5281/zenodo.10030609 Archambault, E. Caruso, J., & Nicol, A, (2014) State-of-art analysis of OA strategies to peer-review publications. Deliverable D.2.1. (2014 Update). Version 5b. Version v1. https://doi.org/10.5281/zenodo.10030787 Caruso, J., Nicol, A, & Archambault, E. (2014) State-of-art analysis of OA strategies to scientific data. Deliverable D.2.2. (2014 Update). Version 4b. https://zenodo.org/doi/10.5281/zenodo.10030812 Caruso, J., Nicol, A, & Archambault, E. (2014) Comparative analysis of the strengths and weaknesses of existing open access strategies. Deliverable D.2.3. (2014 Update). Version 4b. https://doi.org/10.5281/zenodo.10030840 Campbell, D., Nicol, A, & Archambault, E. (2014) Composite indicator to measure the growth of Open Access. Deliverable D.3.2. Version 1. MIA … and the present document: Archambault, E. et al. (2014). Evolution of Open Access Policies and Availability, 1996–2013. Deliverable D.4.5. Version 5b. https://doi.org/10.5281/zenodo.10030853 The ineffectual situation whereby publicly-funded research results published in peer reviewed journals continue to sit behind a 'pay wall', a situation made worse by continuous increases in the price of scholarly journal subscriptions, has fuelled the popularity of open access (OA) in recent years. In response to what many perceive to be a dysfunctional system, individual researchers, libraries, universities, research funders, and governments have become incentivised to join the campaign for OA. Borne on the back of the digital revolution, the movement towards OA to scholarly knowledge is transforming the global research communication and dissemination system. This report presents a summary of this series of studies. It examines the current state of the art of OA strategies to peer-review publications (Part I), a state-of-the-art analysis of OA strategies to scientific data (Part II). A third part of the study performs an assessment of the proportion and the number of OA papers published in peer-reviewed scientific journals. The last part compares the results of policies and strategies across countries and explores policy implications. The study focuses on the 28 member states of the European Union (EU28), as well as the European Research Area (ERA), Brazil, Canada, Japan, and the US. Just as there is a need for policy-makers, researchers, research administrators, and the tax-paying public to consider the inefficiency created by all this public expenditure being made unavailable or available with undue restrictions, difficulties and delays, there is a need to closely monitor the effects of moving the scientific world from one based on Back End Paid Access (BEPA) to one based on Front End Paid Access (FEPA). BEPA created huge social inefficiency; FEPA has the potential to enlarge the rift between wealthier and more poorly financed countries, researchers and scientific disciplines. Many mandates being promulgated at the moment run the risk of favouring a shift from BEPA to FEPA, from inaccessibility to inequality. Neither inaccessibility nor growing inequality are acceptable considering that universalism is one of the core values of scientific research.
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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 | 0.018 | 0.105 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.015 | 0.038 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.010 | 0.010 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.018 | 0.011 |
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".