The four pillars of scholarly publishing: The future and a foundation
Bibliographic record
Abstract
With the rise of electronic publishing and the inherent paradigm shifts for so many other scientific endeavours, it is time to consider a change in the practices of scholarly publication in Ecology and Evolutionary Biology. To facilitate the speed and quality of science, the future of scholarly communication will rest on four pillars - an ecosystem of scholarly products, immediate and open access, open peer review, and full recognition for participating in the process. These four pillars enable us to build better tools to facilitate the discovery of new relevant work for individual scientists, one of the greatest challenges of our time as we cope with the current deluge of scientific information. By incorporating these principles into future publication platforms, we argue that science and society will be better served than by remaining locked into a publication formula that arose in the 1600s. It has served its purpose admirably and well, but it is time to move forward. With the rise of the Internet, scholarly publishing has embraced electronic distribution. But the tools afforded by the Internet and other advancing technologies have profound implications for scholarly communication beyond just distribution. We argue that, to best serve science, the process of scholarly communication must embrace these advances and evolve. Here we consider the current state of the process in ecology and evolutionary biology and propose directions for change. We identify four pillars for the future of scientific communication: (1) an ecosystem of scholarly products; (2) immediate and open access; (3) open peer review; and (4) full recognition for participating in the process. These four pillars will guide the development of better tools and practices for discovering and sharing scientific knowledge in a modern networked world. Things were far different when the existing system arose in the 1600s, and though it has served its purpose admirably and well, it is time to move forward.
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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 | 0.099 | 0.084 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.024 | 0.095 |
| Scholarly communication | 0.085 | 0.098 |
| Open science | 0.005 | 0.021 |
| Research integrity | 0.017 | 0.025 |
| Insufficient payload (model declined to judge) | 0.011 | 0.006 |
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".