Inequality in Knowledge Production: The Integration of Academic Infrastructure by Big Publishers
The implications of a simultaneous redirection of the big publishers' business strategy towards open access business models and the acquisition of scholarly infrastructure utilizing the conceptual framework of rent-seeking theory.
The Scientific Prize Network Predicts Who Pushes the Boundaries of Science
Using comprehensive new data on prizes and prizewinners worldwide and across disciplines, this study examines the growth dynamics and interlocking relationships found in the worldwide scientific prize network.
Gender and International Diversity Improves Equity in Peer Review
The acceptance rate for eLife manuscripts with male last authors was significantly higher than for female last authors, and this gender inequity was greatest when the team of reviewers was all male; mixed-gender gatekeeper teams lead to more equitable peer review outcomes.
Data Sharing in PLOS ONE: An Analysis of Data Availability Statements
Only about 20% of statements indicate that data are deposited in a repository, which the PLOS policy states is the preferred method. More commonly, authors state that their data are in the paper itself or in the supplemental information, though it is unclear whether these data meet the level of sharing required in the PLOS policy.
The Global State of Peer Review is one of the largest ever studies into the practice of scholarly peer review around the world focusing on four questions: 1. Who is doing the review? 2. How efficient is the peer review process? 3. What do we know about peer review quality? 4. What does the future hold?
Where Do the Numbers Published in Scientific Articles Come From?
Study attempts to reproduce values reported in 35 articles published in the journal Cognition revealed analysis pipelines peppered with errors. Elements of a reproducible workflow that may help to mitigate these problems in future research are outlined.
Many efforts are underway to promote data sharing in psychology, however it is currently unclear if the in-principle benefits of data availability are being realized in practice. In a recent study, we found that a mandatory open data policy introduced at the journal Cognition led to a substantial increase in available data, but a considerable portion of this data was not reusable. For data to be reusable, it needs to be clearly structured and well-documented. Open data alone will not be enough to achieve the benefits envisioned by proponents of data sharing.
Practical Tools and Strategies for Researchers to Increase Replicability
This publication provides an overview of some practical tools and strategies that researchers can implement in their own workflow to increase replicability and the overall quality of psychology research.
We present an agent-based model of paper publication and consumption that allows to study the effect of two different evaluation mechanisms, peer review and reputation, on the quality of the manuscripts accessed by a scientific community.
Peer Review of Health Research Funding Proposals: A Systematic Map and Systematic Review of Innovations for Effectiveness and Efficiency
Virtual peer review using videoconferencing or teleconferencing appears promising for reducing costs by avoiding the need for reviewers to travel, but again any consequences for quality have not been adequately assessed.
In a slightly depressing new paper, researchers describe how they tried to get access to the data behind 111 of the most cited psychology and psychiatry papers published in the past decade. Only 14% of the datasets were made available with no restrictions on who could access them.
Citizen Science Can Make Systematic Reviews Faster and More Efficient
Citizen science: crowdsourcing for systematic reviews looks at how people can contribute their expertise to scientific studies using new online platforms - even if they don’t think of themselves as researchers or scientists.
High-Impact and Transformative Science Metrics: Definition, Exemplification, and Comparison
A novel set of text- and citation-based metrics that can be used to identify high-impact and transformative works. The 11 metrics can be grouped into seven types: Radical-Generative, Radical-Destructive, Risky, Multidisciplinary, Wide Impact, Growing Impact, and Impact (overall).
Who benefits from sharing data? The scientists of future do, as data sharing today enables new science tomorrow. Far from being mere rehashes of old datasets, evidence shows that studies based on analyses of previously published data can achieve just as much impact as original projects.