No evidence that women are penalized in peer review and editorial processes, finds study on 145 journals in multiple disciplines.

The purpose of this paper is to analyze the causes and effects of arbitrariness in the peer review process. This paper focuses on two main reasons for the arbitrariness in peer review. The first is that referees are not homogenous and display homophily in their taste and perception of innovative ideas. The second element is that reviewers are different in the time they allocate for peer review. Our model replicates the NIPS experiment of 2014, showing that the ratings of peer review are not robust, and that altering reviewers leads to a dramatic impact on the ranking of the papers. This paper also shows that innovative works are not highly ranked in the existing peer review process, and in consequence are often rejected.

In this paper we review several novel approaches for research evaluation. We start with a brief overview of the peer review, its controversies, and metrics for assessing efficiency and overall quality of the peer review. We then discuss five approaches, including reputation-based ones, that come out of the research carried out by the LiquidPub project and research groups collaborated with LiquidPub. Those approaches are alternative or complementary to traditional peer review. We discuss pros and cons of the proposed approaches and conclude with a vision for the future of the research evaluation, arguing that no single system can suit all stakeholders in various communities.

Service-oriented computing and Web services are becoming more popular, enabling organizations to use the Web as a market for selling their own services and consuming existing services from others. Nevertheless, the more services are available, the more difficult it becomes to find the most appropriate service for a specific application. Existing approaches to Web service discovery tend to address different information-processing styles. However, Web services have functional and nonfunctional characteristics that can be difficult to present and control. Service behavior and quality-of-service (QoS) parameters can vary over time, and new services can emerge in certain business areas.