Peer review is a process of subjecting research findings and research methods to the scrutiny of others who are experts in the same fields. This process is also integral to scholarly research. Peer review is conducted before publication of the research manuscript. The main purpose is to ensure that whatever comes out published will be virtually free of errors. Different types of peer review models are followed by different journals based on the type of research they publish and their journal management style. The most commonly adopted format are single blind peer review and double blind peer review. Recently another type of peer review process is adopted by some journals, i.e. open peer review and post publication peer review.
Single-blind: In this type, the reviewers are aware of the author’s identity but authors are unaware of who reviewed their research manuscript. There is a possibility that making the author’s identity known could influence the review, while this method serves to reduce chances of bias and conflict of interest.
Double blind: In double blind peer review, both the peer reviewer and the author are not aware of each other’s identity. So here is a risk that sometimes it may allow the reviewers to give irresponsible or inaccurate feedback to the authors.
Open: Identities of both the reviewers and author are known. This method of review also allows the author’s responses as well as peer reviewer comments to be published along with the final manuscript.
Post-publication: To bring back the time of immediate feedback called post publication peer review, recently publishers, entrepreneurs and scientific societies have begun using the web. Although these days most scientific journals are published online, peer review is still most often done according to the publication, and the status of peer review is held as an important hallmark of quality.
The review process is one of the most distinctive features of scholarly publication. While it is not perfect, this is the process used by almost all scholarly publications to identify weak data analysis, filter out bad science and make suggestions for better presentation of research results.