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Evaluating Journal Quality — OA Evaluation Tools

A guide to the tools and methods for evaluating the quality of scholarly journals. Intended for authors, editors and reviewers.

Open Access Evaluation Tools Overview

Open access evaluation tools are intended to help authors, editors and reviewers think logically about determining the quality of a journal title. They use simple but often-not-thought-of questions or qualities as signals of quality. While these tools are focused on open access journals, their questions can be used for aspects of subscription journals as well. These tools provide guidance on what questions to ask but don't replace basic common sense on the part of the author, editor or reviewer. Three tools are reviewed below: Open Access Journal Quality Indicators and the Journal Evaluation Rubric.

Open Access Journal Quality Indicators

The Open Access Journal Quality Indicators is a list of positive and negative indicators of potential journal quality. This is one of the clearest and simplest tools out there, because it offers both positive and negative indicators and because it is simple, straightforward and contains some insightful indicators not found on other checklists.

This is a set of indicators only, there is no list of evaluated journal titles. It's up to the author to actually evaluate a journal using the indicators. This list is from the Grand Valley State University Libraries.

Journal Evaluation Rubric

The Journal Evaluation Rubric offers criteria for journal and publisher evaluation with examples of good, fair and poor outcomes. It provides a useful and detailed context to authors in thinking about what aspects constitute a quality journal or publisher. It can be used for any journal but has categories which are particularly appropriate for open access journals. This tool was created by the Loyola Marymount University Library for their faculty's use. It is simple, straightforward and provides a scoring sheet for authors to use in their journal evaluations which contains a rationale for each category and an interpretation of the numerical results.