摘要：

【目的】 挖掘中文科技期刊在同行评议环节存在的问题,并探讨对策,以期为科技期刊优化审稿人队伍,提高办刊质量和影响力提供一定的参考。【方法】 对搜集到的288位审稿专家的11个主要特征信息(学科、学历、职称、单位性质、性别、审稿次数、平均审稿时长、最长审稿时长、缺审次数、投稿次数、平均审稿得分)进行统计和相关性分析, 将定量统计与定性的经验分析有机结合。【结果】 期刊在审稿人选择、审稿专家库构建、审稿效率和质量、审稿评分机制上存在一系列问题。【结论】 为了解决同行评议环节存在的问题,在审稿人遴选上,应尝试为职称较低但具有高学历和高学科活跃度的科研人员提供更多的审稿机会,并构建优秀作者补充审稿专家库的机制。在审稿人管理和评价上,应在突破传统培训模式的基础上,加强培训,并量化审稿评价方法,保障审稿人评价的公正性。期刊还应加强与审稿人的互动和互助,从为其提供服务的角度出发制定合理的激励措施。

关键词: 同行评议, 相关性分析, 审稿人遴选, 审稿质量评价, 激励机制

Abstract:

[Purposes] This paper excavates the problems existing in peer review and explores the countermeasures, in order to optimize reviewers' team and improve the quality and influence of scientific journals. [Methods] The statistical and correlation analyses were carried out on 11 key features (subject, education background, professional title, affiliation character, gender, reviewing number, average review time, maximum review time, rejecting review number, submission number, and average review score) of 288 reviewers, and the quantitative statistics combined with the qualitative analysis was used. [Findings] A series of problems exist in the workflow of reviewer selection, reviewer database construction, review efficiency, and review quality evaluation. [Conclusions] In order to solve the problems in peer review, the following measures should be done. In the selection of reviewers, editors should try to give the young, highly educated, and academically active researchers more opportunities and construct the mechanism in which the talented writers can supply the reviewer database. In the management and evaluation of reviewers, the training of the reviewers should be strengthened on the basis of breaking through the traditional training mode and the reviewer evaluation method should also be quantified to insure the fairness of the review scores. Besides, journals should also strengthen the interaction and mutual assistance with reviewers and establish a reasonable incentive mechanism.

Key words: Peer review, Correlation analysis, Reviewers selection, Review quality evaluation, Incentive mechanism