迈向更好的人格科学的十个步骤-如何在研究评估中获得更多的质量奖励

D. Leising, Isabel Thielmann, A. Glöckner, Anne Gärtner, Felix D. Schönbrodt
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引用次数: 7

摘要

2020年2月,德国心理学会(dpps)的人格与诊断章节(DPPD)要求这组作者概述什么应该被视为“良好的人格科学”,作为如何提高该领域研究可信度的积极愿景。我们主张在以下方面达成更大的共识:(1)共同的重要研究目标;(2)术语的标准化使用;(3)标准化的测量实践;(4)预处理和分析数据的标准化方法;(5)对理论和知识现状的共享观点。所有这些都将有助于大大简化该领域。我们还支持(6)理论形式化,(7)任何验证性声明的预注册要求,(8)更多地重视复制尝试(例如,通过为它们保留期刊空间配额),(9)规划信息性(例如,良好的)研究,以及(10)默认向公众开放数据,代码和材料。目前,学术界以数量为基础的激励结构显然阻碍了许多这些实践的实施,导致研究文献有时具有可疑的效用和/或完整性。作为解决方案,我们提出了一个基于质量的奖励方案,该方案明确地根据其良好的科学价值对已发表的研究进行加权。采用这样的奖励方案可能会导致总体出版数量的显著下降,希望能导致(a)文献中的信噪比得到改善,(b)研究人员更有效地分配资源(如时间),他们将能够阅读更多正在发表的内容,并更仔细地审查彼此的工作。科学家需要因工作出色而得到越来越多的奖励,而不仅仅是工作多。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Ten steps toward a better personality science - how quality may be rewarded more in research evaluation
In February 2020, the Personality and Diagnostics Chapter (DPPD) of the German Psychological Society (DGPs) tasked this group of authors with outlining what should be considered “good personality science”, as a positive vision of how to improve the credibility of research in the field. We argue in favor of working toward greater consensus about (1) shared, important research goals, (2) standardized use of terminology, (3) standardized measurement practices, (4) standardized ways of pre-processing and analyzing data, and (5) shared views of the current state of theory and knowledge. All of these should help streamline the field considerably. We also argue in favor of (6) theory formalization, (7) pre-registration requirements for any confirmatory claims, (8) valuing replication attempts more (e.g., by reserving a quota of journal space for them), (9) planning for informative (e.g., well-powered) studies, and (10) making data, code, and materials open to the public by default. The current, quantity-based incentive structures in academia clearly stand in the way of implementing many of these practices, resulting in a research literature with sometimes questionable utility and/or integrity. As a solution, we propose a quality-based reward scheme that explicitly weights published research by its good science merits. Adoption of such a reward scheme may incur a significant decline in overall publication numbers, hopefully resulting in (a) an improved signal-to-noise ratio in the literature, and (b) more efficient allocation of resources (e.g., time) by researchers, who would be enabled to read more of what is being published, and to review each other’s work more carefully. Scientists need to be increasingly rewarded for doing good work, not just lots of work.
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