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What Behavioral Scientists Are Unwilling to Accept 行为科学家不愿接受的
Pub Date : 2021-11-01 DOI: 10.2458/jmmss.3061
L. Petrinovich
Meehl (1986) published a brilliant paper with the title “What Social Scientists Don’t Understand.” I believe that that a better characterization of the situation is to broaden the reference class to include behavioral scientists in general. Also, I believe that most behavioral scientists do understand these issues at some level, but that they are not willing to accept the implications that an explicit understanding would force. Concern has been expressed, for the past 40 years or so, that the strategies of research design and statistical analysis used by behavioral scientists are woefully inadequate to support a progressive scientific enterprise. In this article I will summarize the nature of some of these concerns, and will identify some of the impediments that they impose to the development of progressive conceptual frameworks adequate to the task of achieving an understanding of the behavior of complex organisms in their environment. Although there has been little disagreement regarding the soundness of the methodological criticisms that have been made, there is little reason to believe that the methodological and statistical criticisms have had any great impact on the activities of either journal editors or research scientists. A review of these concerns is appropriate at this time because a number of articles have appeared recently that defend the status quo, and which are based either on faulty premises or a questionable view of the problems that impede scientific progress. And, hopefully, yet another critique might enhance the rate at which we arrive at a more satisfying state of affairs. Following this polemic I will suggest some orienting attitudes, research procedures, and analytic strategies that should lead us to a better understanding of the universe of events we, as behavioral scientists, are attempting to understand. These alternative views are based on current developments in the philosophy of science and entail the use of design and analytic strategies that are of sufficient complexity to permit advances in the understanding of the behavior of organisms in their environment.
Meehl(1986)发表了一篇精彩的论文,题目是“社会科学家不理解的东西”。我认为,更好地描述这种情况的方法是扩大参考类别,将行为科学家包括在内。此外,我相信大多数行为科学家确实在某种程度上理解这些问题,但他们不愿意接受明确理解会带来的影响。在过去40年左右的时间里,人们一直担心行为科学家使用的研究设计和统计分析策略远远不足以支持进步的科学事业。在这篇文章中,我将总结其中一些问题的性质,并确定它们对发展足以理解复杂生物体在其环境中的行为的渐进概念框架造成的一些障碍。尽管对方法论批评的合理性几乎没有分歧,但几乎没有理由相信方法论和统计批评对期刊编辑或研究科学家的活动产生了重大影响。目前对这些问题进行审查是适当的,因为最近出现了一些捍卫现状的文章,这些文章要么基于错误的前提,要么基于对阻碍科学进步的问题的可疑看法。而且,希望另一种批评能提高我们达到更令人满意状态的速度。在这场争论之后,我将提出一些有针对性的态度、研究程序和分析策略,使我们更好地理解我们作为行为科学家试图理解的事件的宇宙。这些替代观点基于科学哲学的当前发展,需要使用足够复杂的设计和分析策略,以促进对生物体在其环境中行为的理解。
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引用次数: 1
Why Did It Take So Many Decades for the Behavioral Sciences to Develop a Sense of Crisis Around Methodology and Replication? 为什么行为科学花了这么多年的时间才发展出一种围绕方法论和复制的危机感?
Pub Date : 2021-11-01 DOI: 10.2458/jmmss.3062
A. Gelman, S. Vazire
For several decades, leading behavioral scientists have offered strong criticisms of the common practice of null hypothesis significance testing as producing spurious findings without strong theoretical or empirical support. But only in the past decade has this manifested as a full-scale replication crisis. We consider some possible reasons why, on or about December 2010, the behavioral sciences changed.
几十年来,主要的行为科学家对零假设显著性检验的常见做法提出了强烈的批评,认为它在没有强有力的理论或经验支持的情况下产生了虚假的发现。但直到过去10年,这才表现为一场全面的复制危机。我们考虑了一些可能的原因,为什么在2010年12月左右,行为科学发生了变化。
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引用次数: 1
Latent Variable Structural Equation Modeling: A Flexible Tool for Establishing Validity and More 潜在变量结构方程建模:一个灵活的工具,建立有效性和更多
Pub Date : 2021-11-01 DOI: 10.2458/jmmss.3065
D. Altschul
Petrinovich highlighted many salient issues in the behavioral and social sciences that are of concern to this day, such as insufficient attention to construct validity. Structural equation modeling, particularly with regard to latent variables, is introduced and discussed in this context. Though conceptual issues remain, analytic and statistical techniques have made immense strides in the past three decades since the article was written, and properly used, offer solutions to many problems Petrinovich identified.
彼得里诺维奇强调了行为科学和社会科学中许多值得关注的突出问题,例如对建构效度的重视不够。结构方程建模,特别是关于潜在变量,是介绍和讨论在这种情况下。尽管概念上的问题仍然存在,分析和统计技术在过去的三十年里取得了巨大的进步,自从这篇文章发表以来,正确的使用,为彼得里诺维奇发现的许多问题提供了解决方案。
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引用次数: 0
Preface: What Behavioral Scientists Are Unwilling to Accept 前言:行为科学家不愿意接受什么
Pub Date : 2021-11-01 DOI: 10.2458/jmmss.3060
A. Weiss, Melinda F. Davis
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引用次数: 0
Forward: What Behavioral Scientists Are Unwilling to Accept by Lewis Petrinovich 《前进:行为科学家不愿接受的东西》作者:刘易斯·佩特里诺维奇
Pub Date : 2021-11-01 DOI: 10.2458/jmmss.3059
A. Figueredo
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引用次数: 0
Modelling Inference in the Comprehension of Cinematic Narratives 电影叙事理解中的建模推理
Pub Date : 2021-04-01 DOI: 10.2458/V11I2.23919
Nick Redfern
The viewer’s processes of inference making in the cinema involve the framing of hypotheses about the world of the narrative that may be overturned by subsequent information and are, therefore, nonmonotonic. The goal of narrative researchers is to understand the nature of those processes and how texts organise the deployment of those processes in order to present a narrative successfully. To do this we need methods capable of describing processes of hypothesis framing and belief revision. In this paper, I describe the application of the Transferable Belief Model to a hypothetical example of narrative comprehension based on an episode of CSI: Crime Scene Investigation as one such method.
观众在电影中进行推理的过程包括对叙事世界的假设框架,这些假设可能会被随后的信息推翻,因此是非单调的。叙事研究者的目标是理解这些过程的本质,以及文本如何组织这些过程,以成功地呈现叙事。要做到这一点,我们需要能够描述假设框架和信念修正过程的方法。在本文中,我描述了可转移信念模型在基于CSI:犯罪现场调查一集的叙事理解的假设示例中的应用。
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引用次数: 2
From the Editors 来自编辑
Pub Date : 2020-12-31 DOI: 10.2458/v11i2.23918
E. Board
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引用次数: 0
Journal of Methods and Measurement Reviewers 方法与测量审稿人杂志
Pub Date : 2020-12-31 DOI: 10.2458/v11i2.23920
E. Board
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引用次数: 0
Evaluation During a Pandemic 大流行期间的评估
Pub Date : 2020-12-31 DOI: 10.2458/V11I2.23944
Melinda F. Davis, B. Krauss
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引用次数: 0
From the Editors 来自编辑
Pub Date : 2020-12-30 DOI: 10.2458/v11i1.23913
E. Board
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引用次数: 0
期刊
Journal of methods and measurement in the social sciences
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