More Noise than Signal in Proliferation Studies?

Etel Solingen
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引用次数: 2

Abstract

Mark Bell’s article (2016) is a welcome contribution to the unavoidable task of evaluating a research program that exhibits the problems he identifies: the failure of most quantitative studies to offer strong explanations for proliferation patterns, and their inability to predict out-of-sample cases. His findings resonate with those of other proliferation experts. The existing quantitative literature, argues Bell, produces more tentative findings than scholars typically understand. We concur fully with the first part of the last sentence but believe that the broader community of experts typically does understand the serious limitations of most quantitative studies (and qualitative ones) on this topic. What are those limitations of quantitative studies according to Bell? First, there are many more distinctive explanations than cases. Second, most variables identified as significant determinants of proliferation “fail to provide robust explanations for existing patterns.” Third, studies question the robustness of each other’s quantitative findings. Fourth, they provide little sense of the hierarchy of importance of different explanations. Fifth, they offer “little predictive ability beyond what we can achieve with an extremely simple model” (which, incidentally but unstated in Bell’s piece, can be of a qualitative kind). Sixth, they are not transparent about those limitations. Seventh, they typically model the effects of variables as constant across time and space. Here Bell reiterates a point others have made: studies must control for the world-time under which nuclear weapons are developed or eschewed, such as pre- or post-NPT era (Solingen 2007). Because of all of the above and more, Bell concludes that weak correlations between proliferation and many variables in extant quantitative studies offer no proof whatsoever that those variables do not in fact cause or prevent proliferation. In other words, the absence of evidence is not evidence of absence, as is sometimes argued in court. Most of these shortcomings are well known, and some can afflict qualitative studies as well (for an extensive review, see Wan and Solingen 2015 and Solingen 2007).
扩散研究中的噪音比信号多?
马克·贝尔(Mark Bell)的文章(2016)对评估一个研究项目这一不可避免的任务做出了受欢迎的贡献,该项目展示了他所发现的问题:大多数定量研究未能为扩散模式提供强有力的解释,以及它们无法预测样本外案例。他的发现与其他核扩散专家的发现产生了共鸣。贝尔认为,现有的定量文献所产生的初步发现比学者们通常理解的要多。我们同意最后一句话的第一部分,但相信更广泛的专家社区通常确实理解大多数定量研究(和定性研究)在这个主题上的严重局限性。贝尔认为定量研究的局限性是什么?首先,有许多比案例更独特的解释。其次,大多数被认为是扩散的重要决定因素的变量“无法为现有模式提供有力的解释”。第三,研究对彼此定量结果的稳健性提出了质疑。第四,它们几乎没有提供不同解释的重要性等级的概念。第五,它们“几乎没有预测能力,超出了我们用一个极其简单的模型所能达到的水平”(顺便说一句,贝尔的文章中没有说明,这个模型可能是定性的)。第六,他们对这些限制并不透明。第七,他们通常将变量的影响建模为跨越时间和空间的常数。在这里,贝尔重申了其他人提出的观点:研究必须控制核武器被开发或被避免的世界时间,比如不扩散核武器条约之前或之后的时代(Solingen 2007)。由于以上种种,贝尔得出结论,在现有的定量研究中,增殖与许多变量之间的弱相关性无法证明这些变量实际上不会导致或阻止增殖。换句话说,证据的缺失不是缺席的证据,就像有时在法庭上争论的那样。这些缺点大多是众所周知的,有些也会影响定性研究(有关广泛的回顾,请参阅Wan and Solingen 2015和Solingen 2007)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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