治理如何改变研究内容?将科学政策研究与科学社会学联系起来

J. Gläser
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引用次数: 22

摘要

尽管科学研究通常假设治理可以改变研究内容,但我们对治理如何做到这一点知之甚少。科学政策行为体、商业利益和民间社会行为体利用各种治理工具和过程来改变方向或提高研究质量。只有让研究人员选择不同的目标和方法,即改变他们的工作内容,才能实现这两者。最近的一项综述显示,很少有研究调查了治理对研究内容的影响,更少的研究令人信服地确立了因果关系(Gläser和Laudel 2016)。竞争性项目资助的实证研究侧重于选择程序的有效性和可靠性,而在很大程度上回避了对项目内容的先发制人适应或选择性资助对研究领域动态的影响的调查(同上:122-125)。对新兴领域的治理进行了研究,将领域的增长作为唯一近似于内容的因变量(同上:126-129)。大多数关于业绩资助影响的研究都局限于出版行为的变化,将其归因于业绩资助的因果关系可以仁慈地描述为脆弱的(同上:129-134;格拉泽2017)。最后,对学院-产业联系的研究在这种联系对知识扩散的影响方面产生了一些有趣的结果(Evans 2010a;b)与产业资助者的利益相一致的发现的可能性增加(Krimsky 2013),以及这种联系对知识传播的影响(Evans 2010a;b).然而,许多研究的经验证据是相互矛盾的,这导致人们呼吁对学院-产业联系进行更深入的研究(Krimsky 2013)。这些发现中的大多数都不适合从理论上进行概括,因为它们都是在特定领域中借鉴的具体案例。更重要的是,目前科学研究的子领域之间的隐性分工无法实现理论进步。科学政策
本文章由计算机程序翻译,如有差异,请以英文原文为准。
How can governance change research content? Linking science policy studies to the sociology of science
Although science studies routinely assume that governance can change research content, we know little about how it does that. Science policy actors, commercial interests and civil society actors utilise a variety of governance instruments and processes to change the directions or to improve the quality of research. Both can be achieved only by making researchers select different goals and approaches, that is, change the content of their work. A recent review returned very few studies that investigated the impact of governance on research content and even fewer that convincingly established causality (Gläser and Laudel 2016). Empirical studies of competitive project funding focused on the validity and reliability of selection procedures and largely shunned the investigation of pre-emptive adaptation of project content or effects of selective funding on the dynamics of research fields (ibid: 122–125). The governance of emerging fields has been studied with the fields’ growth as the only dependent variable approximating content (ibid: 126–129). Most studies of the effects of performance-based funding limit themselves to changes in publication behaviour, whose causal ascription to performance-based funding can charitably be described as tenuous (ibid: 129–134; Gläser 2017). Finally, studies of academy–industry links have produced some interesting results on the impact of such links on the diffusion of knowledge (Evans 2010a; b) and on the increased likelihood of findings that are consistent with an industrial funder’s interests (Krimsky 2013) and on the impact of such links on the diffusion of knowledge (Evans 2010a; b). However, the empirical evidence of many studies is contradictory, which has led to a call for more in-depth studies of academy–industry links (Krimsky 2013). Most of these findings do not lend themselves to theoretical generalisation because they draw on specific cases in particular fields. More importantly, theoretical progress cannot be achieved with the current implicit division of labour between subfields of science studies. Science policy
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