Selective citation and the shaping of scientific knowledge: Citation network analysis and the diet-heart debate

我的研究关注的是发展新的科学知识是如何在科学家之间传播的理解，以及如何传播的扭曲对知识的建设和发展的影响。科学家通过发表他们的实验结果来为特定的证据基础做出贡献，但在撰写论文时，他们也使用他人提供的证据。然而，他们往往在他们引用的证据中有选择性，并且可以在他们对证据的解释中有所不同。我提出的问题包括：科学家在引用证据时有多客观？为什么有些发现和解释变得广为人知，而另一些却默默无闻？对过去研究的使用和解释如何塑造最终被视为科学知识的东西？我对这些问题的处理方法包括：-系统的文献检索，以捕获与特定科学辩论相关的所有论文。映射这些论文之间的引用，并分析网络以了解证据使用的动态。- 针对具体主张的网络分析，分析具体论文的解释，评估其对科学观点的影响，并检测证据选择中的偏见。- 主要路径分析，以确定研究主流中涉及的研究-被广泛引用的论文及其相互间的参考文献，这提供了一个框架，据以评估特定研究和成果的传播及其对科学发展的影响，包括引用失真的普遍性及其对科学观点的影响。我已经应用这种方法来理解猜想的发展，在1908-1984年的科学文献中，膳食脂肪与冠心病有因果关系。主要结果是：（i）科学家倾向于引用最近发表的文献，并解决了类似的研究问题的引用论文。(ii)幂律近似于引用分布，即，核心文件相对较少，被引用的次数不成比例。(iii)支持这种联系的研究结果比不支持的研究结果更常被引用，其影响被幂律分布的基础因素放大。(iv)片面引用偏见，即选择性地只引用支持特定结论的证据的行为，在检查饮食治疗对心脏病患者有效性的评论中很普遍。这种偏倚影响了已发表的结论; 82%支持这种治疗的综述仅引用了支持这一结论的单一临床试验，而忽略了文献中的三项不支持性试验。虽然我将这种方法应用于一个具体的案例研究，但其设计和方法也适用于其他案例。在此期间，我将发表我对饮食心脏辩论的分析，并将我的研究结果传播给不同学术界的科学家，对循证政策感兴趣的政策制定者和公众。我将利用我在定量科学研究和引用偏见方面的专业知识，通过为爱丁堡大学的“负责任的团队”做出贡献，为提高研究诚信做出贡献。我将花3周时间访问莱顿大学，在那里我将展示我的研究，并与欧洲领先的科学计量学和研究评估中心建立专业联系。我还将通过与苏格兰议会和下议院的研究人员讨论，在一次会议上向研究人员介绍引用偏见问题及其检测方法，从而参与决策社区。最后，我将开始一个新的研究项目，重点不是历史上的争论，而是目前正在展开的争论，关于激素“催产素”特别参与社会行为的概念，对自闭症的治疗有潜在的好处。

My research is concerned with developing an understanding of how new scientific knowledge is disseminated amongst scientists, and how distortions introduced by dissemination impact on the construction and development of that knowledge. Scientists contribute to a particular evidence-base by publishing the results of their experiments, but in writing their papers they also use evidence produced by others. However, they are often selective in the evidence that they cite, and can differ in their interpretations of that evidence. Amongst the questions that I ask are: how objective are scientists when they cite evidence? Why do some findings and interpretations become widely known while others fade into obscurity? And how does the use and interpretation of past studies shape what is eventually taken to be scientific knowledge?My approach to these questions involves:- Systematic literature searches to capture all papers relevant to a specific scientific debate.- Mapping the citations between these papers, and analysing the network to understand the dynamics of evidence use. - Claim-specific network analysis to analyse the interpretation of specific papers, to evaluate their impact on scientific opinion, and to detect bias in evidence selection. - Main path analysis to identify studies that are involved in the mainstream of research - well-cited papers and their references to one another.This provides a framework by which to evaluate the dissemination of particular studies and findings and their impact on scientific development, including the prevalence of citation distortions and their impact on scientific opinion.I have applied this approach to understand the development of the conjecture that dietary fats are causally related to coronary heart disease in the scientific literature from 1908-1984. The main outcomes were (i) Scientists tended to cite literature recently published and which addressed similar research questions to the citing paper. (ii) A power-law approximated the citation distribution i.e., a relatively few core papers were cited disproportionately often. (iii) Findings that supported the link were cited more often than unsupportive findings, and their impact was amplified by the factors that underlie the power law distribution. (iv) One-sided citation bias, the act of selectively citing only evidence that supports a particular conclusion, was prevalent in reviews that examined the effectiveness of dietary treatment in those with heart disease. This bias impacted published conclusions; 82% of reviews supportive of such treatment cited only the single clinical trial supporting this conclusion while ignoring the three unsupportive trials in the literature. While I applied this approach to a specific case-study, its design and methods will be applicable to other cases. During this Fellowship I will publish my analysis of the diet-heart debate, and disseminate my findings to diverse audiences of scientists in different academic communities, to policy makers interested in evidence-based policy, and to the general public. I will use my expertise in quantitative science studies and citation bias to contribute to ongoing efforts to improve research integrity by contributing to the 'Responsible Metrics' group at Edinburgh University. I will spend 3-weeks visiting Leiden University, where I will present my research and form professional ties with Europe's leading centre for scientometrics and research evaluation. I will also engage the policy-making community through discussions with researchers at the Scottish Parliament and House of Commons in a session introducing researchers to the problem of citation bias and methods for its detection. Finally, I will begin a new research project focussing not on a historical debate but on a currently unfolding controversy, about the notion that the hormone "oxytocin" is specifically involved in social behaviour, with potential benefits for the treatment of autism.