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

我的研究关注的是如何在科学家中传播新的科学知识，以及传播带来的扭曲如何影响知识的构建和发展。科学家通过发布他们的实验结果来为特定的证据库做出贡献，但在撰写论文时，他们也使用其他人提供的证据。然而，他们引用的证据往往是有选择性的，而且他们对这些证据的解释可能会有所不同。我问的问题包括：当科学家引用证据时，他们的客观程度如何？为什么一些发现和解释变得广为人知，而另一些则变得默默无闻？以及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？我对这些问题的方法包括：-系统地进行文献搜索，以获取与特定科学辩论相关的所有论文。-绘制这些论文之间的引用图，并分析网络以了解证据使用的动态。-特定索赔网络分析，以分析对具体论文的解释，评估其对科学意见的影响，并在证据选择方面发现偏见。-主要路径分析，以确定涉及主流研究的研究-经常被引用的论文及其相互引用。这提供了一个框架，用于评估特定研究和发现的传播及其对科学发展的影响，包括引用扭曲的流行及其对科学观点的影响。我应用这种方法来理解1908-1984年科学文献中饮食脂肪与冠心病因果关系的猜想的发展。主要结果是(I)科学家倾向于引用最近发表的文献，这些文献涉及与引用论文类似的研究问题。(2)引文分布符合幂规律，即相对较少的核心论文经常被不成比例地引用。(3)支持这一联系的调查结果比不支持这一结论的调查结果更多地被引用，其影响被作为幂定律分布基础的因素放大。(Iv)片面引用偏差，即选择性地只引用支持某一特定结论的证据的行为，在审查心脏病患者饮食治疗有效性的综述中很普遍。这种偏见影响了已发表的结论；82%的支持这种治疗的综述只引用了支持这一结论的一项临床试验，而忽略了文献中三项不支持这一结论的试验。虽然我将这种方法应用于具体的案例研究，但其设计和方法将适用于其他案例。在这次奖学金期间，我将发表我对饮食-心脏辩论的分析，并将我的发现传播给不同学术界的不同科学家受众、对循证政策感兴趣的政策制定者和普通公众。我将利用我在定量科学研究和引用偏差方面的专业知识，通过为爱丁堡大学的“负责任的度量”小组做出贡献，为正在进行的提高研究完整性的努力做出贡献。我将用3周的时间访问莱顿大学，在那里我将展示我的研究成果，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。我还将在一次会议上与苏格兰议会和下议院的研究人员讨论，让政策制定者参与进来，向研究人员介绍引用偏差的问题及其检测方法。最后，我将启动一个新的研究项目，重点不是一场历史性的辩论，而是目前正在展开的一场争论，这场争论的主题是，荷尔蒙“催产素”具体涉及社会行为，具有治疗自闭症的潜在益处。

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.