Klein and Myers’ (1999) statement that the natural science model of social science is widely accepted in information systems (IS) epitomises the ongoing debate in IS research about the research foundations and the methods that are applicable in the discipline. This is neither a new problem, nor one isolated to IS. Right from the enlightenment, the abandoning of the theological and the metaphysical led to the reliance on science as the philosophical foundation and direction for enquiry and study. This developing view of what is scientific led to the classification of sciences and an increasing dominance of reductionism as the consensus approach. Comte placed sociology as the pinnacle of science, where all science merges to act on humans. Furthermore, it was Durkheim who sought to place social science on what was perceived as the firmer foundation of natural sciences, viewing the social realm as external to us and hence best addressed by the empirical methods of natural sciences (Prowse, 2005). Human agency was eclipsed and individuals became part of a collective, a deterministic social machine. While Durkheim’s influence may have waned, the ideas of what is scientific and its application to our understanding ourselves as social beings have been woven into our culture and way of thinking. The dominance of logical positivism and empiricism in the 20th century right up to the 1960s suggested that anything not grounded in empirical, repeatable observation should be rejected and was ‘unscientific’. The high regard for natural sciences by the logical positivists led to its reification and the view of social sciences as a lower form of academic pursuit. Popper’s refining of logical positivism established an ideology that scientific method required theory and that theory must be refutable. Good scientific theory is a prohibition (Ebringer, 2011). Such a philosophy underpins much of IS research in which hypotheses are proposed and then declared true or false as a result of the statistical analysis of surveys. Critical to the logical positivism view of scientific endeavour was a stripping of context and time. Science practice was seen as ahistorical (Okasha, 2002). Positivism sought to strip philosophy itself of reflection and metaphysics and make it more ‘scientific’. However, as logical empiricism disintegrated; it was understood that science is far from a simply neutral and objective process. Rather it is influenced by history, context and is strongly political. Kuhn’s (2012) The Structure of Scientific Revolutions opened the debate on the nature of science and its practice; something reflected in sociological treatments such as Latour’s (1988) Science in Action. The underlying belief or rather worldview which sees science and scientific ‘method’ as the sole arbiter for thinking and acting has not only persisted but grown in academia. In business schools, a dominant scientific model including abstract financial and economic analysis, statistical multiple regressions, and laboratory psychology (Bennis and O’Toole, 2005) not only excluded exploration of alternatives but rendered research irrelevant to practice and devoid of political and economic context. The questioning of whether IS is a science only reflects debates in business schools or in economics departments where the failure to predict the recent financial crisis despite a plethora of mathematical models raised severe doubts as to the scientific credentials of economics (Wang, 2013). The afterglow of positivist philosophy permeates popular culture: ‘Philosophy is dead . . . scientists have become the bearers of the torch of discovery in our quest for knowledge’ according to Hawking and Mlodinow (2010). This dominant paradigm subordinates social sciences as secondclass citizens below the natural sciences and creates an ambition to rise to the standards of natural science in our study of IS. And yet as the paradigm of the scientific method frays at the edge as Kuhn predicted, more and more effort is made to ignore problems or explain away the inadequacies of the scientific method in social sciences. The authors’ treatment of natural sciences and questioning what we believe in natural science is one such attempt. If efforts to achieve our ambition to raise social science to the level of respect accorded natural sciences in our society is failing our response will be to reinterpret natural sciences. If we apparently cannot raise our status to that of Human in the loop

中文翻译：

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人在循环

Klein 和 Myers (1999) 声明社会科学的自然科学模型在信息系统 (IS) 中被广泛接受，这集中体现了信息系统研究中关于研究基础和适用于该学科的方法的持续争论。这既不是一个新问题，也不是孤立于 IS 的问题。从启蒙开始，对神学和形而上学的抛弃，导致了依靠科学作为探究和研究的哲学基础和方向。这种关于什么是科学的不断发展的观点导致了科学的分类，以及越来越多的还原论成为共识方法。孔德将社会学视为科学的顶峰，所有科学在这里融合以作用于人类。此外，涂尔干试图将社会科学置于被认为是更坚实的自然科学基础之上，将社会领域视为我们之外的领域，因此最好通过自然科学的经验方法来解决（普劳斯，2005 年）。人类的能动性黯然失色，个人成为集体、确定性社会机器的一部分。虽然涂尔干的影响力可能已经减弱，但关于什么是科学的概念及其在我们理解自己作为社会存在方面的应用已经融入了我们的文化和思维方式。逻辑实证主义和经验主义在 20 世纪直至 1960 年代的主导地位表明，任何不基于经验的、可重复的观察的东西都应该被拒绝，并且是“不科学的”。逻辑实证主义者对自然科学的高度重视导致了自然科学的具体化，并将社会科学视为学术追求的低级形式。波普尔对逻辑实证主义的提炼确立了一种意识形态，即科学方法需要理论，而理论必须是可驳斥的。好的科学理论是一种禁令（Ebringer，2011）。这种哲学支撑着很多 IS 研究，在这些研究中，假设被提出，然后作为调查统计分析的结果宣布为真或假。对科学努力的逻辑实证主义观点至关重要的是剥离背景和时间。科学实践被视为非历史性的（Okasha，2002）。实证主义试图剥夺哲学本身的反思和形而上学，使其更加“科学”。然而，随着逻辑经验主义的瓦解；据了解，科学远非简单的中立和客观过程。相反，它受到历史、背景的影响，并且具有强烈的政治色彩。库恩 (2012) 的《科学革命的结构》开启了关于科学本质及其实践的辩论；一些反映在社会学治疗中的东西，例如拉图尔 (Latour) (1988) 的《科学在行动》中。将科学和科学“方法”视为思考和行动的唯一仲裁者的基本信念或更确切地说是世界观，不仅在学术界持续存在，而且在不断发展。在商学院，包括抽象金融和经济分析、统计多元回归和实验室心理学在内的占主导地位的科学模型（Bennis 和 O'Toole，2005 年）不仅排除了对替代方案的探索，而且使研究与实践无关，并且缺乏政治和经济背景. 对 IS 是否是一门科学的质疑仅反映了商学院或经济学系的争论，尽管有过多的数学模型，但未能预测最近的金融危机，这引发了对经济学科学凭证的严重怀疑（Wang，2013 年）。实证主义哲学的余辉渗透到流行文化中：“哲学已死”。. . 根据霍金和姆洛迪诺（Hawking and Mlodinow，2010）的说法，科学家们已成为我们寻求知识的发现火炬的承担者。这种主导范式将社会科学置于自然科学之下的二等公民，并在我们对 IS 的研究中创造了达到自然科学标准的雄心。然而，正如库恩所预测的那样，科学方法的范式在边缘发生了冲突，人们越来越努力地忽视问题或解释社会科学中科学方法的不足之处。作者对自然科学的处理和质疑我们对自然科学的信仰就是这样一种尝试。如果努力实现我们将社会科学提高到社会对自然科学的尊重水平的努力失败了，我们的回应将是重新解释自然科学。如果我们显然不能将我们的地位提升到循环中的人类地位 如果努力实现我们将社会科学提高到社会对自然科学的尊重水平的努力失败了，我们的回应将是重新解释自然科学。如果我们显然不能将我们的地位提升到循环中的人类地位 如果努力实现我们将社会科学提高到社会对自然科学的尊重水平的努力失败了，我们的回应将是重新解释自然科学。如果我们显然不能将我们的地位提升到循环中的人类地位