How organizational cognitive neuroscience can deepen understanding of managerial decision-making:a review of the recent literature and future directions

There is growing interest in exploring the potential links between human biology and management and organization studies, which is bringing greater attention to bear on the place of mental processes in explaining human behaviour and effectiveness. The authors define this new field as organizational cognitive neuroscience (OCN), which is in the exploratory phase of its emergence and diffusion. It is clear that there are methodological debates and issues associated with OCN research, and the aim of this paper is to illuminate these concerns, and provide a roadmap for rigorous and relevant future work in the area. To this end, the current reach of OCN is investigated by the systematic review methodology, revealing three clusters of activity, covering the fields of economics, marketing and organizational behaviour. Among these clusters, organizational behaviour seems to be an outlier, owing to its far greater variety of empirical work, which the authors argue is largely a result of the plurality of research methods that have taken root within this field. Nevertheless, all three clusters contribute to a greater understanding of the biological mechanisms that mediate choice and decision-making. The paper concludes that OCN research has already provided important insights regarding the boundaries surrounding human freedom to act in various domains and, in turn, self-determination to influence the workplace. However, there is much to be done, and emerging research of significant interest is highlighted

Experimentation on Analogue Models

Summary Analogue models are actual physical setups used to model something else. They are especially useful when what we wish to investigate is difficult to observe or experiment upon due to size or distance in space or time: for example, if the thing we wish to investigate is too large, too far away, takes place on a time scale that is too long, does not yet exist or has ceased to exist. The range and variety of analogue models is too extensive to attempt a survey. In this article, I describe and discuss several different analogue model experiments, the results of those model experiments, and the basis for constructing them and interpreting their results. Examples of analogue models for surface waves in lakes, for earthquakes and volcanoes in geophysics, and for black holes in general relativity, are described, with a focus on examining the bases for claims that these analogues are appropriate analogues of what they are used to investigate. A table showing three different kinds of bases for reasoning using analogue models is provided. Finally, it is shown how the examples in this article counter three common misconceptions about the use of analogue models in physics

Technology as 'Applied Science': a Serious Misconception that Reinforces Distorted and Impoverished Views of Science

The current consideration of technology as 'applied science', this is to say, as something that comes 'after' science, justifies the lack of attention paid to technology in science education. In our paper we question this simplistic view of the science-technology relationship, historically rooted in the unequal appreciation of intellectual and manual work, and we try to show how the absence of the technological dimension in science education contributes to a na¿ ve and distorted view of science which deeply affects the necessary scientific and technological literacy of all citizens

Understanding Scientific Practices: The Role of Robustness Notions

This article explores the role of `robustness-notions¿ in an account of the engineering sciences. The engineering sciences aim at technological production of, and intervention with phenomena relevant to the (dis-)functioning of materials and technological devices, by means of scientific understanding thereof. It is proposed that different kinds of robustness-notions enable and guide scientific research: (1) Robustness is as a metaphysical belief that we have about the physical world ¿ i.e., we believe that the world is robust in the sense that the same physical conditions will always produce the same effects. (2) `Same conditions ¿ same effects¿ functions as a regulative principle that enables and guides scientific research because it points to, and justifies methodological notions. (3) Repetition, variance and multiple-determination function as methodological criteria for scientific methods that justify the acceptance of epistemological and ontological results. (4) Reproducibility and stability function as ontological criteria for the acceptance of phenomena described by A¿B. (5) Reliability functions as an epistemological criterion for the acceptance of epistemological results, in particular law¿like knowledge of a conditional form: ¿A¿B, provided Cdevice, and unless other known and/or unknown causally relevant conditions.¿ The crucial question is how different kinds of robustness¿notions are related and how they play their part in the production and acceptance of scientific results. Focus is on production and acceptance of physical phenomena and the rule-like knowledge thereof. Based on an analysis of how philosoophy of science tradtionally justified scientific knowledge, I propose a general schema that specifies how inferences to the claim that a scientific result has a certain epistem ological property (such as truth) are justified by scientific methods that meet specific methodological criteria. It is proposed that `same conditions ¿ same effects¿ as a regulative criterion justifies `repetition, variation and ultiple¿determination¿ as methodological criteria for the production and acceptance of (ontological and epistemological) scientific result

Rigorous Results, Cross-Model Justification, and the Transfer of Empirical Warrant: The Case of Many-Body Models in Physics

This paper argues that a successful philosophical analysis of models and simulations must accommodate an account of mathematically rigorous results. Such rigorous results may be thought of as genuinely model-specific contributions, which can neither be deduced from fundamental theory nor inferred from empirical data. Rigorous results provide new indirect ways of assessing the success of models and simulations and are crucial to understanding the connections between different models. This is most obvious in cases where rigorous results map different models on to one another. Not only does this put constraints on the extent to which performance in specific empirical contexts may be regarded as the main touchstone of success in scientific modelling, it also allows for the transfer of warrant across different models. Mathematically rigorous results can thus come to be seen as not only strengthening the cohesion between scientific strategies of modelling and simulation, but also as offering new ways of indirect confirmation

Understanding the developing role of global health partnerships on access to medication: an STS perspective

A conceptual framework for studying the role of global health partnerships (GHPs) in determining policy practices on access to medication is presented. Although GHPs are of a practical nature, they are implicitly theory informed. The narratives used by GHP partners in relating to access to medication have theoretical origins. Building on the theoretical literature on models and the notion of embodied knowledge found in science and technology studies, GHPs are conceptualized as models that mediate between theory and practice. The proposed framework can be used to investigate the role of theory in the creation of GHP models and how the models shape global and national policy practices. A social constructivist approach is suggested as a suitable method for empirical analysis