Online research in philosophy

Organic chemists have been able to develop a robust, theoretical understanding of the phenomena they study; however, the primary theoretical devices employed in this field are not mathematical equations or laws, as is the case in most other physical sciences. Instead it is the diagram, and in particular the structural formula, that carries the explanatory weight in the discipline. To understand how this is so, it is necessary to investigate both the nature of the diagrams employed in organic chemistry and how these diagrams are used in the explanations of the discipline. I will begin this paper by describing and characterizing the roles of the most important sort of diagram used in organic chemistry. Next I will present a model of explanations in organic chemistry and describe how diagrams contribute to these explanations. This will be followed by two examples that will support my abstract account of the role of diagrams in the explanations of organic chemistry.

This paper presents an integrative, descriptive model of ethical decision making, with special attention given to issues of measurement. After building the model, hypotheses are developed from a portion of it. These hypotheses are tested in an exploratory analysis to determine if further research and testing of this model and the measurement instruments it employs are warranted.

In recent years, there has much attention given by philosophers to the ubiquitous role of models and modeling in the biological sciences. Philosophical debates has focused on several areas of discussion. First, what are models in the biological sciences? The term ‘model’ is applied to mathematical structures, graphical displays, computer simulations, and even concrete organisms. Is there an account which unifies these disparate structures? Second, scientists routinely distinguish between theories and models; however, this distinction is more difficult to draw in the biological sciences since biologists often only have a variety of models and rarely have something like a fundamental theory. What then is a theory in biology? Third, how are models related to empirical or “target” systems?

The purpose of this paper is to provide an analysis of the concept of model as it is applied in the physical sciences, and to show that this analysis is fruitful insofar as it can be used as an acceptable account of the role of models in physical explanation.A realist interpretation of theories is adopted as a point of departure. A distinction between theories and models is drawn on the basis of this interpretation. The relation between model and prototype is expressed in terms of the concepts of access and accessibility, and four conditions are proposed as an analysis of the concept of model. It is concluded that models are introduced when approximate methods are used.

This commentary is intended to illuminate Gold's & Stoljar's main contentions by exploiting a favorite comparison, namely, that between biology and electronics. Roughly, and leaving out Darwinian theory and the like, biology is physics and chemistry plus natural history just as electronics is physics plus wiring diagrams. Natural history (even that discovered by sophisticated apparatus such as electron microscopes) contains generalizations, not laws. Psychology and cognitive science typically give more abstract explanations, as do “block diagrams” in electronics, and are less dispensable.

It is argued that due to the complexity of most economic phenomena, the chances of deriving correct models from a priori principles are small. Instead are more descriptive approach to modelling should be pursued. Agent-based modelling is characterised as a step in this direction. However many agent-based models use off-the-shelf algorithms from computer science without regard to their descriptive accuracy. This paper attempts an agent model that describes the behaviour of subjects reported by Joep Sonnemans as accurately as possible. It takes a structure that is compatible with current thinking cognitive science and explores the nature of the agent processes that then match the behaviour of the subjects. This suggests further modelling improvements and experiments.

Through an examination of the actual research strategies and assumptions underlying the Human Genome Project (HGP), it is argued that the epistemic basis of the initial model organism programs is not best understood as reasoning via causal analog models (CAMs). In order to answer a series of questions about what is being modeled and what claims about the models are warranted, a descriptive epistemological method is employed that uses historical techniques to develop detailed accounts which, in turn, help to reveal forms of reasoning that are explicit, or more often implicit, in the practice of a particular field of scientific study. It is suggested that a more valid characterization of the reasoning structure at work here is a form of case-based reasoning. This conceptualization of the role of model organisms can guide our understanding and assessment of these research programs, their knowledge claims and progress, and their limitations, as well as how we educate the public about this type of biomedical research.

This paper aims to identify the key characteristics of model organisms that make them a specific type of model within the contemporary life sciences: in particular, we argue that the term “model organism” does not apply to all organisms used for the purposes of experimental research. We explore the differences between experimental and model organisms in terms of their material and epistemic features, and argue that it is essential to distinguish between their representational scope and representational target. We also examine the characteristics of the communities who use these two types of models, including their research goals, disciplinary affiliations, and preferred practices to show how these have contributed to the conceptualization of a model organism. We conclude that model organisms are a specific subgroup of organisms that have been standardized to fit an integrative and comparative mode of research, and that it must be clearly distinguished from the broader class of experimental organisms. In addition, we argue that model organisms are the key components of a unique and distinctively biological way of doing research using models.

In this article, three descriptive models are described and compared in an attempt to discover the minimum number of concepts and relations necessary to an abstract description of social structure. It is argued that a "situational model" which uses the concepts of social time, social space and social role together with the relations of internal structure and external distribution is both adequate to the task and superior to the two other models. The advantages and implications of the situational model are discussed.