Abductive Research Methods in Psychological Science

This chapter discusses a number of different abductive research methods of relevance to psychological research. The first of these, exploratory factor analysis, has been widely employed to generate rudimentary explanatory theories about common causes, although it is not generally recognized as an abductive method. The second method, analogical modelling, can be viewed as an abductive strategy for developing explanatory theories once they have been generated. The third abductive method, known generally as inference to the best explanation, gets formulated in different ways. These methods of inference to the best explanation can be used to evaluate the worth of competing explanatory theories. Theories of explanatory coherence are important in this regard.

Comparing Theories with the Ising Model of Explanatory Coherence (IMEC)

Theories are among the most important tools of science. Lewin (1943) already noted “[t]here is nothing as practical as a good theory”. Although psychologists discussed problems of theory in their discipline for a long time, weak theories are still widespread in most subfields. One possible reason for this is that psychologists lack the tools to systematically assess the quality of their theories. Thagard (1989) developed a computational model for formal theory evaluation based on the concept of explanatory coherence. However, there are possible improvements to Thagard’s (1989) model and it is not available in software that psychologists typically use. Therefore, we developed a new implementation of explanatory coherence based on the Ising model. We demonstrate the capabilities of this new Ising Model of Explanatory Coherence (IMEC) on several examples from psychology and other sciences. It is also available in the R-package IMEC so that it can help scientists to evaluate the quality of their theories in practice.

Past as prologue: Approaches to the study of confirmation in science

In the 1970s, quantitative science studies were being pursued by sociologists, historians, and information scientists. Philosophers were part of this discussion, but their role would diminish as sociology of science asserted itself. An antiscience bias within the sociology of science became evident in the late 1970s, which split the science studies community, notably causing the “citationists” to go their own way. The main point of contention was whether science was a rational, evidence-based activity. To reverse the antiscience trend, it will be necessary to revive philosophical models of science, such as Bayesian confirmation theory or explanatory coherence models, where theory-experiment agreement plays a decisive role. A case study from the history of science is used to illustrate these models, and bibliometric and text-based methods are proposed as a source of data to test these models.

Reliability profile of an information source: The most basic version

The aim of this paper is an attempt at analyses and reconciliation of some prima facie confronted theories of reliability in the context of formal theories of coherence. Formal coherentists attempted to show that there is an epistemologically interesting connection between coherence of an information set and reliability of information sources. Amongst these authors there are divisions and differences concerning the nature of coherence, as well as the nature of reliability. On the one side, we have before us probabilistic coherentists who support a statistical understanding of reliability. On the other side we have supporters of explanatory coherence who see reliability as a dispostition. There are two goals that we shall attempt to achieve in this paper: to present and explain some ideas of reliability, without going into fine detailes and depths of theories in which they were formulated and to show that those ideas about reliability are not that irreconcilable as they might appear, but that they together can form something that we shall call ?reliability profile of an information source?, ?the most basic version?, or shorter: RPISbasic.

Philosophy Matters

Philosophy is the attempt to answer general questions about the nature of knowledge, reality, and values. Natural philosophy draws heavily on neuroscience and psychology to develop interconnected theories of knowledge, reality, morality, justice, meaning, and the arts. It uses a procedure that identifies the most important philosophical issues as questions, considers a range of available answers to these questions, evaluates these answers based on coherence with scientific knowledge and other defensible philosophical doctrines, and reaches philosophical conclusions by accepting some answers and rejecting others based on explanatory coherence with evidence and on emotional coherence with human goals. Philosophy differs from science in being more general, ranging across all of the sciences, and in being more normative, concerned with how the world can be made better.