That's Interesting! A Flawed Article Has Influenced Generations of Management Researchers

Davis's (1971) article “That's interesting! Towards a phenomenology of sociology and a sociology of phenomenology” is regarded by many management researchers as a classic work and a basis for guiding management studies; in the wake of its publication, an interesting research advocacy gradually emerged. However, from the perspective of scientific research, Davis's core argument that great theories have to be interesting is seriously flawed. Interestingness is not regarded as a virtue of a good scientific theory and thus has little value in science. Moreover, obsession with interestingness can lead to at least five detrimental outcomes, namely promoting an improper way of doing science, encouraging post hoc hypothesis development, discouraging replication studies, ignoring the proper duties of a researcher, and undermining doctoral education.

Epistemology, Philosophy of Science, and Virtue

This chapter offers an overview of how virtue-based concepts have been used by philosophers of science to shed light on epistemic aspects of science. In the epistemology of science, the word virtue has referred to two different concepts. First, virtue can be understood as excellence, where excellence is a quality of a model, a theory, or a hypothesis. Second, virtue can be understood more narrowly as a stable character trait and/or disposition of scientists themselves. The first meaning is connected to the long-standing debate on the qualities that make a scientific theory a good scientific theory. The second meaning is connected to a much more recent conversation exploring the connections between virtue epistemology and philosophy of science. I explore how these two meanings of virtue have been developed, and I highlight underexplored areas that can advance our understanding of the relation between virtue theory and philosophy of science.

Philosophy and Physics

Philosophy is the escape from the darkness of superstition and ignorance, and the ascent into the world of light and knowledge. It is “the vision of truth,” or what the Greeks called “the gift of wonder.” Adding to such a gift is science, the systematic study of nature and the organization of acquired knowledge into timeless, universal, causal, testable laws that are derived from observation and rational consideration. A good scientific theory makes experimentally verifiable and falsifiable predictions, which must be tested by experiment. Science is evidence-based knowledge; it is not knowledge based on opinion or dogma. In the quest for truth about nature, science without (the wisdom of) philosophy is rational but (arguably) dull, and philosophy without (the empirical facts of) science is wise but (experimentally) unverified. The road to the truth is paved by science and philosophy, but certainly by other fields, too. The view is otherwise crude and muddled.

Simplicity and Model Selection

Is simplicity a virtue of a good scientific theory, and are simpler theories more likely to be true or predictively successful? If so, how much should simplicity count vis-à-vis predictive accuracy? We address this question using Bayesian inference, focusing on the context of statistical model selection and an interpretation of simplicity via the degree of freedoms of a model. We rebut claims to prove the epistemic value of simplicity by means of showing its particular role in Bayesian model selection strategies (e.g., the BIC or the MML). Instead, we show that Bayesian inference in the context of model selection is usually done in a philosophically eclectic, instrumental fashion that is more tuned to practical applications than to philosophical foundations. Thus, these techniques cannot justify a particular “appropriate weight of simplicity in model selection”.

The case against memory consolidation in REM sleep: Balderdash!

Unfortunately, some researchers think a good scientific theory is one that has been repeatedly confirmed, and a bad theory is one that has not received consistent confirmation. However, confirmation of a theory depends on the extent to which a hypothesis exposes itself to disconfirmation. One confirmation of a highly specific, falsifiable experiment can have a far greater impact than the disconfirmation of twenty experiments that are virtually unfalsifiable. This commentary (1) counteracts misleading biases regarding the REM sleep/memory consolidation theory, and (2) demonstrates how chaotic cerebral activation during sleep is an essential component of long-term memory storage processes.[Vertes & Eastman]