Factive Scientific Understanding Without Accurate Representation

This paper analyzes two ways idealized biological models produce factive scientific understanding. I then argue that models can provide factive scientific understanding of a phenomenon without providing an accurate representation of the (difference-making) features of their real-world target system(s). My analysis of these cases also suggests that the debate over scientific realism needs to investigate the factive scientific understanding produced by scientists’ use of idealized models rather than the accuracy of scientific models themselves

The Explanatory Value of Abstracting Away from Idiosyncratic and Messy Detail

Some explanations are relatively abstract: they abstract away from the idiosyncratic or messy details of the case in hand. The received wisdom in philosophy is that this is a virtue for any explanation to possess. I argue that the apparent consensus on this point is illusory. When philosophers make this claim, they differ on which of four alternative varieties of abstractness they have in mind. What's more, for each variety of abstractness there are several alternative reasons to think that the variety of abstractness in question is a virtue. I identify the most promising reasons, and dismiss some others. The paper concludes by relating this discussion to the idea that explanations in biology, psychology and social science cannot be replaced by relatively micro explanations without loss of understanding.This work has received funding from the European Research Council under the European Union’s Seventh Framework Programme (FP7/2007-2013)/ERC Grant agreement no 284123.This is the author accepted manuscript. The final version is available from Springer via http://dx.doi.org/10.1007/s11098-015-0554-

The Psychobiology of Hunger – A Scientific Perspective

From a scientific perspective, hunger can be regarded as an identifiable conscious sensation which can be distinguished from other conscious states (e.g., pain, fear). The hunger state can be measured and is a marker of the existence of underlying biological processes. Measured hunger is functional and is normally associated with the act of eating. However, the conscious state of hunger, although driven physiologically, is not exclusively determined by biology; there is an environmental influence that can modulate its intensity and periodicity, and cultural factors that shape the appropriateness of the expression of hunger. Within a psychobiological framework, hunger can be considered as the expression of a ‘need state’ which mediates between biological requirements and environmental (nutritional) satisfaction. Our empirical studies show that hunger is clearly associated with biological signals (e.g., resting metabolic rate and some gastrointestinal peptides) and is central to the relationship between energy expenditure and energy intake

First principles in the life sciences: the free-energy principle, organicism, and mechanism

The free-energy principle states that all systems that minimize their free energy resist a tendency to physical disintegration. Originally proposed to account for perception, learning, and action, the free-energy principle has been applied to the evolution, development, morphology, anatomy and function of the brain, and has been called a postulate, an unfalsifiable principle, a natural law, and an imperative. While it might afford a theoretical foundation for understanding the relationship between environment, life, and mind, its epistemic status is unclear. Also unclear is how the free-energy principle relates to prominent theoretical approaches to life science phenomena, such as organicism and mechanism. This paper clarifies both issues, and identifies limits and prospects for the free-energy principle as a first principle in the life sciences

Big dragons on small islands: generality and particularity in science

Angela Potochnik’s Idealization and the Aims of Science (Chicago) defends an ambitious and systematic account of scientific knowledge: ultimately science pursues human understanding rather than truth. Potochnik argues that idealization is rampant and unchecked in science. Further, given that idealizations involve departures from truth, this suggests science is not primarily about truth. I explore the relationship between truths about causal patterns and scientific understanding in light of this, and suggest that Potochnik underestimates the importance and power of highly particular narrative explanations