Philosophy of Science book

by Rani Lill Anjum and Elena Rocca

The book is under contract with the Palgrave Philosophy Today series

List of contents


1. What counts as scientific knowledge?

We all have some idea of what science is and what it means to do science. The question is whether there is a common definition of science that everyone could accept. We might take for granted that science is the best way to generate knowledge, but how exactly does it do so? What are the features of science that make it superior to other knowledge-generating systems? Are there some scientific approaches that are better than others, and how are we able to decide what these are? In this chapter we look at some suggestions for how to define science and show that this is not a settled debate, neither among philosophers nor scientists.

2. Should science be defined by its methods?

Returning to the question, ‘What is science?’, various suggestions have been offered. Some say that science is best defined by its methods, but this just brings us to another question: ‘Which methods?’ There are many different types of methods in science, and none of them seem universally accepted. Are some methods better than others? If so, then what exactly make them better?

3. Is science defined by its community?

Here, we look at different views on how science happens, or should happen, within a scientific community. While some philosophers of science see scientific practice and discovery as something that stands on its own, regardless of the wider scientific community, others take communities to be crucial. For instance, who accepts or rejects new data as valuable results, and given which assumptions? If two researchers can arrive at different conclusions when considering the same empirical data, as we will see in part II and III is quite common in scientific controversies, the question remains how our gathering and use of data can ever remain objective and independent on the scientific community to which we belong. Should science be a democratic matter, where we accept the theory that has the most support in the scientific community? That seems to go against intellectual freedom, but also against the historical fact that most theories we accept today started out as the minority view.

4. Is science defined by power?

We have seen that philosophers of science disagree over what science is, what is the best method for science and how or even whether science can make progress. In sum, there seems to be no commonly accepted way to guarantee objective and true scientific results. A question is then whether science can ever be objective or independent of prior beliefs. In this chapter we will see how philosophers such as Paul Feyerabend and Sandra Harding challenge the objectivity and democracy of science and then look at how power structures influence science and technology.


5. Conflicting evidence and the bias that science cannot avoid

We introduce the idea of philosophical bias (basic implicit assumption in science) and explain how they influence the whole enterprise of science: from the formulation of meaningful research questions and the choice of method, to the evaluation and interpretation of evidence. We will also explain and show with examples that such conceptual premises are necessary to do science: they are, in other words, the one bias that science cannot avoid.

6. What is causation? Scientific methods and causal evidencing

We here explain some of the existing philosophical theories of causation, and we will argue that the choice of what is the best way to evidence causation in science depends on what one thinks causation is. The latter is a conceptual, non-evidential premise that one could acquire from one’s discipline or from the current paradigm: it is, then, a philosophical bias. We use some examples to show how philosophical bias about causation can influence the choice of scientific method to establish causation.

7. Processes or entities? Understanding and analysing complexity

In this chapter, we explain some basic principles of two ontologies: substance ontology and process ontology. These two world-views differ on what they take to be more basic: dynamic processes of change in one case, or static entities or things in the other. We will show how this philosophical and abstract discussion has theoretical, methodological and practical consequences for science.

8. Realism or relativism? Knowledge as objective or constructed

We present two opposite stances about scientific knowledge: realism and constructivism (relativism). Realists see scientific knowledge as something factual, real, and objective. Constructivism, or relativism, is the view that scientific truths are created by our perspectives and social cultures. We will show how these two stances translate into different views on the hierarchy of knowledge and the role of big data, as well as different opinions on the expert/layman divide and different levels of participation into the research design.

9. Probability, uncertainty or propensity? Defining and assessing risk

This chapter deals with risk and risk evaluations. Since the beginning of 20th century, with increasing role of technology for development and production, the notion of ‘risk’ has become ubiquitous in science and science-based decision-making. We are often told that a problem is handled with a ‘risk perspective’, or with a ‘risk-based approach’. However, ‘risk’ is a multifaceted concept, and has different meanings that are sometimes discipline-specific. An economist and a medical researcher might both talk about risk, meaning rather different things. We will here explore some of the implicit philosophical biases linked to the concept of risk.


10. Philosophical analysis of some cases of disagreement

We have seen in Part II that different philosophical bias can motivate different, sometimes conflicting, scientific practices. We will now give some practical examples of how such analysis could look like. Philosophical bias of ontological, epistemological and ethical types are strictly intertwined and multiple types of philosophical bias can be found in each case. There is by definition no real-life cases that can be analysed in light of only one philosophical bias. However, our purpose in this chapter is to show the principle of how these kinds of analyses can be carried out. We have therefore made a selection of real-life cases of expert disagreement and focus on one type of philosophical bias per case.


We have shown that it is possible to analyse cases of expert disagreement over common evidence in light of diverging philosophical bias. The question remains: what comes next? What can we do, once we have identified and explicated the philosophical biases in a scientific controversy? If scientific evidence cannot solve a controversy, how could we proceed to develop strategies to do this, using extra-evidential elements? A first answer is about philosophical bias of an ethical type, or value judgements. The proposal is that once such implicit biases are explicated, the community that will be affected by the research can choose the scientific approach based on the value that most represents them. But how about all the other extra-evidential assumptions, for instance of an ontological nature? Is it possible to find a way to select one preferred philosophical bias, for instance about causation, over all others? This is a question that scholars are starting to address in the literature, and we now present some recent proposals.

Author: Rani Lill Anjum

I am a philosopher at NMBU, Norway. I work on causation etc.

%d bloggers like this: