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Peter CopelandOver the past year or so, there has been continuous reference to complex social decisions as scientific, as though value judgments do not apply, or play only a limited role.

Some of the most prominent examples include the designation of types of work as essential/non-essential. Liquor stores have been open throughout the pandemic, but access to care and supports from a small circle of family and friends and places of worship was often not. The official justification references the concept of maintaining public health, supported by empirically informed measurements and predictions of rate of spread per type of occupancy and activity.

They were valid concerns, no doubt, and difficult decisions to make. We can all agree. But the value judgments that prioritize certain goals and activities implicit in these decisions are often downplayed and stamped with the imprimatur of science so as to lend them unquestionable support. To what extent do values enter into the equation?

There are two broad types of values operative in scientific inquiry: the epistemic and the normative. Both are essential components of scientific inquiry, though, as we’ll see, they run into one another due to their common status as values.

Epistemic values are principles that orient scientific inquiry. They assist the inquirer in the goal of scientific endeavour – explanation of some sort. There are different kinds of explanations – rendering a data point or set more consistent with other findings, making a connection between related phenomena more logically rigorous, or providing tighter explanations by filling in gaps in the causal story. All of the above involve an explanans (that which explains) and an explanandum (that which is to be explained). A scientific theory explains (explanans) a set of phenomena (explanandum).

This small list is already very revealing. Scientific inquiry is an activity with a purpose. As such, the standards of success and the methods used to achieve them are determined, in no small part, by the goal of the endeavour.

Here are a few examples to illustrate the point.

First, ontological simplicity: the idea that we should not multiply the entities that populate the object domain of study, or terms in a theoretical lexicon, in order to explain some phenomenon. It is also known as Ockham’s Razor, after William of Ockham, the 14th century Franciscan Friar.

By adhering to this principle, the temptation to make up a concept in order to solve some problem is easier to avoid. It is also closely linked to testability. The more entities and assumptions that are made in theorizing, the less testable is the theory, for there are simply too many moving parts.

However, there is no definitive reason why there should be fewer entities in one’s theoretical lexicon, or that the simpler explanation is the better one. In some sense, the principle is hygienic: it forces theoreticians or practitioners to be more rigorous about their practice than they might otherwise be. Very well then, but it is hardly a necessary feature of scientific inquiry.

Second, a preference for the falsifiability of a claim or theory. It is argued that if a claim is falsifiable, it marks it out as something with tangible implications. Without the ability to falsify a claim, or body of knowledge, it is said to be unworthy of scientific inquiry.

There are, naturally, limits to such a view, for not every piece of knowledge is falsifiable, even if it is nonetheless knowledge. Furthermore, what standard of falsifiability must we adhere to in order for something to count as scientific? Such simple questions demonstrate the extent to which the preference for falsifiability is indeed a value choice, determined by the nature of the question we are seeking to answer.

Evidently, values play a role in shaping the standards of inquiry, methods, and evaluation of the logic of a scientific conclusion, but must that be the case? Is there not a set of principles that others are reducible to?

If, for example, we take correspondence (to empirical observation) or consistency (with other known empirical facts) as our standard of truth, would it not follow that questions about method, explanation, and ontology have a clear and determinate answer?

At first glance, it would seem that there are foundational claims that are evidently true, and so form the bedrock and the litmus test for theories to pass. They would also serve as the starting point for hypotheses, for it is from these most basic statements that more complex ones can be deduced and inferred.

New scientific findings would have to correspond to repeated empirical observation. They would also have to be consistent with all of our other established knowledge, most importantly the bedrock claims.

It is here where we can see that the problem is much more pervasive. Independently, a philosopher, Willard Van Orman Quine, and a physicist, Pierre Duhem, arrived at a thesis about the underdetermination of theory by evidence.

In its various forms, it states that the evidence for a given claim (a proposition, or hypothesis, for example), or a larger body of claims (theory), is always underdetermined. The evidence can never provide sufficient grounds to conclusively deduce a particular conclusion from it.

It could be that other theories are equally consistent with the facts, but the evidence does not itself necessitate the choice of one explanation over another. Other, extraneous considerations enter into the equation in the process of selecting the explanation for the piece of evidence in question. This is a logical consequence of the relationship between evidence and a conclusion, as well as that which is empirically demonstrable.

The first is logical. There is nothing contained in an isolated piece of evidence that strictly entails a conclusion of some sort. We can see this by examining claims about the genetic versus environmental determinants of behaviour, for example.

If a collection of genes (a polygenetic score) is correlated with a pattern of behaviour, such as a personality trait, there is in principle no amount of data (by itself) that entails the conclusion that the genes cause the behaviour. This requires additional assumptions about the presence of other behaviours that affect the outcome, the path between individual genes and phenotypic expression in space and over periods of time, as well as non-empirical arguments about the understanding of what a cause is, and the contemporary taxonomy used in biology that cuts up the world in such a way that assigns privileged ontological and causal power to strands of DNA, for example.

This is not to say that all explanations are equal; that is nonsense. It is about showing that additional considerations extraneous to empirical observation are needed to fill in the logical gaps from the evidence to local causal explanation, and larger explanatory frameworks.

Quine’s epistemological holism is informed by the idea that no knowledge claim can be tested in isolation. We must always have recourse to a set of background assumptions – part of the web of understanding – in order to test even the simplest claim.

Yet, it does not go far enough. Before we are faced with a fork in the road in choosing between competing theoretical explanations for a set of data, we bring our nature, habits, values, personal and cultural history to bear on the world in perceiving and interacting with it.

For our purposes, then, the important conclusion is that values play a necessary role in the evaluation of the simplest claims to knowledge, as well as more complex choices between theories or explanatory frameworks.

All of these considerations go to show that much of scientific practice is non-empirical. There is no reason why any of the most commonly held assumptions about the standards and methods used in the sciences are required in order for something to be scientific or true. These values are principles used to help us in the pursuit of an explanation of some sort.

Far from this being a licence to say such things as atoms or particles are not real, genes do not causally influence behaviour, or everyone’s favourite ‘reality is socially constructed’ – such humdrum observations show what any scientist worth their salt would readily admit – scientific findings are empirically-based descriptions of the patterns and regularities that we find in the world around us. They are not the be-all and end-all of explanation. They are local explanations of aspects of the world around us that are provisional in nature.

However, the most common conclusion to be drawn from this sort of thinking in the 20th-century Western tradition – and now culture – is some form of skepticism about knowledge of a variety of types – scientific, philosophical, ethical, aesthetic, etc.

Yet, this is in no way entailed by the above considerations. Rather, we ought to realize that scientific inquiry consists of a set of methods that we use to rigorously observe a narrow range of reality around us, and systematically explain the causal relations between entities in that object domain.

Skepticism in all its many colours stems from a misunderstanding of the activity of scientific inquiry. Science does not say anything about the ‘meaning of life,’ the nature of causation, the origins of the universe, whether there is ‘free will’, etc., until its findings are combined with additional premises in an argument. Arguments, being made as they are in human language, are strictly speaking, philosophical in nature.

Philosophy is a practice that everyone does, every day of one’s life. It is the practice of thinking about the meaning of things. Simply put, reflection.

Like science, reflection – systematic or freewheeling, rigorous or intuitive – does not have much to say in isolation about the chemical structure of water, the causes of poverty in 16th century Italy, or the physics of black holes. Why? Quite simply, because it is a different kind of activity, with a different area of inquiry and a different set of questions that animate it.

Rather than science providing unmediated access to reality, the scientific outlook affords a perspective. Not a trivial one in the slightest, not the only one, not a self-sufficient one, but a perspective nonetheless.

Some would argue that there is nothing but perspective from such a view. But this is hardly warranted. Only the person who denies that they are making sense when they speak, or acting as the agent of their own thoughts, can utter that kind of nonsense and actually take themselves seriously. Yet, this is done frequently and is even the default position among many advocates of scientific naturalism.

Scientific reasoning can never prove the truth or falsity of its own assumptions (which are values), nor can it have much to say at all about normative questions, only indirectly. A scientific argument can be used to support a premise used in a philosophical argument about some conclusion, but it cannot constitute the argument.

Finally, I think the best science is rooted in the best values. Social Darwinists, eugenicists and abortionists, materialist psychiatrists and physicians are not doing the best science. Not because they are fraudulently engaged in the process of searching for causal explanations, and explanatory frameworks that make sense of diverse sets of local phenomena. Those theories represent bad science because of the assumptions that underlie them, the ontology they assume, and the ends of which they are in service.

Far from there being a divorce between scientific truth, and moral and aesthetic truth (goodness and beauty), an explanatory scientific theory that describes the nature of reality must be consistent with truth as it pertains to all three aspects of being.

Peter Copeland is a public policy advisor and Cardus NextGen fellow.

Peter is one of our contributors. For interview requests, click here.

This commentary was submitted by Convivium, Cardus‘s online magazine. Cardus is a leading think tank and registered charity. Convivium is a Troy Media Editorial Content Provider Partner.

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