Reductionism

For much of the 20th century, the dominant approach in science has been reductionism – "the idea that it is possible, at least in principle, to explain a phenomenon in terms of less complicated constituents".

"The basic question of reduction is whether the properties, concepts, explanations, or methods from one scientific domain (typically at higher levels of organization) can be deduced from or explained by the properties, concepts, explanations, or methods from another domain of science (typically one about lower levels of organization)." —Ingo Brigandt & Alan Love: Reductionism in biology; Stanford Encyclopedia of Philosophy

This principle has ancient roots - Francis Bacon (1561-1626) quotes Aristotle as declaring "That the nature of everything is best seen in his smallest portions." In many fields, reductionist explanations are impractical, and in such fields all explanations involve 'high level' concepts. Nevertheless, the reductionist belief has been that the role of science is to progressively explain high level concepts by concepts at a more and more basic level.

In the realm of biology, Ayala has suggested three kinds of reductionism:

1. Ontological: An organism is composed exhaustively of nonliving atoms and life processes do not involve non-material entities

2. Methodological: The study of organisms should begin at the lowest levels of complexity

3, Epistemological: Biology is built upon the laws and theories of the physical sciences.

As pointed out by Yates, each of these assertions can be seen as a question by inverting the verb-subject order. He rephrases the second assertion, in particular, as:

"Does discovery of the properties of the smaller elements and reference to them give greater scientific understanding than reference to the larger?"

Yates says the answer to this question is unclear. There are at least two aspects to this. One is that the reduction of (say) chemistry to a quantum field-theoretic explanation conveys no useful information, and obscures the important features of chemical bonding made more understandable at a more macroscopic level of explanation. In fact, such an explanation is so complex as to exceed our capacity. A related issue is whether a complex system can always be usefully divided into an assembly of subsystems. Such analysis abstracts away some of the actual system, making it in effect invisible, and can lead to unpredictable behavior, such as 'emergence' and unanticipated macroscopic 'order parameters'.

Reductionism in physics

Perhaps the prototypical example of reductionism is the historical progress of physics. It is a history of ever more fine-grained explanations. In the 19th and 20th centuries concepts have evolved from the atom as the indivisible building block of nature; to the neutron, electron, and proton; and on to the leptons and quarks of the Standard model; and possibly still further to string theory, although that step is controversial today. At each stage the indivisible fundamental particles were found to have structure that could be explained only with new and tinier particles with different interactions between them. There is a belief that eventually all theories will be combined in the grand 'theory of everything', replacing the Standard model and the general theory of relativity.

Reductionism in biology

Brigandt and Alan break reductionism in biology into three parts, ontological, epistemological and methodological. Ontological reductionism is the view that a biological system (for example, the human brain) is nothing more than molecules and their interactions. Although not taking things down to a molecular level, a great many biologists support a form of ontological reductionism:

"...consciousness is a biological process that will eventually be explained in terms of molecular signaling pathways used by interacting populations of nerve cells.." —Eric R. Kandel: In Search of Memory: The Emergence of a New Science of Mind

Although not stated, the idea that a 'nerve cell' also can be explained at a molecular level lurks in the background.

As an example, to explain the behavior of individuals we might refer to motivational states such as hunger. These reflect features of brain activity that are still poorly understood, but we can investigate, for example, the 'hunger centers' of the brain that house these drives. These centers involve many neural networks – interconnected nerve cells, and each network we can be probed in detail. These networks in turn are composed of specialized neurons that can be analyzed individually. These nerve cells have properties that are the product of a genetic program that is activated in development – and so are reducible to molecular biology. However, while behavior is thus in principle reducible to basic elements, explaining the behavior of an individual in terms of the most basic elements has little predictive value, because the uncertainties in our understanding are too great.

Others find such reduction of all mental states improbable.

Reductionism in philosophy

In philosophy the question of reductionism is connected to the two large fields of ontology (what exists) and epistemology (how do we find out about what exists?). In both cases there are pluralistic (manifold approaches) and monistic (there is only one approach) schools of thought.

Measurement

The reductionist approach assigned particular importance to measurement of quantities; quantification of observations makes them accurately and objectively verifiable, and quantitative predictions are more readily testable than purely qualitative predictions. For some things there is a natural scale by which they can be measured, but for many, measurement scales are human constructs. For example the IQ scale used to purportedly measure intelligence in fact measures how well an individual performs on certain standardised tests, and how such performance relates to cognitive ability is open to debate. Nevertheless, such measurements are objectively repeatable. Measurements may be tabulated, graphed, or mapped, and statistical analysed; often these representations of the data use tools and conventions that are at a given time, accepted and understood by scientists within a given field. Measurements may need specialized instruments such as thermometers, microscopes, or voltmeters, whose properties and limitations are familiar within the field, and scientific progress is often intimately tied to their development. Measurements also provide operational definitions: a scientific quantity is defined precisely by how it is measured, in terms that enable other scientists to reproduce the measurements. Scientific quantities are often characterized by units of measure which can be described in terms of conventional physical units. Ultimately, this may involve internationally agreed ‘standards’; for example, one second is defined as exactly 9,192,631,770 oscillations or cycles of the cesium atom's resonant frequency [2]. The scientific definition of a term sometimes differs substantially from their natural language use; mass and weight overlap in meaning in common use, but have different meanings in physics. All measurements are accompanied by the possibility of error, so their uncertainty is often estimated by repeating measurements, and seeing by how much these differ. Counts of things, such as the number of people in a nation at a given time, may also have an uncertainty: counts may represent only a sample, with an uncertainty that depends upon the sampling method and the size of the sample.