Explanation

In ordinary usage, as well as in philosophy, an explanation tells us not only what happens but also why. This idea is embodied in the distinction between description and explanation. In the literature on research methods, explanation has generally been understood as causal explanation and its pursuit has been limited to quantitative (or even, more narrowly, experimental) methods. Qualitative researchers, in reaction, have generally denied that they were seeking causal explanations, arguing that their goal was the interpretive understanding of meanings rather than the [Page 323]identification of causes; some (e.g., Egon Guba and Yvonna Lincoln) have rejected the entire concept of causality as outdated and inappropriate for the social sciences.

However, this argument has usually failed to take account of recent philosophical developments in our understanding of explanation and causality. The traditional view of causal explanation, and the basis for its restriction to quantitative methods, derives from David Hume's analysis of causality, generally known as the “regularity theory.” Hume argued that we cannot directly perceive causal relationships and, thus, that we can have no knowledge of causality beyond the observed regularities in associations of events. This view treats the actual process of causality as unobservable—a “black box”—and focuses on discovering whether there is a systematic relationship between inputs and outputs.

This view has more recently been challenged by an alternative approach to causal explanation, one that sees causality as fundamentally referring to the actual mechanisms and processes that are involved in particular events and situations. These mechanisms and processes can include mental phenomena as well as physical phenomena and can be identified in unique events as well as through regularities. In philosophy, advocates of this view include Wesley Salmon and Hilary Putnam. In the social sciences, this approach is associated (although not exclusively) with the position known as “critical realism.”

This position's emphasis on understanding processes, rather than on simply showing an association between variables, provides an alternative approach to causal explanation that is particularly suited to qualitative research. It incorporates qualitative researchers' emphasis on meaning for actors and on unique contextual circumstances, and by treating causal processes as real events, it implies that these may be observed directly rather than only inferred. Thus, it removes the restriction that causal inference requires the comparison of situations in which the presumed cause is present or absent. It is strikingly congruent with Herbert Blumer's approach to qualitative research, known as symbolic interactionism, as well as with the work of more recent qualitative researchers such as Matthew Miles and Michael Huberman. With its grounding in a realist ontology, however, it is in conflict with “strong” versions of social constructivism that deny the existence of any “reality” outside of our constructions.

A great deal of qualitative research implicitly incorporates such an understanding of explanation as an understanding of causal processes, a view that is very congruent with commonsense views of explanation. The challenge for these qualitative researchers is to make this view of explanation more explicit, to use it to defend the legitimacy of explanation as a goal of qualitative research, and to further develop qualitative procedures for systematically generating and testing causal explanations.

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