Causation (sociology)

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Causation refers to the existence of "cause and effect" relationships between multiple variables.[1] Causation presumes that variables, which act in a predictable manner, can produce change in related variables and that this relationship can be deduced through direct and repeated observation.[2] Theories of causation underpin social research as it aims to deduce causal relationships between structural phenomena and individuals and explain these relationships through the application and development of theory.[3] Due to divergence amongst theoretical and methodological approaches, different theories, namely functionalism, all maintain varying conceptions on the nature of causality and causal relationships. Similarly, a multiplicity of causes have led to the distinction between necessary and sufficient causes.

- A and B represent some form of phenomena (either concrete or abstract),

- A is statistically related to B in so far as an observed change in A will produce a proportional change in B,

- If the change to A precedes the change to B and the change is not caused by an intervening variable (spurious relationship) then:

- A is said to have a causal relationship (either sufficient or necessary) to B.[4]

This nature, extent, and scope of this relationship, however, must be further defined through further research that accounts for the weaknesses and limitations of preceding works.[3]

Causation and social research

Classical conceptions of causation have demonstrably informed the development of social research and different methodological approaches, as the vast majority of research seeks to explain phenomena in terms of cause and effect.[3] Typical criteria for inferring a causal relationship includes: i) a statistical association between the two variables ii) the direction of influence (that changes in the causal factor induce change in the dependent variable) and; iii) a requirement that the relationship between variables is non-spurious.[3] The identification of intervening variables and further replications of studies can also strengthen claims of causal inference.[3] Different methodological approaches make tradeoffs between statistical rigor (the ability to confidently attribute change to one variable or cause), qualitative depth, and finances available for research. Experimental methods, which maximize statistical rigor, are often difficult to conduct as they are expensive and can be detached from the social processes that researchers seek to undertake. In contrast, ethnographical methods and surveys, which maximize the qualitative richness of the data, lack the statistical generalizability that experimental studies produce. As such, causality deduced from social research can be relatively abstract (findings from an ethnography) or exact (statistical research, laboratory studies). As such, care must always be taken when attributing or describing causal relationships from the findings of social research, as this will vary based on methodology and, consequently, the nature of the data.[3]

Sufficient and necessary causes

A functionalist theory of causation

References

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