In general, research is in much safer territory when exploring correlation than causation. Moreover, we often admonish or students with a phrase like causation does not necessarily imply causation.

Seldom do I hear or read scholars even mentioning or discussing causation. Correlation is far more common.  I should mention most of these interactions and/or readings are in economics, math, statistics, and occasionally in philosophy and other areas.

Similar discussions and scholarly exchanges have been around for a long time on related issues; just look at the writings of philosophers like David Hume and Karl Popper. The latter suggests we cannot prove causation; instead, we can can go through something of a falsification process to find were it does not exist.  Look at the link for more.

I hope this helps.

Rob

http://www.stephenjaygould.org/ctrl/popper_falsification.html

Thanks Rob,

I find your comment most appropriate for explaining a phenomenon of interest.

There are, however, situations that call for improvement. Obviously, such improvement could only be promoted when the analysts tackle all causation aspects.

It is indeed difficult to prove causation; however, we carry out our everyday lives with a series of decisions and actions that will, hopefully, yield the expected outcome. Usually, the outcome falls short of our expectations. Maybe this everyday lesson should be taken seriously and trigger the development of intellectual tools that could help us reach a full understanding of all situations that we encounter.

Reality will not become simpler because we, humans, cannot understand its complexity.

Indeed in the complex reality it is quite typical to find multiple causes for most consequences. Even clear cut examples like the flu do not escape this problem. The necessary cause is a virus, but other causes or contextual factors play a role such as weakened resistance in the body. 

However, this complexity does not render the search for causes useless. Knowing at least the most important causes of a consequence does allow us to take effective action in most cases. When studying causes in isolation is the most effective way to get to know the causes in the first place this is a fair first step, not?

One approach which is quite realistic when it comes to complexity and causation in the CIMO (Context, Intervention, Mechanism, Outcome) logic. By specifying both context and mechanisms it does a good job in scoping the complexity of real world interventions.

My2Cents

I agree that in research especially in social science multiple factors play role in consequence. The problem lies with the strategy to address the problem using research  approach. Actually research needs to be conducted as a team work in contemporary as well as chronological times. All the causes for a phenomenon can't be studied through a single research project at a point of time. we need to combine results obtained by different people at a time as well as different times. I mean a kind of technical meta analysis needs to be done to reach a consequence.  

Research work gives us a better understanding of all kind of situations, some of them calling for improvement.

My engineering background leads me to, not only to achieve a full understanding of the situation being examined, but also to seek some ways in which such situation could be effectively improved. In this field of knowledge, causality analysis is essential for ensuring effective interventions.

I thank Koen for calling my attention to CIMO. Truly, as Vijay explains, complex phenomena need to be tackled by a team of analysts, if possible, with supplementary perspectives. Which, in itself, poses quite a challenge.

It makes me feel human to realize that some fellow researchers share some of my views. I shall keep looking for strategies and methodologies that could help me characterize and examine these causes-consequences cyles.