I see ontology as being about how and what we believe about the nature of being and reality. This is a reasonably hard concept for me to wrap my head around because it is such a metaphysical concept and wants me to question notions that I always just assume as truths because you get into too much a spiral of breaking everything down into its components, and at the end of the day we’re all just a ton of atoms piled on top of each other and should a pile of atoms really question the essence of being and what is identifiable and what is knowable in the world. But, in reality, ontology is just that: a way to say what things are and how those things can be grouped.
Methodology is the process by which we get to a conclusion and the reason why we used that logic. Methodology also varies across disciplines and in daily life. In an academic setting, no matter what discipline, there is an expectation that you will record your procedures and methods and that there was a specific reason for the methodology you choose. This methodology selection is crucial because it allows people to understand how you got to the point that you did, and even if they disagree with the hypothesis or some of the assumptions made, they can understand how that impacted the data and results in certain ways. Methodology is also crucial because it dictates what we view as important versus unimportant, for example, large-n methodology doesn’t care about individual cases it’s looking at the overall patterns that emerge from the cases to tell a story whereas interpretivism cares very much individual cases rather than the overall trends.
I think that as humans, we can never be a true impartial observer of the social world because we enviably apply our own biases and life experiences to everything we see. But we can try to minimize our unobjectively by either accounting for it when we interpret our data, and we must also understand that there are several ways to account for bias. Some of these ways include substantiating your data against other similar data, have peers review your data and work, recognize different types of researcher bias and actively work to make sure they don’t infiltrate your work. But at the end of the day, we are inevitably a co-producer of the reality we inhabit. As Abbott discusses our positions in the social world very much affects our research, for example, if you are too self-confident that you will disregard the work others have done before you and the help your peers are likely to offer (1). I think that anything you can put into words and still have others understand what you’re talking about is something that can be measured. So, this means both visible and invisible phenomena are measurable.
- Andrew Abbott, Methods of Discovery (W.W. Norton & Company, Inc., 2004), 240.