Research Portfolio Post 3: Philosophical Wagers

In high school, I studied the theory of knowledge. The main point of this class was to answer the question – “how do we know what we know?” Throughout, we learned that the ways of knowing can be divided into two main categories. One is ontological, like sense perception, emotion, faith and intuition. Ontology determines how researchers look at and perceive the world – a framework for how researchers ascertain the events and the patterns that they are researching. As Andrew Abbott posits, “social science aims to explain social life.[1]” Researchers can use ontological frames to analyse the things they perceive to be true and to make sense of the things they believe to be fact. This relates directly to the sine qua nonof interpretive research Schwartz-Shea and Yanow present in their work: “(interpretive research) seeks knowledge about how human beings, scholars included, make individual and collective sense of their particular worlds.[2]” Another category is methodological ways, like reason, memory and language. Methodology determines how researchers can carry out their research, mainly the methods they can use to conduct data collection. It allows researchers to make more systematised conclusions about the world around them through means like surveys or structured interviews.

Since there are so many ways of knowing, it is not difficult to conduct research and to make knowledge claims about the same. However, this brings us to a new question – what really can be stratifiedas knowledge? There is no real obvious answer about what knowledge is. It can be argued that we know these things through the observation of people, things and events happening in our environment, but it can also be argued that the knowledge we have is a product of the programming and opinions passed down intergenerationally. I am of the view that the knowledge we hold is the product of a combination of factors. It is undoubtedly the ideas and things we can see materially but also the beliefs, opinions and feelings we can experience in a more abstract way. There is no all-encompassing definition of knowledge because it is itself an extremely broad concept and is heavily subjective, depending on a person’s interpretation of the world around them.

On that note, as a researcher, I do not believe that anyone can ever truly be an objective observer of the world they live in. Even the most rational of people are often affected by their biases or preconceived notions. Therefore, while we can try as much as possible to be aware of these prejudices, it is also important to note that we can never truly suspend them. Due to this, I believe that we are always contributing to the world of knowledge that we prescribe to. We tend to create work that is similar to that of people who share our worldview. This does often lead to the creation of biased work, but this is not necessarily a negative thing – it aids in providing more holistic views of the things we study and research, which deepens our understanding of the same.

[1] Abbott, Andrew Delano. Methods of Discovery: Heuristics For The Social Sciences. New York: W.W. Norton, 2004.

[2] Schwartz-Shea, Peregrine, and Dvora Yanow. Interpretive Research Design: Concepts And Processes. New York, N.Y.: Routledge, 2012.

 

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3 Comments

  1. I agree with your belief that the “knowledge we hold is the product of a combination of factors,” therefore there is no cookie-cutter definition for it. You provide a clear explanation of something that can often be hard to discuss (I think it’s really cool that you took a class on this topic in high school!). When looking at the question I viewed “knowledge” more like something that meets certain criteria (like internal validity or credibility), so I appreciate that you describe it as something more personal/ambiguous. You make a great point about how biased work isn’t necessarily a negative thing, and I’d be interested in learning more about that, especially because I do think that is an important concept in scholarship. There is a fine line between “holistic” or useful bias and work that is blatantly wrong/uncredible, but there might be instances where that line is blurred, especially due to sociohistorical contexts or societal norms of the time of that research. An example that comes to mind is of scientific studies that made outrageous (often racist) claims about the biology/physicality of race, yet they were widely accepted and supported for hundreds of years until new studies came along. Today, these works are considered good examples of how bias negatively impacts research, but they also support your point by shedding light on the values, personal experiences, and other factors that produced the knowledge of that time. An interpretivist and a neopositivist would approach these studies in very different ways by either focusing on contextualization or generalization (although we have discussed in class that neopositivists still look at the context, just for finding a broader pattern). A great next step would be looking at how one’s school of thought affects the acknowledgment of or response to bias in his or her own work and the work of others.

  2. I am really interested in how you discussed the theory of knowledge, particularly since I have spent the past couple weeks grappling with understanding the concept of, “how do we know what we know”. I have come to understand that everyone has a different view on what reality is (such as an interpretivist’s ontological view where reality is changing and impacted by human behavior vs. a positivist perspective where the natural world is shaped by the laws of nature). However, I have been struggling with understanding how each individual’s world view is shaped. I seem to agree with you that our knowledge and “realities” are shaped by environment and intergenerational programming and opinions. Thus, with each individual coming from different experiences, there can never be one objective lens that one can use when conducted research. What particularly struck me, however, was how you mentioned that our biases aren’t necessarily a bad thing. This idea made me realize that our research isn’t supposed to prove what is “true”, but rather be a voice in the conversation. For instance, as Abbott explained when discussing puzzles, our research isn’t supposed to serve as “weapons” against others ideas, but rather, “mutual challenges” to others ideas. I agree with you that a holistic conversation is crucial. Thus, as we discussed in class, we shouldn’t be critical toward the ideas in a piece of research or the choice of methodology the researcher chooses to use based on the researchers ontological view. Instead, we should be critical towards how the researcher uses the methodology and the conventions they follow to see whether the researcher has objectively analyzed and interpreted their puzzle based off of their specific ontological view of the world.

  3. Paroma — you have given us a very good discussion of your connection to core concepts like ontology as well as some thought-provoking ideas concerning our own positionally in the creation, reception, and (re-)transmission of knowledge. You’ve also received some very good questions and comments from Rhea and Caroline, so be sure to keep thinking about those concepts as you continue to reflect on your own philosophical wagers.

    I like your “big-picture” thoughts on the idea of knowledge as being both very individual and also a combination of a range of other factors and influences. I would ask you to think a bit more about the idea of “bias” that comes up in your post (and in many others). We often toss that term around quite casually. Although it is not unimportant, I think that the term “assumptions” might be a bit more accurate here. Particularly in a research context “bias” suggests some sort of deliberate slant, whereas our ontological and epistemological assumptions are more subconscious and involuntary. Moreover, even if we do recognize that researchers can be biased (consciously or unconsciously), don’t we have sets of procedures — transparent, systematic methodologies — to counter such biases?

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