Blog 3- How is it Possible to be Unbiased?

How is it Possible to be Unbiased?

            I found these readings on the digital divide to be very informative to my point of view, specifically because I was naïve enough to believe most of the population in the U.S. had access to the internet. In another class I asked, “How has Social Media (specifically Facebook) been used to create action for or against public policy?” and while I see it is a topic that can be further investigated, the question still remains who would be affecting public policy through these social media channels? Could my research have been skewed if I were not thinking about what types of data to collect? Could it be skewed because I am trying to prevent this bias from occurring? I think it is possible. While I believe it is important to develop research ideas, I now see the dilemma on gathering fair and unbiased data as there are variables that we simply do not think of.

            This leads me to my next thought; what is more important to researchers, collecting data that supports their thesis or collecting unbiased data? (I hope it is to be unbiased, but I won’t assume.) In these readings, I feel as though the scholars did their best to be unbiased in their findings, but did they try to avoid their preferences too well? Researchers are not able to provide equal representation of their thesis when only looking to prevent a bias. For example, Scheeder et all only focused on digital divide determinants instead of including variables that can help bridge the gap between the divide like Obama’s ‘net-neutrality’ rules. This is where validity from other scholars comes into play. Do we as scholars, who might be using this data we have found, believe that these results are valid and true? If we do, then we must look to see if we believe them to be true because we want to further explain our hypotheses, or because it truly is valid. I think that might be the hardest part when looking at validity in another person’s work.

            Furthermore, by trying to avoid favoritisms in our research and constantly thinking about avoiding these original biases, do we accidentally become close-minded from the opposite point of view? Do we end up constructing the data to amplify our “unbiased” results instead of simply collecting it? I worry that purely knowing about a bias does not prevent it from taking on a bigger role in our research.

            To avoid predisposed results on both ends of our questions, I think scholars must take data from two sides of their hypotheses into consideration. From the readings, I found Sasaki to have the best method of analysis, for he was able to look at the “Educated” & “Less Educated” to reach a clear answer at the end of his research. With my original research question at the beginning of my blog, I would have to find data for the higher and lower ends of the digital divide to answer if those groups are able to affect public policy through social media channels. From there, I can use those results to tell me if people, in a general sense, are able to create action via social media to affect public policy. I do not believe that by simply knowing about the digital divide I would be able to accumulate impartial data. Nor do I believe that by trying to avoid the preconceptions of the digital divide, I would be able to have impartial results at the end of my research. It is important to do the research on both ends of a question or your results, in my opinion, are not valid.