by “I have had my results for a long time: but I do not yet know how I am to arrive at them” ~Karl Gauss
Karl Gauss’s quote allows one to ponder on how facts and statistics may hold more than one perspective. I personally agree with his position that the results do not tell the whole story of scientific research; rather, evidence can be used to push an agenda. Moreover, it is important to note the drastic outcomes that can occur from interpreting a singular set of data without further clarifying other key parts (Simpson’s Paradox). Using my personal experiences in research as well as looking into various case studies, there is overwhelming evidence that supports Gauss’s quote of the importance of distinguishing between the significance of the results versus the utility of the results.
Working in multiple biology labs, I run into this problem many times. In the summer of 2019, I was a researcher at Mote Marine Laboratory doing an independent study on Elasmobranch health profiles. When I finished collecting all of my data, I had discovered the new health parameters (SOD, Lysozyme activity, Protein Electrophoresis) of three marine species. However, the challenge I found was interpreting my results. While these health parameters were very important to the field of marine biology as a whole, the way I intended for readers to interpret the results was a different story.
I had to make sure the readers understood why there exists such a wide variation of health parameters within each sample and how you could only understand the health of a certain Elasmobranch given the data on ALL health parameters, not just a single parameter. For example, a bonnethead shark with abnormal SOD does not always mean it is sick (given normal protein and lysozyme levels). Rather, the sample with abnormal SOD may be extremely stressed due to being moved into a new environment. I found that one the challenge in research comes when trying to figure out how to present your final results, rather than how you arrive at them in the beginning. Unfortunately, when research becomes used to promote corporate wealth, the genuine love of science diminishes, and a commercial bias becomes apparent in certain studies.
On a societal level, there have been a multitude of cases where the results of a given study have been technically ‘correct’ but have a skewed interpretation of them. For example, let’s say a study found that binge drinking at Colby increased from 10% to 20% in the past year. Now, is this increase a 10% increase or 100% increase in binge drinking? If you’re at 10%, then you could add another 10% in order to get to 20% (obviously). However, let’s say you make $10/ hour and you get a 100% raise– you’ll technically be at $20/ hour (same idea as a 100% increase). Which value do you think paints a better picture of the current situation at Colby? I think many people would have a variety of opinions on this hypothetical scenario, but what if I told you this was very similar to a certain study of a birth control pill in the United Kingdom? In 1995, the Committee on Safety of Medicine issued a warning that a new birth control pill would increase the risk of life-threatening blood clots by 100%. Around 1 in 8000 women would develop a blood clot with the older pill whereas 2 in 8000 would develop a blood clot with the new pill–very insignificant results when you compare the increase of rates instead of quantity. This led to hundreds of thousands of women who stopped taking the birth control and the study was responsible for over 10,000 unwanted pregnancies that year.
In the age of our technological revolution, scientific research is constantly being integrated into society. I could even say that data and statistics are a large part of my decision making every single day. However, when research leans towards driving action rather than pursuing the truth, it truly manipulates society within certain classes, genders, race, and other categories. It is important for scientists to understand that they are the experts in their own field. Ultimately, it is their job to reveal the truth of the results rather than introducing bias and skewing the perspective of research to their liking.
Sources:
https://www.tandfonline.com/doi/abs/10.1080/01443619867335?journalCode=ijog20#:~:text=In%20October%201995%2C%20the%20Committee,Safety%20of%20Medicines%2C%201995).
https://www.britannica.com/story/how-do-birth-control-pills-work
https://en.wikipedia.org/wiki/Bonnethead