What does it mean to be a scientist?
Further, what does it mean to have a “scientific” mindset, without being an actual scientist?
In our pop culture view, we recognize the meme of “scientist” to hold a PhD in an area such as chemistry, biology, neurology, physics, astronomy or another natural science. He or she is often wearing a lab coat and looking into a device of some kind to magnify what cannot be seen to the naked eye.
Broadly, we accept that scientists share talents with mathematicians and theoreticians, where often it requires the deep understanding of one in order to advance another. And while science, at times, considers philosophy, philosophers are not considered to be scientists. Scientists can work to inform laws, yet are not lawmakers, themselves.
So what exactly is a scientist, outside the markers of holding a PhD in a science field or working in a lab?
In Part I of the Scientific Mindset series, I will begin looking at what makes a scientific mindset, to determine what makes a scientist.
In Part II, we will consider how our definition of “scientist” informs our understanding of having a “scientific mindset” as well as how this impacts daily life.
What is a Scientist?
From Wikipedia, we gather this, ” A scientist, in a broad sense, is one engaging in a systematic activity to acquire knowledge. In a more restricted sense, a scientist may refer to an individual who uses the scientific method.”
However, it is difficult to explain how frustratingly simplistic this definition is. The complexities behind the word “systematic” cannot be accurately captured and clarity around the systematic activity and definition of knowledge are needed to clarify the way in which a scientist gathers factual information. Using this definition, a scientist could be someone who routinely logs onto Facebook and reads the latest articles of someone who claims to be an “expert”. This activity is both systematic (if done routinely) and he/she is technically acquiring knowledge (whether factual or fictional). However, this person is not a scientist and we know that instinctively.
In reference to the second example, we teach fifth graders to use the scientific method, yet we would not consider everyone to be a scientist. So, what then, is a scientist?
A more accurate definition can be found on this forum from the user, sentipolis, where he/she writes in response to the question “What constitues a scientific mindset?”
“A person adhering to honest, coherent epistemology and pursuit of truth.“
He/She adds to clarify:
“By coherent, I mean the tendency to be logically consistent.
By honest, I mean the courage to admit the inconsistencies in one’s logic .“
I think that the latter, from sentopolis, is a great place to begin on understanding our definition of scientist and the mindset implied.
What is the “Truth”, Scientifically Speaking?
In life, “truth”, of course, means factual reality. However, many people use the word “truth” to mean things that they feel in a strong emotional sense, in essence, what is felt to be true such a belief or opinion that helps to prop up a specific world view. But, scientists know that no matter how strong the emotion around a belief or opinion, the labels do not change. It remains a belief or opinion. A “fact” has a different set of criteria. Here is short explanation of the differences between fact, belief, opinion and prejudice.
“Truth”, in my opinion, is far too ambiguous a word for science, unless once uses it interchangeably with fact or theory. In science, there are many categories to consider findings and they are all very specific to the level of how the statement can be proven to help . Follow this link for more concrete definitions and clarity around the differences between the labels “fact”, “hypothesis”, “theory”, “inference” (deductive and inductive) and “evidence”. Even if you have a basic understanding of how people use these terms in every day life, scientists have much more specific requirements for their use so it is a good idea to become re-familiar with those individual nuances in language. Communicating ideas and knowledge appropriately leads to greater comprehension and hopefully, a greater clarity in communicating it to another in the future.
The pursuit of “truth”, as I interpret it from the quotation above, requires that the outcome is both valid and reliable, two foundational components of experimental design and the scientific method.
Many of the claims I find on the Internet that are debunked by actual chemists and biologists either (1) do not pass the two tests of reliability and validity or (2) use logical fallacies to extrapolate a false meaning or application (which I will discuss in a moment). And to my sadness, many of these claims are quickly accepted as “scientific proof” by the masses without hesitation. Those peddling the claims, and their followers, are not scientists; They are spin doctors. They are not using the scientific method and are showing their ignorance in both the stating of overreaching claims, as well as the immediate acceptance of such claims without further investigation into the actual studies attached themselves, if any exist. What you are witnessing is marketing attempting to leverage the word “science” as a form of authority to convince you to buy a product. It can also be quite dangerous to buy into false claims that “cure” ailments and forgoing known methods for fighting diseases that are valid and reliable, backed by extensive research.
It is important that, in “the pursuit of truth”, one know how to appropriately read a scientific research article. Understand that the complex, formal language is there to provide a description and claims as specific as possible in order to explain the outcome and lend to the study’s ability to be repeated. It is important to understand that scientists try to make scientific concepts as easy-to-understand as possible, but subjects like biology, chemistry and physics study the complexities of the world and are not easily broken down always. So, it is important to learn the nuances of this language in order to communicate scientific findings and trends clearly. Those who attempt to sum it up simply can sometimes over-simplify and leave out important nuances that are crucial to understanding a concept fully. Without knowing how to read an article appropriately, your understanding of a study will be at the whim of a third party, many of which like to post “shocking” headlines that overstate findings in order to receive link clicks, who may also not understand the language, leading to higher instances of misinterpreting the data and stating overreaching claims. These headlines and articles are click-bait; These are not scientific.
An aside about logic, as well, is important in the scientific process. This link to a list of logical fallacies with examples is a great place to begin, not only to understand which logical fallacies you may be most susceptible towards in a debate, but also to acknowledge another fundamental principle of all experimental design interpretation and statistics: correlation does not equal causation. That is to say that just because two lines on a graph run in a parallel, downward trend, does not mean that one line makes the other so. They are simply correlated. In these findings, in this study, they are parallel. The cause of their parallel nature could be a number of things, accounted and unaccounted for, depending upon on the quality of control in the research study. There are many variables within a scientific experiment and much of the experimentation process works to isolate these variables. Once enough variables are accounted for with a control, researchers can work towards isolating those variables to find causation of trends.
I might also add that an important part of any scientific experimentation is statistical significance. When discussing research, many times I’ve come across results where a trend was found but it wasn’t statistically significant enough. Results with a statistically significant findings versus results with a trend emerging that is not statistically significant is an important distinction in the scientific community. To read more on what statistical significance means mathematically and how it is determined, follow this link.
Lastly, I will add that it is the mark of a scientist is self-awareness of his or her own bias, as well as to confront it regularly. In the original quotation above from sentipolis on the definition of a scientist, “the courage to admit the inconsistencies in one’s logic” is a daily task. We are all biased as we are fallible human beings, but the maintaining a balanced approach to science is the responsibility and mark of a scientist. The best that we can do is to be self-aware and to actively work to minimize the effects of our own bias while writing or interpreting scientific findings and research. Are you curious about your conscious and unconscious bias? Take this test to help Harvard researchers and to find out more about your bias in different subjects, including gender, skin color, religion, age and sexuality.
These are very short summaries of some ways that scientists and researchers go about determining accurate findings of an experiment by isolating variables and ensuring correct logic in testing a hypothesis. It is also important to point out that even the most basic of experimental research requires a basic understanding of the body of previous research in the field specific to hypothesis being tested in this experiment as well as logic and statistics. In my opinion, the universe speaks in the language of mathematics, understood and interpreted by the written language of logic, but that is another post for another day.
Did you find this post helpful? Let me know in the comments! Be sure to check back in next week on Science Sunday for the installment of Part II where I will explore how our definition of “scientist” from this week’s post informs our base for understanding the scientific mindset, as well as how this mindset can be applied in daily life.