For Those Less Math-Inclined Social Science Majors
As a social science major, I’ve always been fascinated by those in STEM fields. All the equations, experiments, diagrams, chemicals and just about everything else feels like another language in my mind and leads me to view those who do understand as a whole other category than myself. I mean, how can I compare studying congress, economic behavior, and the history of WWI to analyzing complicated integrals, chemical structures, or velocity equations? It has always felt like those who understand STEM concepts are undoubtedly smarter than me, and their fields are far more respected due to hard data and facts that result from experiments and equations.
For a long time, I’ve dubbed this feeling as a matter of immature jealousy and an inferiority complex, and have tried my best to ignore it. However, it came as a shock when I found that professionals and hard-core academics in social science fields experience the very same feeling, and so commonly that it has earned its own term: physics envy. Physics envy has become a well-known phenomenon in more humanities-based fields, but in economics especially. It generally refers to the tendency of economists to overuse numbers, equations, graphs and so forth to explain concepts in econ, or in other words “mimic” the science of physics in an attempt to be viewed as more rigorous in academia.
One could argue that there’s value in this mathematical work, as it is always good to back up a theory with data. However, many have argued that this obsession with numbers is actually detrimental to social sciences like economics, as it fails to consider other factors in the field. The bottom line is that social sciences are named as such for a reason – people’s behaviors, relationships, intentions, etc. are important. It has become evident that there are some things numbers just can’t account for.
The consequences of physics envy can be seen throughout the field of economics. As one example, let’s look at the measure of Gross Domestic Product (GDP). GDP is a calculation that measures all economic activity in a nation within a given year and has grown into a number one indicator of a nation’s wealth and wellbeing. But while GDP may gauge how economically powerful a nation is, it falls short on a number of factors. For one, GDP is far from a perfect measure; it fails to account for “black-market” transactions (like babysitting), or activities such as growing your own vegetables. Additionally, this tool has no way of separating “bad” spending from “good” spending. For example, while increased spending on healthcare may indicate a decline in overall health, it is a positive addition to GDP. Other examples include money spent on gas that contributes to pollution, overconsumption of plastic, natural disaster relief, and more. Critics of GDP have noted that the economists who created it focused too much on the numbers of spending, but not enough on consumer behavior and overall societal health (including education, mortality rates, happiness, etc.)
Beyond GDP, this problem spreads into a number of other branches of econ, specifically finance. Here, the problem lies where economists attempt to predict the outcome of certain markets, actions, and so on through mathematical models. Where the problem comes, however, is a failure to account for risk and uncertainty that comes with a field so closely linked to human behavior, which can be highly unpredictable.
So while economists’ physics envy may not be completely comparable to my own math-related inferiority complex, it does provide valuable lessons for myself and other social science majors. While equations and diagrams are useful and can at times aid in explaining certain ideas, there’s nothing wrong with focusing on the human side of things. When it comes down to it, numbers can’t perfectly explain people, and some could argue trying to do so is at times even harder than pure numerical thinking. Social science is difficult, as there are usually no clear-cut answers. It’s challenging enough to just study institutions, behaviors, and trends, even if this may be viewed as less “rigorous” or “exact” than math or science because without these factors, social science is not complete.