Like with many groups, scientists have a lot of technical terms (read: jargon) that we often use to either mean something incredibly specific or misuse to shortcut a lot of verbose language that’s often unnecessary.
The first option is somewhat obvious: when a lamp’s specification says it outputs 1000 lumens, it’s referring to its brightness output within a very special metric. This is an agreed upon measurement that’s much easier to imagine than discussing how the light is equivalent to 1000 candles all burning at the exact same location.
The second option is a little more implicit. If I tell you “gravity exists,” I don’t actually know that for a full, 100% fact. The only certain facts exist within mathematics where logically derived statements follow axioms and certain rules of derivations. However, I would be a total asshole if I said gravitational force wasn’t a fact. Where’s the disconnect?
Shortcutting language
The difference is when I talk about gravity, what I’m actually saying (to fellow scientists) is “gravity exists (as we believe with overwhelming confidence as is based on numerous scientific experiments and expert consensus until we are provided with a more credible hypothesis),” but clearly I’m not going to say that in real life, especially I’m not going to say that every time I say something to be true. In fact, we do this a LOT in science and every day life
- it works (as far as I’ve tested it)
- You’re wrong (I can disprove you, I know someone who can disprove you, OR based on a hunch)
- etc. There are certain times where it does make sense to fully quantify our language when talking with other scientists; it’s a bit of an art to identify when assumed language will behave weirdly and other times where you definitely should (like when asked a job question and you need to say “I don’t know [BUT …]”). I don’t think we should all going around fully quantifying language all the time.
However, especially in recent times based on scientific charlatans and incredibly misleading pop-sci articles, I think whenever we’re talking to non-scientists we should heavily quantify what we’re saying. People outside the scientific world will hear a scientist say something, not know/understand the full quantified statement the speaker thought they were making, and then (understandably) misinterpret it. For example, surely you’ve read pop-sci articles with statements like “science proves …” or “new study shows …” followed by the most fringe, non-consensus statements thereafter. As an important shortcutting of terms, there’s really no such noun of ‘science’, what we are referring to are things that are ‘scientific’ (notice the adjective) or follow the scientific method. This is obvious, and often meaningless to scientists, but it does allow non-scientists to state a claim and say (incorrectly) it “is science.”
Even though I’m not in immunology, I, as a technically trained person, could likely look at a very good and a very bad immunology study and tell you which one is the good one and which is the bad one. This is because I could see if their methods are sound, look at what the data is actually saying instead of what it might be implying, compare them to other papers in the field, see if their sample size is large enough, etc.
However, when a non-technically trained person (or someone without infinite hypothetical time) reads a headline that says “new study proves our new drug will make you lose weight,” in a headline, they will probably reasonably believe that it does so; that’s what it says! What they’re probably missing is that the study might actually have said “our drug showed an average weight loss of -0.1 lbs in our study participants ().” Any scientifically trained person would tell you not to even consider the drug until numerous other tests are done and much more statistical significance is reached + a bigger effect is measured; also what are the side effects?
This has always been a problem with pseudoscientists trying to sell false ideas to promote a shadow ideology by using scientific terms and appearing to be credible. I think that it’s become worse though with the advent of hyper-popular scientific journalism and, worse, scientifically trained charlatans that intentionally misuse scientific terms to sell their own ideas. This is especially apparent in the fitness space where lots of people (whom I won’t name to not implicate myself legally) use superlative statements and claim “science proves”-sorts of statements all over their work to sell their false ideas. Compare these people to others who really do a good job of scientifically sharing their ideas to the public like Mike Israetel, Zack Telander, and Jeff Nippard. These people use a variety of scientific sources and heavily quantify their statements so it’s incredibly obvious where the limitations of their claims end.
Takeaway
As scientists, and especially scientific journalists, I understand that we want to sell our work, but we also have to understand that the shortcuts we use in language amongst ourselves is not universal. Be aware of the technical shortcuts you take and understand when it might be a good idea to fully quantify a statement. Do this for the benefit of the public being able to more easily identify when they are being fooled.