So obviously there are sets of questions that science is not very well equipped to handle. Does that make these questions useless and invalid?
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What does peer review mean? Does it mean a paper is correct? No. Does it mean a paper is the final word? No. Does it mean that the scientific community has accepted the results? No. It means that one or a couple random reviewers thought the paper was interesting, new, and not obviously wrong.
Theories are the structures that science builds. The artifacts. The things that last. The starting points for even more.
If you apply your skepticism to some statements (or categories of statements) but not others, why are you even bothering?
Quite honestly, the current brand of science is...all over the place.
So what does it mean for a scientist or science communicator to have a mission when it comes to the public?
What do you do when a skeptic or fanatic tosses out a dozen arguments at once? Focus on just one.
Bad science headlines usually involve some use of obviously over-the-top exaggerations, easily-refuted statements, and bold exclamations. Sometimes it’s even all three wrapped up in one.
Is it better to tear down junk science, or leave it be?
What hidden dangers lurk behind even the simplest assumptions?
Here's a warning, from me to you: don't look to science for cheap validation, ever, because it will end up breaking your heart.
Here's my advice, as a scientist and science communicator, on how to handle a flat-Earther: don't.
It looks us almost a hundred years to finally convince ourselves that atoms existed. Be patient.
Peer review is an absolutely essential tool to the scientific machine, but it's also a human enterprise. It has flaws.
There’s a certain liberation in being able to constantly update your beliefs based on the evidence.
So where do sensationalistic science headlines start? They start with the scientists themselves.
When we ask people to "trust" a particular scientist or result, we need to make sure that it's not the person itself that is necessarily deserving of trust, but the method and structures that they represent.
Is the presentation of the data hiding something? Was anything excluded or minimized? Was anything glossed over? Was one part of the graph highlighted or emphasized to draw attention away from something else?
Take the case of the interior of a black hole (a question I get a lot). We'll never see inside a black hole, and if you were to visit one you would a) die horribly, and b) never be able to communicate your gruesome results to the outside world. So how do we know what's inside?
The most interesting stories are when theory connects to observations, when there's a strong attempt to refute or bolster some piece of (un)known science. And here the name of the game is error bars.