Category Archives: Science-general
Trust Me
An illustrated story about critical thinking, inspired by Carl Sagan’s The Demon-Haunted World.
Discredited Theories
Why Einstein will never be wrong
You could say we now know that the caloric model is completely wrong.
Except it isn’t. At least no more wrong than it ever was.
A perhaps subtle but important point. Models are adopted because they work, and it’s a matter of their scope that leads us to later discard them. And, as the article continues on to say, if you want a newer model to be adopted, it had better do more than the model you want to supplant.
Einstein’s theory didn’t supplant Newton’s until we had experimental evidence that agreed with Einstein and didn’t agree with Newton. So unless you have experimental evidence that clearly contradicts general relativity, claims of “disproving Einstein” will fall on deaf ears.
The inability of a thought experiment, rather than a physical experiment, to confirm a model is something I’m fond of pointing out, and something that the psychoceramics never seem to grasp.
The Hard is What Makes it Great
New theories are hard to get right…but that’s OK
Theoretical physics is hard.
Or more to the point: coming up with workable new theories in physics is difficult. Partly that’s because of the vast successes of science: we are remarkably good with our current theories at describing, predicting, and otherwise characterizing a huge number of physical phenomena. Any new theory has to cover known phenomena adequately and do better at characterizing experimental or observational evidence than existing successful models. That’s hard to do, which is why big shifts in the way we do things — relativity, quantum physics, and so forth — are much rarer than smaller advances.
This is a recurring theme among scientists who have some exposure to the public — new “theories” arrive unbidden all the time, and these days anyone with an idea can start up their own website. I think Matthew nailed the characteristics pretty well — pretty pictures but no math, intelligent but little formal training, bold general predictions but nothing specific that could be tested, and the complaint that they are being ignored, or worse, censored.
The devil’s in the details, and these proposals generally lack detail. There’s also an observation about pop-sci books not giving you enough to actually do science, which people may not recognize. This reminds me of something that I’ve seen elsewhere (Physics and Physicists, IIRC): pop sci books don’t teach you science, they teach you about science.
Required Reading
Ask Ethan #17: The Burden of Proof
Perhaps no word in the English language generates as much misunderstanding as the word theory. In scientific circles, this word has a very specific meaning that’s different from everyday use, and — as a theoretical astrophysicist myself — I feel it’s my duty to help explain exactly what we mean when we use it.
An excellent piece on what it means to have a theory vs a law vs an hypothesis.
Twenty Tips for Interpreting Scientific Claims
Policy: Twenty tips for interpreting scientific claims
[W]e suggest that the immediate priority is to improve policy-makers’ understanding of the imperfect nature of science. The essential skills are to be able to intelligently interrogate experts and advisers, and to understand the quality, limitations and biases of evidence. We term these interpretive scientific skills. These skills are more accessible than those required to understand the fundamental science itself, and can form part of the broad skill set of most politicians.
A good list, but not a great list. I think some of the examples are still too esoteric. Also, for politicians, one could use more targeted examples, such as the one for sample size. Put it in terms of polls — do politicians ever wonder why polls generally get about 1100 respondents? Sample size to make the results significant at a reasonable-sized random error of about 3%. They might relate better to that.
The list also can be applied to people in general, and it’s concepts such as the ones here that are really the basis of scientific literacy. Not so much the facts of any one discipline, but in the process all of them share. Knowing these tidbits can weed out a lot if bad science.
Rube-y Goldberg Tuesday, Girls Edition
Yeah it’s an ad but I like the sentiment. However, I can’t help but notice that the packaging and toy components shown at the end is kinda … pink.
Quantum Crosswords
Uncertain Principles: Quantum Crosswords: My TED@NYC Talk
[W]hen we look around us, we see waves in water and particles of rock, and they’re nothing alike. So, what bizarre thought process could make physicists think they’re the same? The answer is surprisingly familiar. We were led to the dual nature of the universe through the same process you follow to solve a crossword puzzle.
I don’t mean dictionaries full of words sorted by length. I’m talking about the puzzle as a whole—those theme clues that run all the way across the grid, and contain a five-word phrase or a dreadful pun. You can’t look those up, and you won’t guess them. Instead, you piece them together a letter at a time from the simpler clues that cross them. If all of those other crossing words fit together in a satisfying way, you can be confident that you’ve also got the right the theme answer.
I think this is an excellent analogy. Like the jigsaw puzzle analogy, it conveys that the bit of science one proposes has to fit in with other science (whether part of a model that’s not being replaced and/or the evidence we have gathered) so if your “word” is the wrong length, it doesn’t matter that it matches that you know that “a” is the third letter. It has to fit in with what we observe to be true. (This, by the way, is where a lot of crackpots fail — they’re so fixated on one specific area of science that they ignore all the other bits with which a new theory must be consistent.)
One could take this a step further and note that you always do the crossword in pencil, because at any time you can get to a part that shows all of the other words around them are wrong, even though they made sense when you first filled them in. But the more the words interlock and are consistent, the more confidence you have that you’re right.
Can’t wait for the book to come out.
We Don't Talk About What We Know, We Talk About What We Don't Know
Stuart Firestein: The pursuit of ignorance
I really liked this talk. The post title is from his discussion of what scientists do at the end of the day at a conference, when they get together for a beer — they ask questions, and discuss the unknown.
Another paraphrase — Knowing a lot of stuff doesn’t make you a scientist. The purpose of knowing stuff is so you can ask questions. IOW, the whole purpose of learning a body of knowledge is to be able to define what isn’t known. Then you can go off and investigate that.
I also liked that even though he’s in a different field, the talk addressed general issues. There was nothing specific to neuroscience or the life sciences; even though he used examples from neuroscience, the concepts applied to physics (and, I imagine, chemistry). That doesn’t always happen
STEMming the Myth
A pretty good summary of the situation, I think, including the point that making more students scientifically literate is not the same as churning out more science majors.
Also, this:
Clearly, powerful forces must be at work to perpetuate the cycle. One is obvious: the bottom line. Companies would rather not pay STEM professionals high salaries with lavish benefits, offer them training on the job, or guarantee them decades of stable employment. So having an oversupply of workers, whether domestically educated or imported, is to their benefit. It gives employers a larger pool from which they can pick the “best and the brightest,” and it helps keep wages in check.