WHAT I SAID WAS "Scientific knowledge is socially constructed" BUT SOME PEOPLE HEARD "Scientific truth is a social construct". For me, there is a difference!
When you tweet things out to 45k people, you learn a lot about the difference between what you think you said and what people hear.
I now understand that some percentage of people are hearing me say "Scientific truth is a social construct" whenever I say "Scientific knowledge is socially constructed". I think both are true but that's not the whole story. Let me explain.
Let's talk about language for minute. I'm sure you will agree that the words we use for things are somewhat arbitrary. However, the things in the world that we use language to describe aren't arbitrary. The word "rose" is a social construct but the rose itself is not.
Languages imperfectly depict reality. They disagree with each other on how to carve up the world. Distinctions in one language often don't match up with distinctions in other languages. These mismatches can help us learn something about objective reality.
Here's what I think. I think it's possible to socially construct something which technically speaking is a social construct (like words in a particular language) but which approximates a non-social construct (like physical reality).
The level of correspondence between the social construct and reality is an objective property of the construct. For instance, "unicorn" and "horse" are both words and both socially constructed but one of these words matches up better with reality than the other.
When we create a social construct with a goal in mind like helping us manipulate the physical world, I think that goal IS constraining on our construct. I would expect some convergence in the form of the construct as it comes to better describe objective reality.
In the language analogy, the process of "socially constructing" scientific knowledge is like translating sentences back and forth between multiple languages as a way of telling us something about the biases each language contains and about reality itself.
When we participate in science as individuals, we create mental constructs. When we participate in science as a group, we exchange our mental constructs with each other and test them out.
This process empirically tests whether our mental constructs, our personal knowledge that appears to us to correspond to reality, is indeed mind-independent knowledge. Only after we have verified that a useful mental construct is mind-independent, can we safely call it "science".
To summarize. I believe that:
1. Scientific knowledge is socially constructed
2. Scientific knowledge is a social construct
3. Scientific truth is NOT a social construct
Let me translate this into the language analogy.
1. English is socially constructed
2. The precise wording of any collaboratively written sentence is a social construct
3. The correspondence of that sentence with reality is not a social construct.
Addendum: There is a lot more to say about how one would establish the degree of correspondence between a social construct and reality or how one would come up with good candidate mental constructs to begin with but that's another longer essay.
Forgive me for not addressing every aspect of the scientific method in this tweet thread. I'm only focusing on the "social construction" aspect for now because I find it interesting! Also please don't take this essay as me saying I know all the answers because I don't.
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If you think about how statistics works it’s extremely obvious why a model built on purely statistical patterns would “hallucinate”. Explanation in next tweet.
Very simply, statistics is about taking two points you know exist and drawing a line between them, basically completing patterns.
Sometimes that middle point is something that exists in the physical world, sometimes it’s something that could potentially exist, but doesn’t.
Imagine an algorithm that could predict what a couple’s kids might look like. How’s the algorithm supposed to know if one of those kids it predicted actually exists or not?
The child’s existence has no logical relationship to the genomics data the algorithm has available.
These grants aren't charity. They're highly competitive contracts where the US government determines Harvard is the best institution for conducting specific research, and then pays Harvard for services rendered to US taxpayers.
Each grant represents a fair contract that a group at Harvard won after being in competition with hundreds or even thousands of other groups. These are not handouts.
The US government pays Harvard and other universities to provide answers to questions that aren't directly profitable in themselves, but which provide a foundation for private sector innovation, and help maintain American dominance over geopolitical rivals like China.
As a someone who translates ideas into math for a living, I noticed something weird about the tariff formula that I haven't seen anybody else talk about. 🧵
The formula defines the tariff rate as exactly the percent you need to charge on imports to make up for the trade deficit. Basically,
trade deficit = tariff rate x imports
It's constructed as if tariffs are a kind of compensation for trade deficits but this raises a question.
If tariffs are something foreign countries owe to the American people for having a trade deficit, then forcing US businesses to make up for the difference, by paying extra money to the US government, is kind of a weird solution.
Whenever I see students with good grades but lots of college rejections, my first thought is a bad personal essay. As predicted, this guy's essay was kind of a disaster.
Since I did get into Harvard, I'll give my two cents on the essay:
In honor of international women's day, let's take a moment to remember the most famous statistician in history.
You've definitely heard of her, but you probably have no idea she was a statistician.
It's Florence Nightingale.
Nightingale was first female member of the Royal Statistical Society and a pioneer in using statistical analysis to guide medical decisions and public health policy.
Florence Nightingale's most famous statistical analysis was her investigation into the mortality rates of soldiers during the Crimean War. She demonstrated that the majority of deaths among soldiers were due to preventable diseases rather than battlefield injuries!
Took one for the team and made a histogram of the Elon social security data. Not sure why his data scientists are just giving him raw tables like that.
It’s also weird that they keep tweeting out these extremely strong claims without taking a few days to do some basic follow up work.
It doesn’t come off like they even:
- plotted the data
- talked to any of the data collectors
- considered any alternative explanations