* The study of knowledge (epistemology): https://en.wikipedia.org/wiki/Epistemology

* The study of existence and what exists (ontology): https://en.wikipedia.org/wiki/Ontology

* The study of the purpose of things (teleology): https://en.wikipedia.org/wiki/Teleology

It turns out that these are hard areas of study and it requires a lot of properly focused leisure time to understand properly. Most people don't consider these things, wing it, and wind up working with a half-baked meta-meta science of their own creation ... oh, I see what you mean :-D

1. There is no such thing as objectivity in inquiry. There is always a scientist interpreting things, and they are always looking at things through the lens of their own biases and cultural norms. The best you can hope to do is to be aware of your limitations.

1. Statistical evidence on its own is not always a good basis for believing something to be true. Typically you also want a good theoretical model, and an understanding of the mechanism that underlies the observed phenomena (physics is good at this, psychology not so much).

3. That there is more knowledge than is detectable through statistical methods (currently at least). And that lack of evidence from statistical studies does not necessarily constitute good evidence that a theory is false.

2. This is studied in statistics classes. It is impossible to analyze data without a statistical model, so of course your conclusions rely on it. So this is also quite trivial.

3. Again, are scientists oblivious to this simple notion? I doubt it.

That’s a question that Richard Feynman supposedly asked his grad students. Once you answer it, I think you’ll realize that #1 is anything but trivial.

Answer below, stop reading this comment if you want to figure it out on your own.

It’s because you’re comparing the mirror image to what you’d look like if you walked around the mirror, instead of to what you’d look like if you floated over the top. This assumption of horizontal travel is incredibly deeply engrained in humans, to the point that the English language doesn’t even have up/down equivalents to the words “left” and “right”, i.e. a word that means the direction closer to your head than to your feet regardless of your orientation.

The realizations that people expect yaw rotation because that's what they are used to, or that normal day language isn't always precise (my left? your left?), seem extremely trivial to me and doesn't require any deep philosophical "insights".

In the hard sciences, you often don't even need the handwavey "swap a and b" explanation when it is much more useful to just model its behavior (ingress ray/plane intersection, normalize ingress ray, subtract twice normal vector of plane from ray to get egress ray direction).

I'm sure Feynman was a great physicist and teacher, but he's also great at just wowing people by using lots of words without saying much. Like in his famous why-is-ice-slippery video where he goes onto a completely unnecessary discourse on the nature of questions instead of just answering the dang question.

I always felt that is the perfect way to showcase the difference between education and edutainment, and I assume his lectures were a bit more substantial.

Also, just for fun: what makes calling it swapped front to back more valid than left to right? One could recover the (translated, rotated) original image through any of a front to back swap, left to right swap, or top to bottom swap. They’re all lenses, and equally valid.

I guess technically correct, because they're mostly latin loan words.

But reading the article, are those not applicable only to body parts? Would an astronaut ever say to another astronaut, while floating in different orientations, “Hit the button to your superior”?

Either way, I think it’s at least correct to say that there are no layman words for it.

My understanding is that a lot of problems in science are incentive based, and that would look very similar to someone just not knowing things from the outside.

>My understanding is that a lot of problems in science are incentive based, and that would look very similar to someone just not knowing things from the outside.

I can agree that a lot of it may be probably incentive based vs 'scientists' just not being smart enough. But is is hard to glean what the proportions are. I still suspect ( based on a general assessment of people both known and on the internet) that it is the latter.

Every scientist should be able to answer the particular tenets that they take on faith.

Scientists do take on faith that the universe is causal and that the rules today are the same as the rules yesterday.

Yes, scientists double check these assumptions over and over, but they can never "prove" them.

This kind of introspection is important for science to set itself apart from religion, for example.

Iterating on existing systems to see if you can get results to converge and also testing new systems to see if they also result in known good values.

All of these ideas that you tacitly take for granted are itself mutable parts of the scientific process:

* That iterative improvement and hill-climbing is an effective process for improving results.

* That replication of experiments and convergence is a truth-generating enterprise.

* That truth can be expressed numerically.

* That there are some values that are "known good". By what process? According to whom?

To be clear, I don't disagree with those. However, these rules aren't baked into the firmament of the universe. They are processes we humans have chosen to apply in our social process of reaching conensus on truth. In other words, this list here isn't physics, it's technology.

It's entirely possible to imagine a culture whose truth finding bodies don't take for granted one or more of these rules at all. That culture might be more or less effective (again, according to what metrics?), but it would still be well-defined.

Not essential to science; in fact, there’d a major viewpoint within metascience that explicitly rejects this as popular mythology of how science works in practice, holding that models change by revolution more than evolution.

> That replication of experiments and convergence is a truth-generating enterprise.

Not part of science, in the same way that your use of “truth” later is not.

> That truth can be expressed numerically

No. While scientism may make essential connections between science and truth, science itself only depends on useful predictive models being expressable, not about truth being expressable, numerically or otherwise, or even being a coherent, meaningful concept.

> That there are some values that are "known good"

That's not only not essential to the scientific process, but contrary to something that is: that all results are contingent.

Isn't this the idea of "free will". That you get to choose for yourself the metrics you want to optimize your life for?

Now I think that you'll use a combination of learned and inherited desires for it. But the idea here is that each individual can express those desires, and then the "success" of a society is thus to maximize each individuals success, even when they differ in their metrics.

That's a made up concept as well, but I think it still stems from individual desires. We've just mostly all individually observed that an organized society that compromises with each other to maximize each and everyone's individual desires has less risk to our own desires being squandered.

The alternative would be to try to achieve power over others to maximize your desires, and maybe from history and life experience, people have found that to be not sustainable or only achievable for a few, thus your chances at it are lower.

In essence, I think I'm saying that it seems over time people know their desires, but don't know how to beat fulfill them, and this is the metric.

I don't think this is what is held by those-who-do-science-and-philosophy-at-large (though it may be a generally accepted hand-wave, I don't know). See, for example Category Theory for a branch of what-I-believe-would-generally-be-called-science that doesn't use numbers, but instead expresses things with sets and relations.

The logician is the intersection of the set of all scientists and the set of all philosophers.

https://plato.stanford.edu/entries/philosophy-mathematics/#M...

* That truth can be expressed numerically.

Isn't the basic point of quantum physics that this isn't true? We can only make guesses with probabilities, but we can't know the actual truth, and therefore can't express it numerically.

Imagine you were studying ice cream flavors. You might design a study like, "We'll ask a lot of people and the flavor that the most people prefer is the best." In other words, the metaprocess you use to design your experiment itself tacitly assumes you need a numeric result. The presumption of comparison and quantifying frames the questions you even think to ask.

But you can imagine an alternate culture that when studying ice cream flavors doesn't even ask questions with numeric answers. It could be, "We'll ask a lot of people to try flavors and write poems about the experience."

We wouldn't even call this "science". Because there is a hidden border around even the term that affects how we are able to evolve the scientific process.

And no, not poems. Elements of finite groups are not numbers, but they crop up in physics frequently. Topologies are not numbers, but they're also significant in physics.

Engineering. If you can build something that works based on the rules theorized by scientists, they are on to something. e.g. building a skyscraper proves we know the properties of steel to a pretty good margin of error.