A little bit of sociology of science?

I recently published a paper on turbulence in discs around young stars. The basic conclusion was that turbulence tends to inhibit, rather than promote, a potential planet formation process. However, rather than talk about the paper itself, I thought I would briefly highlight some of the background.

The paper was actually a response to an earlier paper, suggesting that turbulence could act to promote, rather than inhibit, this planet formation process. However, the authors of this earlier paper had essentially taken an analysis that is appropriate for star formation in galactic-scale discs and applied it to planet formation in disc around young stars. The problem, though, is that planet forming discs are not directly analogous to galactic-scale discs, even though a lot of the basic phyics is very similar. This is mostly what our paper was highlighting.

What was interesting, though, was that I was at a meeting with one of the authors of the other paper and mentioned their work in my talk. Impressively, they then publicly acknowledged that their analysis may not have been appropriate for planet forming discs, even though it is appropriate for discs in other contexts. One might argue that they should have avoided this in the first place. However, noone had really looked at turbulence in this context, so – ultimately – we’ve hopefully learned something about its role.

The other interesting aspect is that my co-author on this paper has been promoting a planet formation process that myself, and others, have suggested doesn’t really work, or – if it does – rarely operates. However, despite having a scientific dispute about one aspect of this topic, we were quite capable of working together on a related problem. What is partly motivating this, though, is a desire to try and resolve (as best we can) our scientific disputes.

Okay, I’m not all that sure what I’m trying to suggest by this post; maybe just an interesting story that highlights something of how science can work. Maybe I’ll finish by highlighting another interesting science story that I came across on Eli’s blog, but that originates here.

The basic argument is that the validity of some scientific theory (whatever those who support it might say) does not depend on how elegant/beautiful it appears to be. I agree; reality can be complicated. However, my corollary would be that once we have a good understanding of some system, it is often possible to develop elegant descriptions. The problem, which I may expand on in another post, is that these elegant descriptions are often – by their nature – simplifications. This means that sometimes people (especially on blogs) can claim to have falsified some theory because some data doesn’t exactly match what the theory appears to suggest. Essentially, it’s important to appreciate the complexity, even if the basics seem quite simple. I’ll stop there.

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56 Responses to A little bit of sociology of science?

  1. Eli Rabett says:

    Eli’s argument is a really different. That what counts is neither beauty nor simplicity but conciseness. The more that can be encompassed in the most compact way the better the idea.

  2. > Okay, I’m not all that sure what I’m trying to suggest by this post;

    My I suggest you are trying to convey that discussions among scientists and the bizarre US climate “debate” are like day and night? The main similarity is that the English language is used.

  3. Eli,

    Eli’s argument is a really different. That what counts is neither beauty nor simplicity but conciseness. The more that can be encompassed in the most compact way the better the idea.

    Yes, I should have maybe added that. I was trying to keep things reasonably concise 🙂

    Victor,
    Yes, that probably is it.

  4. ATTP – and it isn’t the case that you are claiming that scientists are someone better human beings (not suffering from human frailities like pride, jealousy, anger, etc.). One could mention Eddington’s treatment of the young Chandrasekhar. But ultimately Chandrasekhar won the argument, because ‘the truth will out’, not because of chummy niceness, but because even strong advocates for opposing positions who are scientists, and follow the norms of science – publishing papers, attending conferences, defending papers with peers, etc. – will yield, or yield it sufficient weight to constitute consilience (in the sense Eli discusses in his post).

  5. Richard,

    and it isn’t the case that you are claiming that scientists are someone better human beings (not suffering from human frailities like pride, jealousy, anger, etc.).

    Indeed, this was just one story. There are plenty of others that could be told. Your comment reminds me of a very publi fight between Eddington and Jeans, which I wrote about in this comment.

  6. Chris Ho-Stuart says:

    I noted (in twitter) two things that stuck out to me, which would be be relevant in a climate debate. Relevant in the sense that a bit of experience in how science is done and how it works is going to inform your perspective on some of the claims that show up in climate debates.

    (1) Fraud. There really is no credible scenario for widespread unchallenged fraud dominating an entire field of active science in the way that is frequently asserted with respect to climate science.

    (2) Models. This research is entirely model based. Working scientists will generally have a pretty good idea about the importance of models, how they work, how they are used, what they are able to show and how they may shed light and even resolve scientific disputes. A lot of claims made with respect to climate models reflect no comprehension at all of what models are and how they are used.

  7. Chris,
    Thanks for the comment. As far as (1) goes, yes, I agree completely. As far as (2), yes, this is mostly model based. There are a couple of observational constraints. One thing we point out is that in these discs you would expect strong turbulence to dissipate, heating the disc and – essentially – weakening the turbulence. This is consistent with observations – there isn’t evidence for strong turbulence in protostellar discs.

  8. TTauriStellarBody says:

    Fred Hoyle is someone who had controversial ideas but was widely respected.

    I think in the climate world Richard Lindzen is a man who is controversial but respected. But there is a yawning chasm between the kind of Hoyle\ Lindzen knowledge level and that of much of the skpetics (and some enthusiastic supporters of “climate change”.

  9. TTauri,
    Ray Pierrehumbert has said (about Richard Lindzen)

    He has made a career of being wrong in interesting ways about climate science

  10. Eli Rabett says:

    Eli had a friend who worked in a well respected place. His take was that he had two colleagues who he always asked for help with interesting problems. One ALWAYS gave him the wrong answer for the RIGHT, reason the other the right answer for the WRONG reason. Lindzen appears to fall between those stools.

  11. Chris Ho-Stuart says:

    With regard to models… I am contemplating saying more about this, possibly on my blog, so a bit of help getting this right would be appreciated! In my tweet I was a bit more circumspect, saying your paper was “pretty much entirely model based” rather than “entirely model based”. Was the tweet fair? Could I word it better? Speaking generally, it’s standard (in all fields I can think of) that empirically based constraints are applied to check model results. So I’ll avoid simply saying “entirely” model based.

    As I understand it, and as far as I can see in the paper, work on planet formation is all about developing and refining models. We just don’t have empirical data over a span of time for a single system. We do have estimates for the age of different systems (which also depend on models?) and this provides important empirical constraints on plausible development timelines implied by models; and timelines depend on all kinds of features of the system (mass of the star, luminosity, size of the disk, etc, etc) as well. So models have implications for the expected distribution of system characteristics that may be checked against observations.

    Being very much a novice in this area, I’m not even sure how much of the above is actually coherent, and I struggled with the paper itself; since I had to look at references also to get a feel for where any how empirical constraints came into it.

  12. Steven Mosher says:

    I always thought the most concise was the most beautiful.

    Eli is techncially correct. Concision matters, altough concision metrics are lacking.
    In my mind when people said “more beautiful” they really meant more concise.

    given two theoies they would point at one and say “more beautiful’
    I looked
    I saw more concise. rather than bitch about semantics I just assumed we were both pointing
    at the same thing and using diffeent names.

    Whatever you call it.. beauty or concision.. its hard to measure. because if you could
    measure it every theory would come with a concision metric.

    maybe an information theory metric might apply..

  13. Eli Rabett says:

    Character count is a pretty good measure of concise.

    Try it on Maxwell’s laws or the laws of thermodynamics.

    Symbolic representations allowed.

    Eli is a bunny of few words. Eli is concise. Ms Rabett is beautiful.

  14. Chris,
    That is mostly reasonable. There are people who are developing models of synthetic population which you can compare with the known exoplanet populations (there are now about 3700 known exoplanets, so it is quite a big sample). However, much of the underlying processes are developed through what would mostly be models, since we can’t easily probe the really small-scale processes. Again, even here we know have ALMA (the Atacama Large Millimeter/sub-millimeter Array) which is starting to give us information about what is going on at relatively small scales. Having said that, models do play a big role in trying to understand the formation and evolution of planetary systems.

  15. Steven Mosher says:

    “Character count is a pretty good measure of concise.”

    https://en.wikipedia.org/wiki/Maxwell%27s_equations

  16. Bob Loblaw says:

    What definition are people using for “model”? I tend to work with “an abstract representation of reality”, in which case everything is science is “models”. A lot of people seem to think model=computer model, but that is extremely narrow. Computers are one method of solving mathematical models, but algebra existed long before computers and provide analytical solutions to many mathematical models. Statistical models are another subset of mathematical models.

    Outside of mathematics, we also have descriptive models. Often not as concise as a mathematical expression of the same idea, but a model none the less. What you are reading now is a descriptive model of my thoughts, not my actual thoughts (AFAIK). In climatology the Koppen classification is one example of a somewhat-numerically-based descriptive classification of climate zones, which gives us fairly consistent definitions of what we mean by “maritime” or “continental” climates. Descriptive, but still a model.

    https://en.wikipedia.org/wiki/K%C3%B6ppen_climate_classification

    Outside of science, people’s everyday life is full of models: our ideas of how the world behaves around us, how we can interact with it. At every stage, our minds contain an abstract representation of reality – not an exact copy of reality itself.

  17. Maxwell’s equations are concise after studying physics and mathematics for a decade to understand what the equations mean.

    Concise is a big part of Ms Rabett, but not very well defined.

    During a paradigm change people can debate very long which theory is more beautiful. Fortunately, after some time the dust settles and the answer typically becomes unambiguous.

  18. Eli Rabett says:

    Victor, you gotta study a language. Years to do it well

  19. Joshua says:

    Conciseness is overrated.

    Or actually, concision is overrated, to be more concise.

  20. Mitch says:

    Concise can be beautiful when right; however, concise can hide ugly flaws when wrong.

  21. Joshua says:

    “Character count is a pretty good measure of concise.”

    That reminds me of one of my favorite stories from a student who was working on her writing and a professor wrote on her paper that she needed to be more concise in her writing. So she went to the professor and asked for help in writing more concisely, and the professor offered this sage advice: “Say the same thing in fewer words.”

    Which, of course, is completely useless advice. It says nothing, really, about how to be more concise.

    It’s interesting (to me, anyway) that some cultures consider conciseness in writing to be “ugly” or lacking artistic sensibility or simplistic or insulting to readers. Even the desirability of “clarity” or explicitly conveying meaning in writing is somewhat culturally dependent. As is, even, the degree to which the writer and the reader are primarily responsible for understanding.

    Of course, any connection to those thoughts and the verbose, rambling and unclear writing in my comments is purely coincidental.

  22. Steven Mosher says:

    laconic.

    for others.
    for models, think lossless compression.
    and…
    character count or symbol count is essentially ontological parsimony.

  23. Willard says:

    The philosophical issues surrounding the notion of simplicity are numerous and somewhat tangled. The topic has been studied in piecemeal fashion by scientists, philosophers, and statisticians (though for an invaluable book-length philosophical treatment see Sober 2015). The apparent familiarity of the notion of simplicity means that it is often left unanalyzed, while its vagueness and multiplicity of meanings contributes to the challenge of pinning the notion down precisely.[2] A distinction is often made between two fundamentally distinct senses of simplicity: syntactic simplicity (roughly, the number and complexity of hypotheses), and ontological simplicity (roughly, the number and complexity of things postulated).[3] These two facets of simplicity are often referred to as elegance and parsimony respectively. For the purposes of the present overview we shall follow this usage and reserve ‘parsimony’ specifically for simplicity in the ontological sense. It should be noted, however, that the terms ‘parsimony’ and ‘simplicity’ are used virtually interchangeably in much of the philosophical literature.

    https://plato.stanford.edu/entries/simplicity/

  24. Speaking of concision, one does not simply define simplicity.

  25. Willard says:

    > Speaking of concision, one does not simply define simplicity.

    You do as our forefathers did, you go around it.

    They called it circumcision, I believe.

  26. Steven Mosher says:

    elegant and simple is beautiful

  27. David B. Benson says:

    Concise theory of everything:

    A = 0.

    Of course, it will take me some considerable time to explain the left side of the equation…

  28. Susan Anderson says:

    brevity, wit’s soul

    (rules are made to be broken …)

  29. Pingback: Tendenza delle catastrofi - Ocasapiens - Blog - Repubblica.it

  30. Szilard says:

    Parsimonious & concise ToE:

    (x)(F)(Fx)

  31. Twitterized Trolley Problem or TTP ™:

  32. The 4 C’s are good, but I like the 2 P’s for introducing a new theory — Plausible and Parsimonious.
    I invoke this instead of referring to Occam’s Razor.

    It also matches to the machine learning & reasoning goals of Accuracy vs Complexity, which are simultaneously optimized, Accuracy standing in for Plausibility and Complexity for Parsimony.

  33. angech says:

    There is a runaway trolley moving down railway tracks toward five people who are tied up and unable to move.
    Are they by any chance Republicans, Brandon?
    Now there is a difficult choice.

  34. TTauriStellarBody said
    “Fred Hoyle is someone who had controversial ideas but was widely respected.

    I think in the climate world Richard Lindzen is a man who is controversial but respected. But there is a yawning chasm between the kind of Hoyle\ Lindzen knowledge level and that of much of the skpetics (and some enthusiastic supporters of “climate change”.

    A better example of a contrarian than Hoyle was Thomas Gold from Cornell, who shared Hoyle’s theory but went even further out there with controversial ideas. Some of Gold’s other ideas are preposterous.

    And I don’t think Richard Lindzen is respected at all. Pierrehumbert said he was “very annoyed at Dick and wanted to prove him wrong” and that Lindzen “made a career out of being wrong in interesting ways”

    (about the 36 minute mark)

    And that Lindzen could “spin ever more clever ways of deceiving yourself” which gets to the heart of trying to achieve elegance in science. Lindzen’s work was piles of complex math that I don’t think anyone ever resolved. I spent time working some of his complicated math stuff out and simplified a lot of it.

  35. izen says:

    There is a runaway trolley moving down railway tracks, towards two branches.
    On one is a Norwegian immigrant, on the other is a refugee from a ‘sh!thole country.
    You can switch the trolley to either track by pushing a lever….

  36. Joshua says:

    izen –

    Which one is better educated? (we already know which one is a hard worker).

    Of course, no one knows anything about the racial characteristics of Norwegians.

  37. izen says:

    https://www.cbsnews.com/news/jorge-garcia-detroit-deported-mexico-us-ice/

    ‘For the state must draw a sharp line of distinction between those who, as members of the nation, are the foundation and support of its existence and greatness, and those who are domiciled in the state, simply as earners of their livelihood there.’

    No prizes for sourcing the quote.

    (OT and political, but contrast with the lack of this distinction in the field of science)

  38. > Now there is a difficult choice.

    Not really, Angech … I’d make the same choice as I would in the original problem.

    One of my favourite Trolley Problem variants is to suppose a newborn infant was tied to the side track.

    What is your choice?

  39. Andrew D., the XKCD comic +1.

  40. izen says:

    The idea that concision, elegance or beauty are a useful measure of scientific theories is restricted to physics. It is not regarded as a required quality in Biology or Chemistry.
    Even within physics it is contradicted by reality.

    Newtonian gravitation, optics and mechanics are obviously much more concise and elegant than General relativity of Quantum mech.

    Beauty and concision may still have some currency in mathematics, although since the solution to the four colour problem I don’t think it is regarded as realistic.
    Perhaps a reduction in ambiguity would be a better abstract measure.

  41. izen,

    > On one is a Norwegian immigrant, on the other is a refugee from a ‘sh!thole country.

    I don’t take action. Let it ride and fate to decide.

  42. “what counts is neither beauty nor simplicity but conciseness. The more that can be encompassed in the most compact way the better the idea.”

    Alas for Eli & the rest of us, one ground floor Trump booster has gone on the air with this idea

    https://vvattsupwiththat.blogspot.com/2018/01/learn-from-best-minds-in-world.html

  43. Elegance of a model may in fact be restricted to physics, but as I said earlier, research in machine learning and machine reasoning of scientific data generally have two orthogonal axis that are optimized against.
    One axis corresponds to an accuracy metric, which is how close the machine learning results can be made to fit to the data. Of course this is prone to over-fitting, so the other axis is a simplicity or anti-complexity metric. And this really derives from information and statistical measures corresponding to well known information criteria metrics such as AIC and BIC.

    So in fact huge effort is spent on searching for elegant and accurate models of data, because there are an infinite number of over-fitted models in the solution space.

  44. izen says:

    @-Brandon Gates
    “One of my favourite Trolley Problem variants is to suppose a newborn infant was tied to the side track.”

    That makes the choice much easier if you put any value on preserving gained knowledge/experience.

    Even if you put zero value on acquired sentience and have a Biblicaly arbitrary 3 score and ten limit, the five would need to have an average age over 56 to make it rational to save the newborn.

  45. izen,

    > Even if you put zero value on acquired sentience and have a Biblicaly arbitrary 3 score and ten limit, the five would need to have an average age over 56 to make it rational to save the newborn.

    Right where I was going. So some variants of the one infant variant:

    1) Everyone tied to a track is a infant.
    2) The combined life expectancy of each group is exactly equal.
    3) Five 70 year-olds are tied to the main line.

    And I get your answer of 56 years-old average for the Five, but argue the figure is too low.

    To the assumptions you’ve added, let’s assume retirement age is 65.

    Or maybe to make the maths easier (my base 7 is terrible), life expectancy is 100 and retirement age is 93.

  46. izen says:

    @-Brandon Gates
    Hypothetical senarios generate hypothetical ethics.
    Real morality only exists in a real context.

    I once knew a medic who when working in obstetrics annoyed the midwives a LOT by quoting the principle in difficult deliveries,
    “Maternal survival is paramount.”

  47. Willard says:

    > Hypothetical senarios generate hypothetical ethics.

    As opposed to what, categorical scenarii and ethics?

  48. izen says:

    @-W
    categorical scenarii elicit substantive ethics ?

  49. Joshua says:

    JH –

    Reading comments at Lucia’s, the nexus between views in climate change and views on the deep state conspiracy are interesting.

  50. Michael 2 says:

    I propose that the success of scientific rivalry producing collaborative efforts depends on the personalities involved, not the fact that the activity involves science. Many endeavors experience the same thing.

    I work with a few network engineers. Two are eager to collaborate, knowing well what they know and having a sense of what they don’t know, and that includes me. By working together we patch each other’s holes in knowledge. The third is not collaborative.

    But I have often found myself deprecated because of my uncertainty about some things where insufficient data exists to be certain. Over here is someone that confidently proclaims his certainty, is frequently wrong but who besides me knows it?

    Executives are attracted to confidence, mistaking it for expertise.

    In the long run actual expertise is sometimes recognized and appreciated, uncertainty can be seen as a virtue.

  51. John Hartz says:

    Michael2: The Dilbert comic strip provides insight into the dysfunctional business world. Do you follow it?

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