3 ms·

My take on the self correction is, that later research usually cannot be build on wrong results. So over the decades or centuries the correct results prevail.

mike_hearn 25d ago
You'd think so. I used to believe this too. Surely you try and build on a result which creates an implicit replication study, then your experiments don't work and the problem is discovered pretty quick. Hence, self correction. It often doesn't happen. The reasons seem to vary by field. We do see it in a few very hard fields like materials science. In the softer end of social sciences like anthropology, education or the humanities it's obvious why not: they don't make empirically testable claims about reality anyway so there's nothing to replicate. This is the Arday problem, where he was publishing what they call auto-ethnography: effectively just blog posts about the author's own feelings. He even interviewed himself in the third person. In the harder social sciences it's because nothing actually builds on anything else (see "A problem in theory" [1]). Psychology and related fields like sociology, criminology, etc are basically just a pile of random ideas pooped out in brainstorming sessions. There are hardly any overarching theories generating testable predictions, so studies test whatever random claims the researcher thinks is interesting enough to get in the news. Everything is just rocks lying on the ground rather than towers of understanding, so when one paper is overturned it has no impact on anything else. Citation counts obscure this fact, but do some reverse-citation checks and you'll find a lot of citations are worthless or outright invalid. In modeling based fields like economics, epidemiology or climatology, it's because they can't put the thing they study in a lab and do high speed experimentation. "Replication" comes to mean repeating the same analysis on the same data set. Often they literally just run the same program on the same input file, get the same result and call it replicated - or sometimes they call it replicated even if the outputs don't match! See [2]. But the program is just a set of assumptions, not real discoveries, so building more papers on top of that program's output doesn't detect invalidity. It will all replicate in some very narrow technical sense without that proving anything useful. Sometimes outsiders notice what's happening but over time academia has built up a complex web of lore that protects them psychologically. For example, they routinely reject or ignore feedback from outside their field on the basis that it doesn't come from "experts", meaning themselves, or it comes from "right wing" people, meaning anyone who isn't an academic or close political ally. [1] https://www.nature.com/articles/s41562-018-0522-1 https://www.nature.com/articles/s41562-018-0522-1 [2] https://dailysceptic.org/2020/05/06/code-review-of-fergusons-model/ https://dailysceptic.org/2020/05/06/code-review-of-fergusons...
- tomnicholas1 25d ago
  Whilst I weakly agree with this characterisation, it's not at all fair or accurate to put epidemiology and climatology in the same category as your other examples. Yes they have some weaknesses in replication practices (especially for purely computational work), yes the feedback loop for self-correction can be slow, but it would be a mistake to conclude or imply that the major results of those fields are therefore unreliable. That's because those fields do still make objective empirical predictions about the world, which might take years to be testable but are still ultimately testable. For example, it's been convincingly shown that climate models from decades ago predicted our current climate pretty well. [0] These fields are more comparable to subfields of physics which only get to do big experiments a handful of times, e.g. because they can only observe so many planets/supernovae/universes, or because they have to spend decades building a new billion-dollar machine to test new hypotheses. We should also not confuse these arguments with uselessness - soft social science work can still be societally valuable without being easily empirically testable. [0] https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2019GL085378 https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/201...
  - mike_hearn 25d ago
    Disagree, those two fields are extremely unreliable. It takes a lot of things happening simultaneously to be scientific. Yes, those two do make testable predictions, sort of. But that isn't enough. Modern (computational) epidemiology is rife with unscientific practices. They ignore data that shows a model was invalidated so the fact they make testable predictions isn't really useful. They also engage in a lot of circular reasoning, buggy coding and logical fallacies. During COVID I wrote a whole report on this topic for some politicians [1]. But the biggest issue is "A problem in theory" again - epidemiologists conflate fitting a curve in R with developing a hypothesis, so the field is overrun with overfit models that aren't based on any refinable theory of disease, just misuses of statistics. Even if you prove a paper's predictions were wrong it changes nothing because nothing built on it anyway. The problem in climatology is that when the models don't fit the data they just change the data and claim victory, e.g. September 2013: https://www.spiegel.de/international/world/climate-scientists-face-crisis-over-global-warming-pause-a-923937.html https://www.spiegel.de/international/world/climate-scientist... June 2015: https://www.nature.com/articles/nature.2015.17700 https://www.nature.com/articles/nature.2015.17700 [1] https://plan99.net/~mike/epidemiology.pdf https://plan99.net/~mike/epidemiology.pdf
lazide 25d ago
Only if people fight for that to happen, or there is some external factor forcing it to be so (like a war or other existential threat). Otherwise people will happily go along with BS.
jerf 25d ago
Later correct research can't build on previous wrong results. Later incorrect research most assuredly can build on previous wrong results essentially indefinitely. I'm not constructing a full differential equation model for an HN comment, but I'm pretty sure any realistic model of likelihood of detection of the falseness of past research and other similar parameters would produce a surprisingly sharp cutoff when looked at over time, above which the science does tend to self-correct and below which it disintegrates into endlessly recursive garbage drowning out any real science being produced. And I'm pretty sure a number of fields are below that threshold right now. That doesn't mean the problem is permanent... the parameters can be changed over time, too, but the problem does get worse and harder to fix if allowed to accrue too much.
chermi 25d ago
[flagged]
- amanaplanacanal 25d ago
  Economics is a particularly slippery subject, since double blind experiments are practically impossible. No doubt some of the things Marx wrote correctly describe reality, even if some of the social experiments built on his work were massive failures.
  - chermi 25d ago
    I mean more the Marxist school of thought, not just the economics. Things like critical theory and post modernism. But also, he made predictions of the near future in his time. They were incorrect. No updates were made. Those who did try to refine and update his ideas are far less influential. His original theory survives like gospel. I wish I could say only by non-academics. Edit - back to economics. It's funny. I would say in economics the closest thing we have to double blind wrt economic systems is socialism/communism vs. capitalism. It's clearly not a true double blind. But also clearly some people just don't care to feed that data back in to their models. Because they aren't scientific.
    - undeveloper 24d ago
      marxism (a materialist ideology) is incompatible with post-modernism, a post-truth ideology
dennis_jeeves2 25d ago
>My take on the self correction is, that later research usually cannot be build on wrong results. AFIK, it does not seem to happen much with mainstream medicinal research. Many layers of fraud/incompetence/assumptions for centuries with no correction in sight. Of course there are certain sub-areas that may have advanced. In fact it's the modern day religion, having replaced the god centric religion of yesteryears.
- davidgay 24d ago
  I'll very happily (as a significant benefactor) take this century's medicine over the last. And the one or two centuries before that aren't even worth starting to think about. So something must be working wioth mainstream medicinal research.

mike_hearn 25d ago

You'd think so. I used to believe this too. Surely you try and build on a result which creates an implicit replication study, then your experiments don't work and the problem is discovered pretty quick. Hence, self correction. It often doesn't happen. The reasons seem to vary by field. We do see it in a few very hard fields like materials science. In the softer end of social sciences like anthropology, education or the humanities it's obvious why not: they don't make empirically testable claims about reality anyway so there's nothing to replicate. This is the Arday problem, where he was publishing what they call auto-ethnography: effectively just blog posts about the author's own feelings. He even interviewed himself in the third person. In the harder social sciences it's because nothing actually builds on anything else (see "A problem in theory" [1]). Psychology and related fields like sociology, criminology, etc are basically just a pile of random ideas pooped out in brainstorming sessions. There are hardly any overarching theories generating testable predictions, so studies test whatever random claims the researcher thinks is interesting enough to get in the news. Everything is just rocks lying on the ground rather than towers of understanding, so when one paper is overturned it has no impact on anything else. Citation counts obscure this fact, but do some reverse-citation checks and you'll find a lot of citations are worthless or outright invalid. In modeling based fields like economics, epidemiology or climatology, it's because they can't put the thing they study in a lab and do high speed experimentation. "Replication" comes to mean repeating the same analysis on the same data set. Often they literally just run the same program on the same input file, get the same result and call it replicated - or sometimes they call it replicated even if the outputs don't match! See [2]. But the program is just a set of assumptions, not real discoveries, so building more papers on top of that program's output doesn't detect invalidity. It will all replicate in some very narrow technical sense without that proving anything useful. Sometimes outsiders notice what's happening but over time academia has built up a complex web of lore that protects them psychologically. For example, they routinely reject or ignore feedback from outside their field on the basis that it doesn't come from "experts", meaning themselves, or it comes from "right wing" people, meaning anyone who isn't an academic or close political ally. [1] https://www.nature.com/articles/s41562-018-0522-1 https://www.nature.com/articles/s41562-018-0522-1 [2] https://dailysceptic.org/2020/05/06/code-review-of-fergusons-model/ https://dailysceptic.org/2020/05/06/code-review-of-fergusons...

tomnicholas1 25d ago
Whilst I weakly agree with this characterisation, it's not at all fair or accurate to put epidemiology and climatology in the same category as your other examples. Yes they have some weaknesses in replication practices (especially for purely computational work), yes the feedback loop for self-correction can be slow, but it would be a mistake to conclude or imply that the major results of those fields are therefore unreliable. That's because those fields do still make objective empirical predictions about the world, which might take years to be testable but are still ultimately testable. For example, it's been convincingly shown that climate models from decades ago predicted our current climate pretty well. [0] These fields are more comparable to subfields of physics which only get to do big experiments a handful of times, e.g. because they can only observe so many planets/supernovae/universes, or because they have to spend decades building a new billion-dollar machine to test new hypotheses. We should also not confuse these arguments with uselessness - soft social science work can still be societally valuable without being easily empirically testable. [0] https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2019GL085378 https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/201...
- mike_hearn 25d ago
  Disagree, those two fields are extremely unreliable. It takes a lot of things happening simultaneously to be scientific. Yes, those two do make testable predictions, sort of. But that isn't enough. Modern (computational) epidemiology is rife with unscientific practices. They ignore data that shows a model was invalidated so the fact they make testable predictions isn't really useful. They also engage in a lot of circular reasoning, buggy coding and logical fallacies. During COVID I wrote a whole report on this topic for some politicians [1]. But the biggest issue is "A problem in theory" again - epidemiologists conflate fitting a curve in R with developing a hypothesis, so the field is overrun with overfit models that aren't based on any refinable theory of disease, just misuses of statistics. Even if you prove a paper's predictions were wrong it changes nothing because nothing built on it anyway. The problem in climatology is that when the models don't fit the data they just change the data and claim victory, e.g. September 2013: https://www.spiegel.de/international/world/climate-scientists-face-crisis-over-global-warming-pause-a-923937.html https://www.spiegel.de/international/world/climate-scientist... June 2015: https://www.nature.com/articles/nature.2015.17700 https://www.nature.com/articles/nature.2015.17700 [1] https://plan99.net/~mike/epidemiology.pdf https://plan99.net/~mike/epidemiology.pdf

lazide 25d ago

Only if people fight for that to happen, or there is some external factor forcing it to be so (like a war or other existential threat). Otherwise people will happily go along with BS.

jerf 25d ago

Later correct research can't build on previous wrong results. Later incorrect research most assuredly can build on previous wrong results essentially indefinitely. I'm not constructing a full differential equation model for an HN comment, but I'm pretty sure any realistic model of likelihood of detection of the falseness of past research and other similar parameters would produce a surprisingly sharp cutoff when looked at over time, above which the science does tend to self-correct and below which it disintegrates into endlessly recursive garbage drowning out any real science being produced. And I'm pretty sure a number of fields are below that threshold right now. That doesn't mean the problem is permanent... the parameters can be changed over time, too, but the problem does get worse and harder to fix if allowed to accrue too much.

chermi 25d ago

[flagged]

amanaplanacanal 25d ago
Economics is a particularly slippery subject, since double blind experiments are practically impossible. No doubt some of the things Marx wrote correctly describe reality, even if some of the social experiments built on his work were massive failures.
- chermi 25d ago
  I mean more the Marxist school of thought, not just the economics. Things like critical theory and post modernism. But also, he made predictions of the near future in his time. They were incorrect. No updates were made. Those who did try to refine and update his ideas are far less influential. His original theory survives like gospel. I wish I could say only by non-academics. Edit - back to economics. It's funny. I would say in economics the closest thing we have to double blind wrt economic systems is socialism/communism vs. capitalism. It's clearly not a true double blind. But also clearly some people just don't care to feed that data back in to their models. Because they aren't scientific.
  - undeveloper 24d ago
    marxism (a materialist ideology) is incompatible with post-modernism, a post-truth ideology

dennis_jeeves2 25d ago

>My take on the self correction is, that later research usually cannot be build on wrong results. AFIK, it does not seem to happen much with mainstream medicinal research. Many layers of fraud/incompetence/assumptions for centuries with no correction in sight. Of course there are certain sub-areas that may have advanced. In fact it's the modern day religion, having replaced the god centric religion of yesteryears.

davidgay 24d ago
I'll very happily (as a significant benefactor) take this century's medicine over the last. And the one or two centuries before that aren't even worth starting to think about. So something must be working wioth mainstream medicinal research.