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> If my agreeableness is 1, what does that do? It means you are more likely to answer other questions in a certain way. Other studies might even show that you

by tinco 7y ago

> If my agreeableness is 1, what does that do? It means you are more likely to answer other questions in a certain way. Other studies might even show that you might be likely to behave in a certain way. > Does it have a consistent effect? Yes, but like thermometers only work on groups of molecules, the questionnaires are consistent on groups of humans. > Can I measure the effect? With what? Another questionnaire? So it's questionnaires all the way down? No, you could easily do a follow up study by finding groups of people that answered the questionnaires in a certain way, and then have them participate in behavioral experiments. > Well, I know for sure that whatever thermometers are measuring- it's not thermometers all the way down. The manner in which molecules bump into eachother randomly. The harder they do it the more space they take up. The more people in your group with an agreability score of 1, the more space they might take up ;) Opinions are not science, maths is. We don't improve the social sciences with more vague intuitions. If you want to read intuitions then maybe read a glossy instead. Science is about making quantifiable statements, and maths is the way you turn samples into those. We certainly don't need any more room for so-called experts to tell us how we should behave in their papers. We tried that, and it was awful.

YeGoblynQueenne 7y ago
>> Opinions are not science, maths is. We don't improve the social sciences with more vague intuitions. If you want to read intuitions then maybe read a glossy instead. Science is about making quantifiable statements, and maths is the way you turn samples into those. We certainly don't need any more room for so-called experts to tell us how we should behave in their papers. We tried that, and it was awful. That's a very well structured passage, thanks for the comment. However, what I see is that psychology is trying very hard to make quantifiable statements about things that it can't do quantifiable statements about. Yes, maths can be used to turn observations into quantifiable statements. But just because someone is using maths, it doesn't mean they're turning observations into quantifiable statments. You can use maths to quantify non-existent quantities that you have never observed and the maths themselves won't stop you. I will mention Daryl Bem and his measurements of ESP now, but I don't mean that psychology is like parapsychology, only that you can misuse maths if you're not very, very careful. And just because you have maths it doesn't mean you're being careful. And I think intuitions and personal expertise with a subject are the basis of scientific knowledge. The maths are there as a common language to communicate the intutions gained in a manner that makes them accessible to others who do not have the same expertise. Maths is the language of science, because it's used to communicate scientific knowledge, not because it's a set of magickal formulae that transform eveything to solid science.
- wsy 7y ago
  Psychology talks about 'agreeable' in the same way as Physics talks about 'hot'. In our everyday context, 'hot' is quite vague, and people will have widely varying opinions about something being hot, depending on the context and on their personal experience. To cope with that problem, science needs to detach the term from everyday use, and put an artificial definition in its place which allows to make repeatable statements. In its wake, the term loses a lot of its meaning. That is the price for preciseness. Imagine there was a unit for agreeableness, so you could say 'John has an agreeableness of 4.4 Ag'. Then it would be clear that this statement refers to a formal definition (based on a standardized questionnaire), instead of our common vague understanding. Now you could still argue that this new definition is so detached from what we usually mean with agreeableness that it becomes useless. However, you can't simply dismiss the method, you need to bring concrete arguments why the proposed definition does not capture what it is supposed to capture. For example, you could show that people with agreeableness below 2 Ag are married happily more often than people with agreeableness above 4 Ag. Do you have such concrete objections?
- throworangeaway 7y ago
  you can misuse maths if you're not very, very careful That's what nobody ever addresses in these studies. Even assuming all this linguistic questionnaire stuff passes for a measure of something (certainly not biology, it really falls apart on indigenous populations), the further mathematics gives the joke away. Factor analysis is done just wrong. Questionnaires are mostly positively correlated and no thought is spared to how Frobenius-Perron theorem produces spurious factors, that also are dimensionally invalid to boot (which, one imagines, is not unwelcome, as scaling the data may give a stronger result). Then the methodology manages to fail confirmatory factor analysis on its own terms anyways. https://sci-hub.tw/10.1007/s11336-006-1447-6 https://sci-hub.tw/10.1007/s11336-006-1447-6 Clustering validation is not even attempted beyond trying different number of clusters (anywhere from 4 to 13 results in fits only marginally worse than 5). Denunciations of Big Five (and friends) go far and wide decades back. Then there's a flood of reassertions as if nothing happened, and again some refutations of that new wave. Ascent of data science made things comical. One year they do a metastudy with one million respondents, some dude asks some basic questions, the next year they do it with two million as if this answers anything. It is an endless war of attrition and not worth anyone's time.

by tinco 7y ago

YeGoblynQueenne 7y ago

>> Opinions are not science, maths is. We don't improve the social sciences with more vague intuitions. If you want to read intuitions then maybe read a glossy instead. Science is about making quantifiable statements, and maths is the way you turn samples into those. We certainly don't need any more room for so-called experts to tell us how we should behave in their papers. We tried that, and it was awful. That's a very well structured passage, thanks for the comment. However, what I see is that psychology is trying very hard to make quantifiable statements about things that it can't do quantifiable statements about. Yes, maths can be used to turn observations into quantifiable statements. But just because someone is using maths, it doesn't mean they're turning observations into quantifiable statments. You can use maths to quantify non-existent quantities that you have never observed and the maths themselves won't stop you. I will mention Daryl Bem and his measurements of ESP now, but I don't mean that psychology is like parapsychology, only that you can misuse maths if you're not very, very careful. And just because you have maths it doesn't mean you're being careful. And I think intuitions and personal expertise with a subject are the basis of scientific knowledge. The maths are there as a common language to communicate the intutions gained in a manner that makes them accessible to others who do not have the same expertise. Maths is the language of science, because it's used to communicate scientific knowledge, not because it's a set of magickal formulae that transform eveything to solid science.

wsy 7y ago
Psychology talks about 'agreeable' in the same way as Physics talks about 'hot'. In our everyday context, 'hot' is quite vague, and people will have widely varying opinions about something being hot, depending on the context and on their personal experience. To cope with that problem, science needs to detach the term from everyday use, and put an artificial definition in its place which allows to make repeatable statements. In its wake, the term loses a lot of its meaning. That is the price for preciseness. Imagine there was a unit for agreeableness, so you could say 'John has an agreeableness of 4.4 Ag'. Then it would be clear that this statement refers to a formal definition (based on a standardized questionnaire), instead of our common vague understanding. Now you could still argue that this new definition is so detached from what we usually mean with agreeableness that it becomes useless. However, you can't simply dismiss the method, you need to bring concrete arguments why the proposed definition does not capture what it is supposed to capture. For example, you could show that people with agreeableness below 2 Ag are married happily more often than people with agreeableness above 4 Ag. Do you have such concrete objections?
throworangeaway 7y ago
you can misuse maths if you're not very, very careful That's what nobody ever addresses in these studies. Even assuming all this linguistic questionnaire stuff passes for a measure of something (certainly not biology, it really falls apart on indigenous populations), the further mathematics gives the joke away. Factor analysis is done just wrong. Questionnaires are mostly positively correlated and no thought is spared to how Frobenius-Perron theorem produces spurious factors, that also are dimensionally invalid to boot (which, one imagines, is not unwelcome, as scaling the data may give a stronger result). Then the methodology manages to fail confirmatory factor analysis on its own terms anyways. https://sci-hub.tw/10.1007/s11336-006-1447-6 https://sci-hub.tw/10.1007/s11336-006-1447-6 Clustering validation is not even attempted beyond trying different number of clusters (anywhere from 4 to 13 results in fits only marginally worse than 5). Denunciations of Big Five (and friends) go far and wide decades back. Then there's a flood of reassertions as if nothing happened, and again some refutations of that new wave. Ascent of data science made things comical. One year they do a metastudy with one million respondents, some dude asks some basic questions, the next year they do it with two million as if this answers anything. It is an endless war of attrition and not worth anyone's time.