Can you say a little bit more about the point you are trying to make here? This could be an interesting, or on the other hand trivial, finding for a number of reasons, but I’m curious as to why you don’t speculate on these reasons at all. I’m not sure this correlation is particularly compelling without discussion of why it exists.
Given you favourably cite Lynn, perhaps it is the case you believe in his conclusions regarding race itself determining IQ, and think this explains (at least part) of the effect. Perhaps you don’t believe this. I think it behoves you, given the controversy regarding this work, to state your commitment (or lack thereof) to these ideas since your data source involves work conducted, arguably, to motivate this hypothesis.
Regardless, I think without further context it’s very hard to interpret this evidence as favouring any particular theory: whether it be regarding race, education, culture, nutrition or any number of other factors.
It’s also unclear to me why one would be interested in associating total IQ with GDP rather than average IQ with GDP per capita. Perhaps you could say something about that, if you’ve had any thoughts?
Can you say a little bit more about the point you are trying to make here? This could be an interesting, or on the other hand trivial, finding for a number of reasons, but I’m curious as to why you don’t speculate on these reasons at all. I’m not sure this correlation is particularly compelling without discussion of why it exists.
The point I am trying to make is in the 1st bullet of the summary. Across countries in 2019, the population with an IQ above the global mean IQ was a good predictor of real GDP. I think there is a correlation between IQ and income within countries, so I was not surprised to find a correlation between population with high IQ and real GDP across countries.
Given you favourably cite Lynn, perhaps it is the case you believe in his conclusions regarding race itself determining IQ, and think this explains (at least part) of the effect. Perhaps you don’t believe this. I think it behoves you, given the controversy regarding this work, to state your commitment (or lack thereof) to these ideas since your data source involves work conducted, arguably, to motivate this hypothesis.
Before reading this comment from Stephen, I did not know Lynn was a contentious figure. Lynn being the primary author of Lynn 2019 and other studies about IQ were what I knew about Lynn. I cited Lynn 2019 on the merits of its methodology, and tried to check the validity of the data:
The correlation coefficient for the relationship between the mean IQ by country from Lynn 2019 and WordData is 88.7 %[2] (see M2 of tab “IQ by country”).
Regarding:
Given you favourably cite Lynn, perhaps it is the case you believe in his conclusions regarding race itself determining IQ, and think this explains (at least part) of the effect. Perhaps you don’t believe this. I think it behoves you, given the controversy regarding this work, to state your commitment (or lack thereof) to these ideas since your data source involves work conducted, arguably, to motivate this hypothesis.
I do not know which specific conclusions you are referring to, and I am not very familiar with the arguments and studies supporting the claims that race determines IQ. I am not sure what you mean by “these ideas”, but, to be clear, I believe race has a negligible effect on moral weight. My motivation for not including disclaimers is captured in the following paragraphs from this post from Emrik:
If writers have to spend five paragraphs on disclaimers and clarification just to make sure we don’t accuse them of nazism, well, we’ve wasted everyone’s time, and we’ve lost a hundred good writers who didn’t want to take the risk in the first place.
But it’s worse, because if we already have the norm of constantly suspecting nazism or whatever, then the first writer to notcorrect for that misunderstanding is immediately going to look suspicious. This is what’s so vicious about refusing to interpret with a little more recursive wisdom. If you have an equilibrium of both expecting and writing disclaimers about X, it self-perpetuates regardless of whether anyone actually means or supports X.
As for:
Regardless, I think without further context it’s very hard to interpret this evidence as favouring any particular theory: whether it be regarding race, education, culture, nutrition or any number of other factors.
I agree. This is why I have not made any claims regarding implications of the correlation.
It’s also unclear to me why one would be interested in associating total IQ with GDP rather than average IQ with GDP per capita. Perhaps you could say something about that, if you’ve had any thoughts?
The analysis also focus on country trends (see 2nd bullet of the summary), and I suppose total metrics are more informative than per capita metrics to study the evolution of the global distribution of resources by country. Based on the data I have collected, there is a correlation of 60.6 % between real GDP per capita and mean IQ across countries in 2019.
I take your word for it that you’re naïve about Lynn’s work on race and IQ. I don’t fully buy into the idea that defensive writing is bad per se, but I won’t litigate that here. I don’t think the central errors I was criticising are relevant to this. Briefly:
If you’re going to present data, you should critically engage with the source of that data. Correlation with another source without critically engaging with that source either is meaningless. For instance, that website states: “Often surprisingly but scientifically proven, a warmer climate badly affects the intelligence quotient.” This is not an honest interpretation of the literature nor a coherent account of the scientific method.
Presenting data without any context around that data strikes me as a strange choice at best. I don’t really believe that you think there is no interesting conclusions that might be drawn: why else did you post it? Surely you think there is something interesting to be said about it? Data itself is inherently meaningless, but from its interpretation we can make interesting observations. I therefore think you should at least present relevant context around data, and state why you think it is interesting, so discussion can proceed. The alternative, especially around such a controversial topic, is the result here: confused commenters trying to tease out why you would post this data but not seem inclined to share what conclusions you are drawing from it.
To be totally clear, I believe you that you don’t find this interesting for issues relating to race, I just don’t think given that debate informs an understanding of both the data and its context, that it should be ignored. Unfortunately, information doesn’t exist in a vacuum.
If you’re going to present data, you should critically engage with the source of that data.
why else did you post it? Surely you think there is something interesting to be said about it?
I agree further engaging with the quality of the data would improve the post. However, this does not necessarily imply that I should have engaged more with the data. I had done this analysis for other purposes, and thought that posting this may be better than nothing. I should have tagged the post as “Personal blog” instead of the default “Front page” (I was unaware of the tab “Personal blog”, but will have it in mind for similar posts in the future).
Data itself is inherently meaningless, but from its interpretation we can make interesting observations
I would say data is inherently meaningful. For example, I think the data explorers and graphs from OWID convey lots of useful information. However, interpretation is also valuable to e.g. explain data in plain language, clarify what we can and cannot infer from them, pose further work questions, etc. (so reading articles from OWID besides just checking graphs leads to a better understanding).
Can you say a little bit more about the point you are trying to make here? This could be an interesting, or on the other hand trivial, finding for a number of reasons, but I’m curious as to why you don’t speculate on these reasons at all. I’m not sure this correlation is particularly compelling without discussion of why it exists.
Given you favourably cite Lynn, perhaps it is the case you believe in his conclusions regarding race itself determining IQ, and think this explains (at least part) of the effect. Perhaps you don’t believe this. I think it behoves you, given the controversy regarding this work, to state your commitment (or lack thereof) to these ideas since your data source involves work conducted, arguably, to motivate this hypothesis.
Regardless, I think without further context it’s very hard to interpret this evidence as favouring any particular theory: whether it be regarding race, education, culture, nutrition or any number of other factors.
It’s also unclear to me why one would be interested in associating total IQ with GDP rather than average IQ with GDP per capita. Perhaps you could say something about that, if you’ve had any thoughts?
Hi Kieran,
Thanks for your questions.
The point I am trying to make is in the 1st bullet of the summary. Across countries in 2019, the population with an IQ above the global mean IQ was a good predictor of real GDP. I think there is a correlation between IQ and income within countries, so I was not surprised to find a correlation between population with high IQ and real GDP across countries.
Before reading this comment from Stephen, I did not know Lynn was a contentious figure. Lynn being the primary author of Lynn 2019 and other studies about IQ were what I knew about Lynn. I cited Lynn 2019 on the merits of its methodology, and tried to check the validity of the data:
Regarding:
I do not know which specific conclusions you are referring to, and I am not very familiar with the arguments and studies supporting the claims that race determines IQ. I am not sure what you mean by “these ideas”, but, to be clear, I believe race has a negligible effect on moral weight. My motivation for not including disclaimers is captured in the following paragraphs from this post from Emrik:
As for:
I agree. This is why I have not made any claims regarding implications of the correlation.
The analysis also focus on country trends (see 2nd bullet of the summary), and I suppose total metrics are more informative than per capita metrics to study the evolution of the global distribution of resources by country. Based on the data I have collected, there is a correlation of 60.6 % between real GDP per capita and mean IQ across countries in 2019.
I take your word for it that you’re naïve about Lynn’s work on race and IQ. I don’t fully buy into the idea that defensive writing is bad per se, but I won’t litigate that here. I don’t think the central errors I was criticising are relevant to this. Briefly:
If you’re going to present data, you should critically engage with the source of that data. Correlation with another source without critically engaging with that source either is meaningless. For instance, that website states: “Often surprisingly but scientifically proven, a warmer climate badly affects the intelligence quotient.” This is not an honest interpretation of the literature nor a coherent account of the scientific method.
Presenting data without any context around that data strikes me as a strange choice at best. I don’t really believe that you think there is no interesting conclusions that might be drawn: why else did you post it? Surely you think there is something interesting to be said about it? Data itself is inherently meaningless, but from its interpretation we can make interesting observations. I therefore think you should at least present relevant context around data, and state why you think it is interesting, so discussion can proceed. The alternative, especially around such a controversial topic, is the result here: confused commenters trying to tease out why you would post this data but not seem inclined to share what conclusions you are drawing from it.
To be totally clear, I believe you that you don’t find this interesting for issues relating to race, I just don’t think given that debate informs an understanding of both the data and its context, that it should be ignored. Unfortunately, information doesn’t exist in a vacuum.
Thanks for clarifying.
I agree further engaging with the quality of the data would improve the post. However, this does not necessarily imply that I should have engaged more with the data. I had done this analysis for other purposes, and thought that posting this may be better than nothing. I should have tagged the post as “Personal blog” instead of the default “Front page” (I was unaware of the tab “Personal blog”, but will have it in mind for similar posts in the future).
I would say data is inherently meaningful. For example, I think the data explorers and graphs from OWID convey lots of useful information. However, interpretation is also valuable to e.g. explain data in plain language, clarify what we can and cannot infer from them, pose further work questions, etc. (so reading articles from OWID besides just checking graphs leads to a better understanding).