Navigation and the Wealth of Nations

Global Determinants of Navigational Ability, by Coutrot et al:

Using a mobile-based virtual reality navigation task, we measured spatial navigation ability in more than 2.5 million people globally. Using a clustering approach, we find that navigation ability is not smoothly distributed globally but clustered into five distinct yet geographically related groups of countries. Furthermore, the economic wealth of a nation (Gross Domestic Product per capita) was predictive of the average navigation ability of its inhabitants and gender inequality (Gender Gap Index) was predictive of the size of performance difference between males and females. Thus, cognitive abilities, at least for spatial navigation, are clustered according to economic wealth and gender inequalities globally.

This is an incredible study. They got 2.5 million people from all over the world to participate.

If you’ve been following any of the myriad debates about intelligence, IQ, and education, you’re probably familiar with the concept of “multiple intelligences” and the fact that there’s rather little evidence that people actually have “different intelligences” that operate separately from each other. In general, it looks like people who have brains that are good at working out how to do one kind of task tend to be good at working out other sorts of tasks.

I’ve long held navigational ability as a possible exception to this: perhaps people in, say, Polynesian societies depended historically far more on navigational abilities than the rest of us, even though math and literacy were nearly absent.

Unfortunately, it doesn’t look like the authors got enough samples from Polynesia to include it in the study, but they did get data from Indonesia and the Philippines, which I’ll return to in a moment.

Frankly, I don’t see what the authors mean by “five distinct yet geographically related groups of countries.” South Korea is ranked between the UK and Belgium; Russia is next to Malaysia; Indonesia is next to Portugal and Hungary.

GDP per capita appears to be a stronger predictor than geography:

Some people will say these results merely reflect experience playing video games–people in wealthier countries have probably spent more time and money on computers and games. But assuming that the people who are participating in the study in the first place are people who have access to smartphones, computers, video games, etc., the results are not good for the multiple-intelligences hypothesis.

In the GDP per Capita vs. Conditional Modes (ie how well a nation scored overall, with low scores better than high scores) graph, countries above the trend line are under-performing relative to their GDPs, and countries below the line are over-performing relative to their GDPs.

South Africa, for example, significantly over-performs relative to its GDP, probably due to sampling bias: white South Africans with smartphones and computers were probably more likely to participate in the study than the nation’s 90% black population, but the GDP reflects the entire population. Finland and New Zealand are also under-performing economically, perhaps because Finland is really cold and NZ is isolated.

On the other side of the line, the UAE, Saudi Arabia, and Greece over-perform relative to GDP. Two of these are oil states that would be much poorer if not for geographic chance, and as far as I can tell, the whole Greek economy is being propped up by German loans. (There is also evidence that Greek IQ is falling, though this may be a near universal problem in developed nations.)

Three other nations stand out in the “scoring better than GDP predicts” category: Ukraine, (which suffered under Communism–Communism seems to do bad things to countries,) Indonesia and the Philippines. While we could be looking at selection bias similar to South Africa, these are island nations in which navigational ability surely had some historical effect on people’s ability to survive.

Indonesia and the Philippines still didn’t do as well as first-world nations like Norway and Canada, but they outperformed other nations with similar GDPs like Egypt, India, and Macedonia. This is the best evidence I know of for independent selection for navigational ability in some populations.

The study’s other interesting findings were that women performed consistently worse than men, both across countries and age groups (except for the post-90 cohort, but that might just be an error in the data.) Navigational ability declines steeply for everyone post-23 years old until about 75 years; the authors suggest the subsequent increase in abilities post-70s might be sampling error due to old people who are good at video games being disproportionately likely to seek out video game related challenges.

The authors note that people who drive more (eg, the US and Canada) might do better on navigational tasks than people who use public transportation more (eg, Europeans) but also that Finno-Scandians are among the world’s best navigators despite heavy use of public transport in those countries. The authors write:

We speculate that this specificity may be linked to Nordic countries sharing a culture of participating in a sport related to navigation: orienteering. Invented as an official sport in the late 19th century in Sweden, the first orienteering competition open to the public was held in Norway in 1897. Since then, it has been more popular in Nordic countries than anywhere else in the world, and is taught in many schools [26]. We found that ‘orienteering world championship’ country results significantly correlated with countries’ CM (Pearson’s correlation ρ = .55, p = .01), even after correcting for GDP per capita (see Extended Data Fig. 15). Future targeted research will be required to evaluate the impact of cultural activities on navigation skill.

I suggest a different causal relationship: people make hobbies out of things they’re already good at and enjoy doing, rather than things they’re bad at.

 

 

Please note that the study doesn’t look at a big chunk of countries, like most of Africa. Being at the bottom in navigational abilities in this study by no means indicates that a country is at the bottom globally–given the trends already present in the data, it is likely that the poorer countries that weren’t included in the study would do even worse.

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