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Patents Per Capita and Hofstede's Cultural Dimensions

Thinking about social dimensions and innovation, it occurred to me that there might be relationship with masculinity, but then quickly dismissed it, considering it much more likely to be predicated on science/math education. Even then, other cultural elements might be more likely correlated. What follows is an exploration of various correlations with patents per capita.

Although Hofstede's Cultural Dimensions did have significant correlation with patents per capita, somewhat surprisingly, PISA scores by country, education, nor average IQ, had a strong relationship with patent production, although if Asia was included, statistically it would.

Notes:
I often exclude Asia from analyses, as the initial driver of this work was looking at cultures that are similar, to tease out social effects. That is also why I ignore looking at all countries, as some relationships across the entire world disappear when limited to just developed economies. As an example, the value of work and its b…

Hofstede's Long-term Orientation and Individuality: Obesity Relationships (using R)

Hofstede extended his original four dimensions, adding measures Long-Term Orientation (LTO) and Indulgence (Ind) in response to other researchers studies. While reading Hofstede's Cultures and Organizations: Software of the Mind, Third Edition I was struck by the lackluster reporting of the correlation between obesity and indulgence. It seemed obvious one would delve a bit further, maybe looking at a compound relationship between both indulgence and LTO, e.g., does short-sightedness and indulgence lead to obesity. Although I limit my analysis to OECD countries, that is what I present here.

An explanation of dimensions can be found on Hofstede's site.

Hofstede's Dimensions and Obesity

A first step would be to see what relationships exist between obesity and the dimensions:

1: # LM - Multiple Regression - New Hofstede, LTO and Ind 2: # Load the data into a matrix 3: rm(list = ls()) 4: setwd("../Data") 5: oecdData <- read.table("OECD - Quality…