📖 Read loc 1-682 of 12932 (5.27%) of American Amnesia by Jacob S. Hacker and Paul Pierson
This portends to be very interesting in that they plan to show what has changed over much of the 1900’s to indicate the drastic evolution in American politics, life, and philosophy over the recent decades. In light of the political battles between the left and the right over the past several years, this could provide some much needed help and guidance.
Their basic thesis seems to be that a shift away from a mixed economy has slowed American growth and general prosperity. While they do seem to have a pointed (political) view, so far it’s incredibly well documented and footnoted for those who would like to make the counter-argument. They’ve definitely got some serious evidence to indicate how drastic the situation is, but I’m curious if they can directly tie their proposed cause to the effect. If nothing else, they’ve created a laundry list of problems in America which need to be addressed by some serious leadership soon.
In some sense I’m torn about what to think of a broader issue this touches upon and which I mentioned briefly while reading At Home in the Universe. Should we continue on the general path we’ve struck out upon (the mixed economy with government regulation/oversight), or should we continue evolving away? While we can’t see the complexity effects seven levels further in, they may be more valuable than what we’ve got now. For example Cesar Hidalgo looks at the evolution along a continuum of personbyte to larger groups: firms (firmbyte), governments, and mega-corporations in Why Information Grows, so I can easily see larger governments and corporations like Google drastically changing the world in which we live (operating at a level above what most humans can imagine presently), but the complexity of why and how they operate above (and potentially against) the good of the individual should certainly be called into question and considered as we move forward.
During decades the study of networks has been divided between the efforts of social scientists and natural scientists, two groups of scholars who often do not see eye to eye. In this review I present an effort to mutually translate the work conducted by scholars from both of these academic fronts hoping to continue to unify what has become a diverging body of literature. I argue that social and natural scientists fail to see eye to eye because they have diverging academic goals. Social scientists focus on explaining how context specific social and economic mechanisms drive the structure of networks and on how networks shape social and economic outcomes. By contrast, natural scientists focus primarily on modeling network characteristics that are independent of context, since their focus is to identify universal characteristics of systems instead of context specific mechanisms. In the following pages I discuss the differences between both of these literatures by summarizing the parallel theories advanced to explain link formation and the applications used by scholars in each field to justify their approach to network science. I conclude by providing an outlook on how these literatures can be further unified.
Yesterday I ran across this nice little video explaining some recent research on global language networks. It’s not only interesting in its own right, but is a fantastic example of science communication as well.
I’m interested in some of the information theoretic aspects of this as well as the relation of this to the area of corpus linguistics. I’m also curious if one could build worthwhile datasets like this for the ancient world (cross reference some of the sources I touch on in relation to the Dickinson College Commentaries within Latin Pedagogy and the Digital Humanities) to see what influences different language cultures have had on each other. Perhaps the historical record could help to validate some of the predictions made in relation to the future?
The paper “Global distribution and drivers of language extinction risk” indicates that of all the variables tested, economic growth was most strongly linked to language loss.
Finally, I can also only think about how this research may help to temper some of the xenophobic discussion that occurs in American political life with respect to fears relating to Mexican immigration issues as well as the position of China in the world economy.
Those intrigued by the video may find the website set up by the researchers very interesting. It contains links to the full paper as well as visualizations and links to the data used.
Abstract
Languages vary enormously in global importance because of historical, demographic, political, and technological forces. However, beyond simple measures of population and economic power, there has been no rigorous quantitative way to define the global influence of languages. Here we use the structure of the networks connecting multilingual speakers and translated texts, as expressed in book translations, multiple language editions of Wikipedia, and Twitter, to provide a concept of language importance that goes beyond simple economic or demographic measures. We find that the structure of these three global language networks (GLNs) is centered on English as a global hub and around a handful of intermediate hub languages, which include Spanish, German, French, Russian, Portuguese, and Chinese. We validate the measure of a language’s centrality in the three GLNs by showing that it exhibits a strong correlation with two independent measures of the number of famous people born in the countries associated with that language. These results suggest that the position of a language in the GLN contributes to the visibility of its speakers and the global popularity of the cultural content they produce.
“A language like Dutch — spoken by 27 million people — can be a disproportionately large conduit, compared with a language like Arabic, which has a whopping 530 million native and second-language speakers,” Science reports. “This is because the Dutch are very multilingual and very online.”
I’ve just recently finished the excellent book Why Information Grows by César Hidalgo. I hope to post a reasonable review soon, but the ideas in it are truly excellent and fit into a thesis I’ve been working on for a while. For those interested, he does a reasonable synopsis of some of his thought in the talk he gave the the RSA recently, the video can be found below.
The underlying mathematics of what he’s discussing are fantastic (though he doesn’t go into them in his book), but the overarching implications of his ideas with relation to the future of humankind as a function of our economic system and society could have some significant impact.
“César visits the RSA to present a new view of the relationship between individual and collective knowledge, linking information theory, economics and biology to explain the deep evolution of social and economic systems.
In a radical rethink of what an economy is, one of WIRED magazine’s 50 People Who Could Change the World, César Hidalgo argues that it is the measure of a nation’s cultural complexity – the nexus of people, ideas and invention – rather than its GDP or per-capita income, that explains the success or failure of its economic performance. To understand the growth of economies, Hidalgo argues, we first need to understand the growth of order itself.”
I just ordered a copy of Why Information Grows: The Evolution of Order, from Atoms to Economies by Cesar Hidalgo. Although it seems more focused on economics, the base theory seems to fit right into some similar thoughts I’ve long held about biology.
Why Information Grows: The Evolutiion of Order from Atoms to Economies by Cesar Hidalgo
From the book description:
“What is economic growth? And why, historically, has it occurred in only a few places? Previous efforts to answer these questions have focused on institutions, geography, finances, and psychology. But according to MIT’s antidisciplinarian César Hidalgo, understanding the nature of economic growth demands transcending the social sciences and including the natural sciences of information, networks, and complexity. To understand the growth of economies, Hidalgo argues, we first need to understand the growth of order.
At first glance, the universe seems hostile to order. Thermodynamics dictates that over time, order–or information–will disappear. Whispers vanish in the wind just like the beauty of swirling cigarette smoke collapses into disorderly clouds. But thermodynamics also has loopholes that promote the growth of information in pockets. Our cities are pockets where information grows, but they are not all the same. For every Silicon Valley, Tokyo, and Paris, there are dozens of places with economies that accomplish little more than pulling rocks off the ground. So, why does the US economy outstrip Brazil’s, and Brazil’s that of Chad? Why did the technology corridor along Boston’s Route 128 languish while Silicon Valley blossomed? In each case, the key is how people, firms, and the networks they form make use of information.
Seen from Hidalgo’s vantage, economies become distributed computers, made of networks of people, and the problem of economic development becomes the problem of making these computers more powerful. By uncovering the mechanisms that enable the growth of information in nature and society, Why Information Grows lays bear the origins of physical order and economic growth. Situated at the nexus of information theory, physics, sociology, and economics, this book propounds a new theory of how economies can do, not just more, but more interesting things.”
César A. Hidalgo
