iCLODIVS

by Michael Lind. OVER A century ago, at the Royal Geographic Society in London, Halford Mackinder delivered a paper titled “The Geographical Pivot ...

The midterm elections were a victory for status quo centrists in both parties. by. Michael Lind. November 09, 2022.

James Burnham’s tract on political realism, The Machiavellians, finishes with a number of remarkable postulates. In the sixth, Burnham states, “Historical and political science is above all the study of the elite, its composition, its structure, and the mode of its relation to the non-elite.” This axiom is remarkable because, in contemporary social science, research…

Continue reading What Is an Elite Today? on American Affairs Journal.

A new approach to tech policy is taking root in the GOP, and it’s not what you might expect from the party of Alan Greenspan and Friedrich Hayek.

Led by a handful of ambitious, policy-minded senators, a group of conservatives is embracing the idea of subsidizing the tech industry and advanced manufacturing — with an eye toward building a competitive edge over China, and revitalizing the hollowed-out industrial centers that have given the party its Trump-era populist verve.

Their tolerance, if not thirst, for government intervention might have been anathema in years past (and to some of their current peers). But as the overall regulatory apparatus increasingly finds itself racing to keep up with industry, so too has the GOP. That’s allowed technocratic conservatives like Indiana’s Sen. Todd Young, a chief driver of what would become this year’s CHIPS and Science Act, or Sen.-elect J.D. Vance, who ran his whole campaign as a sort of pilot project for tech-minded, statist Republican politics, to stake out new territory at the cutting edge of conservative think-tank world.

Wells King is the research director at American Compass, one of said think tanks, and a former policy advisor to Sen. Mike Lee (R-Utah). He wrote this week in a paper and adapted essay about what he calls “Silicon Valley’s Public Garages,” or the early computer-era tech innovators whose subsidized roots are now largely forgotten. I spoke with him this morning about why these conversations are happening now, what the future might hold beyond chip manufacturing, and where Republicans might find political support for a more hands-on industrial policy. A version of the conversation — condensed and edited for clarity — follows…

Introduction to Special Issue: Leading Scholars of the Past Comment on Dawn of Everything

Today's reformers of the right have no connection to the Republican Party's past accomplishments in strengthening the social contract.

KEY POINTS FROM THIS ARTICLE

— Special Counsel Robert Mueller’s recent testimony was a reminder that Russia attempted to influence the outcome of the 2016 election and very well may try to do so again in 2020.

— This begs the question: Is there any evidence that Russian interference may have impacted the results, particularly in key states?

— The following analysis suggests that the 2016 results can be explained almost entirely based on the political and demographic characteristics of those states. So from that standpoint, the answer seems to be no.

What explains the 2016 results?

Special Counsel Robert Mueller’s recent testimony before the House Judiciary and Intelligence Committees, and the Mueller Report itself, make it very clear that the Russian government made a major effort to help Donald Trump win the 2016 U.S. presidential election. What the Mueller Report did not determine, however, was whether that effort was successful. In this article, I try to answer that question by examining whether there are any indications from the 2016 results that Russian interference efforts may have played a clear role in the outcome. One such indication would be if Trump did better in key swing states than a range of demographic, partisan, and historical factors would have predicted.

We know from the Mueller Report that Trump campaign manager Paul Manafort briefed a longtime associate who the FBI believes had ties with Russian intelligence about campaign strategy and, according to Manafort deputy Rick Gates, discussed decisive battleground states such as Michigan, Pennsylvania, and Wisconsin. Manafort also directed Gates to share internal polling data, which may have influenced Russian operations.

In order to address the question of whether the Russian interference effort worked, I conducted a multiple regression analysis of the election results at the state level. The dependent variable in this analysis was the Trump margin. My independent variables were the 2012 Mitt Romney margin, to control for traditional state partisanship, state ideology measured by the Gallup Poll (the percentage of conservatives minus the percentage of liberals), the percentage of a state’s population made up of whites without college degrees, the estimated turnout of eligible voters in the state, the state unemployment rate in November 2016 (to measure economic conditions), the number of Trump campaign rallies in the state, the number of Clinton campaign rallies in the state, a dummy variable for the state of Utah to control for the large vote share won by an independent conservative Mormon candidate from that state, Evan McMullin, and, finally, a dummy variable for swing states. The swing states included Arizona, Colorado, Florida, Iowa, Minnesota, Nevada, New Hampshire, Ohio, and Virginia, in addition to Michigan, Pennsylvania, and Wisconsin. The results of the regression analysis are displayed in Table 1 along with a scatterplot of the actual and predicted results in Figure 1.

Table 1: Results of regression analysis of Trump margin in the states

Source: Data compiled by author.

Figure 1: Scatterplot of actual Trump margin by predicted Trump margin in the states

Note: Alaska and District of Columbia omitted due to lack of state ideology data.

Source: Data compiled by author.

The regression equation proved to be extremely successful in predicting the election results, explaining a remarkable 98% of the variance in Trump vote margin in the states. Several of the independent variables had very powerful effects including the 2012 Romney margin, state ideology, and the percentage of non-college whites in the state. Even after controlling for traditional state partisanship and ideology, the size of the non-college white population in a state was a strong predictor of support for Donald Trump. The data in Table 1 also show that Evan McMullin’s candidacy dramatically reduced Trump’s vote share in Utah — although Trump still carried the state easily. In addition, the results show that voter turnout had a modest but highly significant effect on the results — the higher the turnout in a state, the lower the vote share for Trump. These results seem to confirm the conventional wisdom that higher voter turnout generally helps Democrats.

In addition to showing what mattered in explaining the results of the 2016 presidential election in the states, the data in Table 1 also show what did not matter. Economic conditions at the state level, at least as measured by state unemployment, did not matter. The number of campaign rallies held by the candidates in a state did not matter. Finally, and perhaps most importantly from the standpoint of estimating the impact of Russian interference, Donald Trump did no better than expected in the swing states. The coefficient for the swing state dummy variable is extremely small and in the wrong direction: Trump actually did slightly worse than expected in the swing states based on their other characteristics.

Table 2: Predicted and actual Trump margin in key swing states

Source: Data compiled by author.

This can also be seen in Table 2, which compares the actual and predicted results in the three swing states that ultimately decided the outcome of the election: Michigan, Pennsylvania, and Wisconsin. What is most striking about the data in this table is that Donald Trump actually slightly under-performed the model’s predictions in all three states. He did about one point worse than predicted in Michigan, about two points worse than predicted in Pennsylvania, and between two and three points worse than predicted in Wisconsin. There is no evidence here that Russian interference, to the extent that it occurred, did anything to help Trump in these three states.

Conclusions

I find no evidence that Russian attempts to target voters in key swing states had any effect on the election results in those states. Instead, the results were almost totally predictable based on the political and demographic characteristics of those states, especially their past voting tendencies, ideological leanings, and demographics. Of course, that doesn’t mean that the Russians weren’t trying to influence the results or that they might not succeed in the future. Nor does it speak to Russian efforts to hack into U.S. voting systems and potentially alter voter registration data or even election results themselves.

There are plenty of grounds for real concern here. Indeed, the Electoral College system used to choose the president almost invites efforts to interfere in the election. Whereas trying to affect the national popular vote results would probably be prohibitively expensive, efforts to target a few key swing states could be much more cost-effective and harder to detect. As a result, there is little doubt that these efforts will continue in 2020 and beyond, especially if we have a president who seems to be inviting them.

Alan I. Abramowitz is the Alben W. Barkley Professor of Political Science at Emory University and a senior columnist with Sabato’s Crystal Ball. His latest book, The Great Alignment: Race, Party Transformation, and the Rise of Donald Trump, was released last year by Yale University Press.

Scientist-turned-historian Peter Turchin is best known for a dire prediction he made in 2010: we were headed for serious unrest, circa 2020. Peter came to this (as-so-happened) accurate prediction by treating the soft science of history like a hard one — what he calls cliodynamics. He and his team quantified indicators of social unrest in previous historical periods, generating a database of information, and then created a structural-dynamic model that could determine the biggest drivers of social violence and societal collapse. Peter, who’s currently serving as the Project Leader at the Complexity Science Hub in Vienna, talks to us about his approach to history, the factors that are most responsible for our current period of unrest, and the actions that could, just maybe, divert us from Civil War II. 

 Check out our ‘Inscrutable’ blog and ‘Uncertainty’ newsletter for thoughts and rants. To support us and gain access to exclusive content, consider becoming a paid member of Uncertain on Substack. Follow @UncertainPod on your social media of choice.

On the agenda:

-Peter pre-amble and Vishaan post-script (0:00-7:01)

-How cliodynamics work? (07:02-17:21)

-Quantifying instability, locating gaps, and making predictions (17:22-28:33

-The state of our present-day empire (28:34-38:28)

-The trouble with too many elites (38:29-51:34)

-How to stop an unfolding trainwreck (51:35-1:02:44)

Uncertain Things is hosted and produced by Adaam James Levin-Areddy and Vanessa M. Quirk. For more doomsday rumination, subscribe to: uncertain.substack.com.

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Given the ongoing decay of our institutions and their utter failure to address the climate crisis it is not far fetched to ask whether we are headed for some kind of societal collapse. A highly relevant book is Joseph Tainter’s The Collapse of Complex Societies, published in 1988. I had two key takeaways from reading it.

First, there are way more examples of complex societies collapsing than I was aware of. I was of course familiar with the collapse of the Roman Empire and was also aware of Mayas in the Yucatan (having visited there) but Tainter provides at least a dozen examples, including several societies that I had never heard of before. He also rightfully points out that complexity so far is the historical exception and widespread complexity (meaning the world being dominated by complex societies is a particularly recent phenomenon). So the takeaway here is in part that we really aren’t very deep into the current complexity phase and that the past track record over longer time periods isn’t exactly encouraging.

Second, Tainter proposes a very simple and general mechanism leading to collapse: declining marginal returns to complexity. Over time the benefits of complexity diminish and its costs increase. When that happens societies become prone to collapse from (a) having not enough reserves to deal with shocks and/or (b) parts of society that are bearing a disproportionate share of the cost of complexity resisting. He then analyzes the role of this mechanism in three collapses in some detail, including for the collapse of the Roman Empire. One striking feature of that particular collapse is the massive currency devaluation over hundreds of years that has strong echos in today’s world.

Tainter gives many reasons for why the benefits of complexity decline over time and its cost rise. One that he doesn’t discuss much but that is particularly pertinent to today, is the accretion of laws and regulations. While these are essential tools for maintaining complex societies it is particularly easy to see how over time their benefits decline and their costs rise when you only ever add laws and regulations but never do a partial or complete rewrite. It is the societal equivalent of the accumulation of technical debt in startups.

Are there ways of avoiding collapse? First, as Tainter points out, quite a few societies don’t collapse but simply go into a long decline and then get taken over by other societies. He thinks that this is a possible scenario for many societies today because they are surrounded by other complex societies (this does, however, leave open the possibility of many societies collapsing at about the same time). Second, Tainter also points to examples of avoiding collapse through a big resource or energy unlock. Deploying solar at massive scale could be such an unlock, as could be fusion if we get it working.

All in all a very worthwhile read combining a ton of history with an analytical framework. I find most historical writing to be replete with ad hoc explanations that don’t sound much more compelling than CNBC talking about why the market went up or down. The Collapse of Complex Societies stands out from that and all the more so coming in at only 215 pages. Highly recommended.