The Anti-Reactionary FAQ | Slate Star Codex
[The Cathedral is] the self-organizing consensus of Progressives and Progressive ideology represented by the universities, the media, and the civil service…the Cathedral has no central administrator, but represents a consensus acting as a coherent group that condemns other ideologies as evil [...]
Government and social policy is manufactured in universities, first and foremost at Harvard, followed by Princeton, then Yale, then the other Ivies, Berkeley, and Stanford. As far as politics is concerned, institutions outside of these are pretty much insignificant. Memetic propagation is one-way — it is formulated in the schools and pumped outwards. The universities are not significantly influenced by the outside. The civil servants that make government decisions are either borrowed from universities or almost totally influenced by them. The official mouthpiece of this ideological group is The New York Times, which is the most influential publication in the world outside of the Bible.
6 days ago
Unqualified Reservations: Patchwork: a positive vision (part 1)
A Patchwork realm, or any modern corporate sovereign, is no more bound by the laws it imposes on its residents than Linden Labs is bound by the terms-of-use policy it enforces in Second Life. (In fact, it is probably less so bound, because a terms-of-use policy creates at least the vague suggestion of liability. Whereas suing a sovereign is yet another of these political solecisms.)
6 days ago
Tor's ex-director: 'The criminal use of Tor has become overwhelming'
“What’s changed most about Tor is the drug markets have taken over,” Lewman said. “We had all these hopeful things in the beginning but ever since Silk Road has proven you can do it, the criminal use of Tor has become overwhelming. I think 95 percent of what we see on the onion sites and other dark net sites is just criminal activity. It varies in severity from copyright piracy to drug markets to horrendous trafficking of humans and exploitation of women and children.”
7 days ago
What Facebook Did to American Democracy - The Atlantic
The same was true even of people inside Facebook. “If you’d come to me in 2012, when the last presidential election was raging and we were cooking up ever more complicated ways to monetize Facebook data, and told me that Russian agents in the Kremlin’s employ would be buying Facebook ads to subvert American democracy, I’d have asked where your tin-foil hat was,” wrote Antonio García Martínez, who managed ad targeting for Facebook back then. “And yet, now we live in that otherworldly political reality.
10 days ago
The Clickbait Candidate - The Chronicle of Higher Education
And sure thing, here's the text of the Chronicle piece:

The Clickbait Candidate
By Dave Karpf

The field of political science has been collectively… surprised by Donald Trump’s nomination. The idea of a Trump presidency began as something of a gift for Jon Stewart’s farewell tour. Major media outlets treated it as entertainment news. Pundits viewed it as an impossibility. Last summer, I routinely joked that Trump becoming the nominee would be for American political scientists what the Soviet Union’s collapse was for Kremlinologists—it would violate practically everything we know about a given subject (in this case, primaries) from decades of experience and research.
There was good reason to discount Trump’s early rise in the polls. We had seen this sort of thing before. Political scientists John Sides and Lynn Vavreck refer to it as the “discovery-scrutiny-decline” cycle. In 2012, candidates like Michele Bachmann and Herman Cain each briefly stood atop the polls. Early in the primary season, we often see volatile polling numbers as voters slowly tune in to the race. Candidates with high name recognition can often begin with an inflated polling lead; ones who aren’t “serious” can benefit from significant media attention, which boosts their numbers. But as public scrutiny and media coverage are applied across the field of candidates, support for those who lack experience and party backing tends to fall away. Media coverage and poll numbers rise and fall. It is as predictable as the tides. No outsider candidate like Donald Trump has ever maintained their media dominance or polling lead in the way we have just witnessed. Something was different in 2016.
There isn’t one singular explanation for Trump’s rise. He is a unique celebrity candidate, with a particular talent for turning subtext into text. Certainly he benefited from a crowded field that featured an unending series of strategic pratfalls by his opponents. But one feature of his candidacy has stood out above the rest: Trump’s utter dominance of media coverage (print, online, and television). He didn’t have a brief moment in the sun, followed by a return to normalcy. Even when Ben Carson or Marco Rubio were rising in the polls, Trump was never out of the spotlight.
We have never seen this type of overwhelming media dominance from a presidential candidate. But rather than a testament to Trump’s uniqueness as a candidate, his conquest of the media is likely a product of something new altogether: the metrics revolution in newsrooms, where spikes in traffic can be seen as they occur—and, consequently, can drive coverage throughout the 24-hour news cycle. Thus Trump can lay claim to a new title: the first electoral beneficiary of the era of web analytics.

[drop cap]
The observation that Donald Trump has dominated media coverage has been the subject of much analysis. As The New York Times has reported [LINK:], Donald Trump received nearly $2 billion in free media coverage—about six times as much media attention as his closest rival, Ted Cruz. (Cruz, you might recall, is also a bit of a showman with a penchant for making wild, offensive claims.)
The simple explanation for this gift from the media is what it’s always been: the ratings. “We’re giving the people what they want,” goes the usual defense from news executives. And that explanation is correct—as far as it goes. Trump news, Trump articles, Trump hot takes: all have attracted larger audiences than stories about his competitors. The Republican primaries with Trump have been far more entertaining than the primaries without Trump. CBS chairman Les Moonves has suggested that Trump’s candidacy “may not be good for America, but it’s damn good for CBS.” Ross Douthat of The New York Times has likewise remarked that Trump is “such a gift to our industry.”
But that explanation puts the emphasis in the wrong place. Trump’s media dominance isn’t caused by public demand for Trump. It has been made possible by the media’s new real-time tools for observing the ratings.
Gawker CEO Nick Denton once proclaimed, “Probably the biggest change in internet media isn’t the immediacy of it, or the low costs, but the measurability.” Today, all online media outlets—and really, all media outlets are online outlets now—rely on sophisticated analytics to track, monitor, and judge which stories are the most popular. Some of these analytics are made public, through “most read,” “most emailed,” “trending,” or “related” sidebars on their sites. Others are maintained internally, as a tool to aid editorial judgment.
The thing to remember here is that the act of measuring a process also changes that process. Analytics send a signal to journalists and their editors. In this instance, the signal is that Trump brings in way more traffic than Bush, Cruz, Walker, Clinton, Sanders, or Carson. And this signal then helps guide their news routines—people seem to want more Trump, so let’s give it to them. This in turn sets up a positive feedback loop, in which Trump’s endless media dominance feeds into the narrative that this election is All About Trump.
To understand just how much web analytics has influenced this election, imagine how news coverage would operate without these new analytical tools. Trump would still have been the same showman. He would still have the same instincts, display the same press conference antics, boast the same skills on social media. But without real-time analytics, journalists and their editors would have been far less attuned to the immediate feedback of Trump’s effect. Moreover, television ratings and circulation numbers—the tools of the traditional media landscape—do not provide granular data on how a Trump story compares to a Rubio story. They don’t signal which stories were the most read or the most discussed. Modern analytics tools demonstrate with greater precision just how much more popular Trump was than his opponents. In the absence of news analytics, news organizations would have spread their coverage more evenly, as they have in the past. Trump’s media dominance isn’t just driven by our attention—it’s driven by the media’s new tools for measuring and responding to that attention.

There are two important lessons here, not just about the 2016 presidential election, but about the study of politics in the digital age. First, virtually all social science research is premised on a basic assumption: ceteris paribus (all else being equal). When making predictions about the 2016 election, we start from the assumption that the main actors and institutions within the system will behave much like they always have. This is a reasonable and safe assumption, most of the time. But in light of Trump’s upset, it is time for us to reevaluate whether certain static assumptions are now changing. For instance, where once the invisible primary was waged through media organizations that strived for balanced, neutral coverage, will news organizations now allocate political coverage the way they do celebrity coverage? If the media’s behavior has dramatically shifted in this scenario, it is worth thinking hard about what other areas of public life are about to become shockingly less predictable.

The second lesson is that digital media does not only provide alternative means for people to speak; it also creates new pathways for organizations to listen. We have grown accustomed to looking at digital media as an alternative to traditional media. We compare Twitter and Facebook to press releases and news events. We talk about how social media allows direct interaction between candidates and their supporters, and how citizens online are finding new ways to marshal support for their favorite issues and politicians. But digital media vs. mainstream media is not an either/or proposition. We are operating in what Andrew Chadwick calls a “hybrid media system,” reinventing the rules of political and media behavior along the way. Donald Trump’s victory didn’t come about because he bypasses the media through Twitter. It is because he uses Twitter (and press conferences) to create a media spectacle, and media organizations, carefully monitoring their own analytics, respond with blockbuster coverage.
Analytics provide feedback to media organizations about what their readers, visitors, and viewers are most likely to click, view, and share. Media organizations are still learning how to balance this new type of feedback with their traditional news values and editorial judgment. In the aftermath of the 2016 election, they are going to have to take a long, hard look at how they decide what’s news in the digital age.

David Karpf is associate professor and director of graduate studies at the George Washington University School of Media and Public Affairs. His new book, Analytic Activism: Digital Listening and the New Political Strategy is forthcoming this fall with Oxford University Press.
10 days ago
How Much Should We Trust Ideal Point Estimates from Surveys?∗
In recent years, ideological scaling of the mass public has become a standard method in
scholars’ toolkit for studying representation, polarization, and public opinion. Œe assumption
that citizens’ preferences can be represented in a low-dimensional space is typically
adopted uncritically, despite substantial debate about whether most citizens have coherent
political opinions. In this paper, we propose a strategy to test how well ideal point models
can explain aŠitudes. Œe evaluation strategy, which can be derived from the spatial voting
model commonly used to motivate ideal point estimators, uses cross-validation to assess the
predictive performance of ideal point models. If the model assumptions are satis€ed, ideal
point models should be able to generate accurate out-of-sample predictions about survey responses.
However, we €nd that these predictions are only marginally beŠer than those from
a statistical model that does not include ideal points. In other words, knowing a respondent’s
answers to N −1 survey questions does not meaningfully improve our ability to predict their
response to the Nth question. In contrast, we €nd ideal point models perform exceptionally
well when applied to roll-call votes in the Senate. Additionally, we €nd that there is no identi€able
subset of the population that appears to respond to survey questions in a manner
consistent with assumptions of the ideal point model. We discuss possible methodological
and substantive explanations for the poor model performance in the public. Our results suggest
that standard ideal point estimates in the mass public may be misleading measures of
political orientation.
12 days ago
The Moldbug Variations | Corey Pein
Moldbug was comfortably anonymous, with a modest but influential following in Silicon Valley circles, until TechCrunch revealed his identity as Curtis Yarvin, a San Francisco software engineer whose strange and quixotic startup, Tlön, had garnered some investment capital from Thiel.
12 days ago
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