Tag Archives: Fake News

Snopes Attacks Satire In Ominous Self-Satirization

12 Monday Aug 2019

Posted by in Censorship, Free Speech

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Snopes.com began as an investigator of urban legends and rumors, exposing myths in an exercise that was useful and often fascinating. More recently, despite its founder’s weak argument to the contrary, Snopes has fully revealed its bias against certain political viewpoints, along with a tendency to avoid reporting some actual facts as facts when it suits itself. Lately this has reached a pathetic level, with the site drawing amused reaction to its confusion over the satiric nature of The Babylon Bee. The Bee is a truly funny site similar to The Onion, but it bills itself as “Christian Satire”. If you find that off-putting or think it means the humor must be cornpone, think again. Of course, there is no doubt that the Bee’s humor often pokes fun at the Left, which probably explains Snopes’ motives.

Snopes itself has not been above a bit of fibbing. Its “political fact-checker”, Kim Lacapria, is a former leftist blogger, known to have maligned the Tea Party as “Teahadists”, a funny mischaracterization of the unquestionably peaceful movement as violent. She’s not exactly a person you’d trust as an impartial arbiter of political “fact”. Linda Sue Grimes wrote an informative article with several prominent examples of bias by Snopes. There have also been reports of sordid personal and financial exploits  by one of Snopes’ founders, much of which stands up to scrutiny. 

In its latest misadventure in fact-weaving, Snopes’ has charged that the Bee published a story “intended to deceive” readers, and it claimed the Bee  had done so in the past. The story was entitled “Georgia Lawmaker Claims Chick-Fil-A Employee Told Her To Go Back To Her Country, Later Clarifies He Actually Said ‘My Pleasure“. It was inspired by an incident in which the same Georgia lawmaker apparently had too many items in the express checkout at a Publix grocery store. She claimed that an angry white man told her to “go back to where you came from”. However, the Publix clerk with whom she had the altercation, who happens to be Cuban, denies having said any such thing, though he did admit to calling her a bitch. The lawmaker’s allegation seems suspiciously coincidental, having come in the immediate wake of Donald Trump’s controversial tweet that the quartet of federal lawmakers known as “The Squad” should “go back to where they came from”.

Apparently, the humor in the Bee’s article was just a bit too subtle for Snopes, whose “woke” employees have particularly vivid imaginations. The Bee article was funny precisely because it ridiculed those who hear racial “dog whistles” everywhere. The idea that a Chinese employee working a drive-through at Chick-Fil-A would say such a thing is unlikely to say the least. Anyone who has ever visited a Chick-Fil-A knows it. Too many of those with whistles in their ears haven’t had the pleasure.

Has the Bee intended to deceive its readers in the past? Perhaps Snopes was referring to an article entitled “CNN Purchases Industrial-Sized Washing Machine to Spin News Before Publication“. Snopes went to the trouble of calling that story false and bringing it to Facebook’s attention. Facebook actually issued a warning to the Bee (for which FB later apologized). But here’s the thing, in Grimes’ words:

“Debunking a piece of satire renders the debunker as functionally illiterate, appearing too ignorant to understand that a piece of satire does not function to relay information as a news report would.”

It’s actually much worse than that. If Snopes wants to to assess the objective truth of claims, that’s one thing, but it has drifted into the assessment of literary and authorial intent. That’s ominous for the cause of free discourse, especially to the extent that social media sites rely on Snopes as a filter to deplatform certain voices or silence points of view. Snopes has no business attempting to draw distinctions between satire and “fake news” or any intent to deceive, because it’s bound to get it wrong and already has. They might as well fact-check stand-up comics whose routines might confuse a few dimwitted members of the public, and Snopes just might do so if the comic doesn’t support its preferred political narrative. Snopes’ role is not to protect the unsophisticated from satire, and apparently its fact-checkers feel no compulsion to debunk the satire produced by The Onion, for example. The Bee’s pointed satire often serves the purpose of exposing the Left for its congenital stupidity, but that is anything but an effort to deceive, as much as Snopes might wish it was so.

 

Certainty Laundering and Fake Science News

05 Wednesday Dec 2018

Posted by in Global Warming, Risk, Science

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Intriguing theories regarding all kinds of natural and social phenomena abound, but few if any of those theories can be proven with certainty or even validated at a high level of statistical significance. Yet we constantly see reports in the media about scientific studies purporting to prove one thing or another. Naturally, journalists pounce on interesting stories, and they can hardly be blamed when scientists themselves peddle “findings” that are essentially worthless. Unfortunately, the scientific community is doing little to police this kind of malpractice. And incredible as it seems, even principled scientists can be so taken with their devices that they promote uncertain results with few caveats.

Warren Meyer coined the term “certainty laundering” to describe a common form of scientific malpractice. Observational data is often uncontrolled and/or too thin to test theories with any degree of confidence. What’s a researcher to do in the presence of such great uncertainties? Start with a theoretical model in which X is true by assumption and choose parameter values that seem plausible. In all likelihood, the sparse data that exist cannot be used to reject the model on statistical grounds. The data are therefore “consistent with a model in which X is true”. Dramatic headlines are then within reach. Bingo!

The parallel drawn by Meyer between “certainty laundering” and the concept of money laundering is quite suggestive. The latter is a process by which economic gains from illegal activities are funneled through legal entities in order to conceal their subterranean origins. Certainty laundering is a process that may encompass the design of the research exercise, its documentation, and its promotion in the media. It conceals from attention the noise inherent in the data upon which the theory of X presumably bears.

Another tempting exercise that facilitates certainty laundering is to ask how much a certain outcome would have changed under some counterfactual circumstance, call it Z. For example, while atmospheric CO2 concentration increased by roughly one part per 10,000 (0.01%) over the past 60 years, Z might posit that the change did not take place. Then, given a model that embodies a “plausible” degree of global temperature sensitivity to CO2, one can calculate how different global temperatures would be today under that counterfactual. This creates a juicy but often misleading form of attribution. Meyer refers to this process as a way of “writing history”:

“Most of us are familiar with using computer models to predict the future, but this use of complex models to write history is relatively new. Researchers have begun to use computer models for this sort of retrospective analysis because they struggle to isolate the effect of a single variable … in their observational data.”

These “what-if-instead” exercises generally apply ceteris paribus assumptions inappropriately, presuming the dominant influence of a single variable while ignoring other empirical correlations which might have countervailing effects. The exercise usually culminates in a point estimate of the change “implied” by X, without any mention of possible errors in the estimated sensitivity nor any mention of the possible range of outcomes implied by model uncertainty. In many such cases, the actual model and its parameters have not been validated under strict statistical criteria.

Meyer goes on to describe a climate study from 2011 that was quite blatant about its certainty laundering approach. He provides the following quote from the study:

“These question cannot be answered using observations alone, as the available time series are too short and the data not accurate enough. We therefore used climate model output generated in the ESSENCE project, a collaboration of KNMI and Utrecht University that generated 17 simulations of the climate with the ECHAM5/MPI-OM model to sample the natural variability of the climate system. When compared to the available observations, the model describes the ocean temperature rise and variability well.”

At the time, Meyer wrote the following critique:

“[Note the first and last sentences of this paragraph] First, that there is not sufficiently extensive and accurate observational data to test a hypothesis. BUT, then we will create a model, and this model is validated against this same observational data. Then the model is used to draw all kinds of conclusions about the problem being studied.

This is the clearest, simplest example of certainty laundering I have ever seen. If there is not sufficient data to draw conclusions about how a system operates, then how can there be enough data to validate a computer model which, in code, just embodies a series of hypotheses about how a system operates?”

In “Imprecision and Unsettled Science“, I wrote about the process of calculating global surface temperatures. That process is plagued by poor quality and uncertainties, yet many climate scientists and the media seem completely unaware of these problems. They view global and regional temperature data as infallible, but in reality these aggregated readings should be recognized as point estimates with wide error bands. Those bands imply that the conclusions of any research utilizing aggregate temperature data are subject to tremendous uncertainty. Unfortunately, that fact doesn’t get much play.

As Ashe Schow explains, junk science is nothing new. Successful replication rates of study results in most fields are low, and the increasing domination of funding sources by government tends to promote research efforts supporting the preferred narratives of government bureaucrats.

But perhaps we’re not being fair to the scientists, or most scientists at any rate. One hopes that the vast majority theorize with the legitimate intention of explaining phenomena. The unfortunate truth is that adequate data for testing theories is hard to come by in many fields. Fair enough, but Meyer puts his finger on a bigger problem: One simply cannot count on the media to apply appropriate statistical standards in vetting such reports. Here’s his diagnosis of the problem in the context of the Fourth National Climate Assessment and its estimate of the impact of climate change on wildfires:

“The problem comes further down the food chain:

  1. When the media, and in this case the US government, uses this analysis completely uncritically and without any error bars to pretend at certainty — in this case that half of the recent wildfire damage is due to climate change — that simply does not exist
  2. And when anything that supports the general theory that man-made climate change is catastrophic immediately becomes — without challenge or further analysis — part of the ‘consensus’ and therefore immune from criticism.”

That is a big problem for science and society. A striking point estimate is often presented without adequate emphasis on the degree of noise that surrounds it. Indeed, even given a range of estimates, the top number is almost certain to be stressed more heavily. Unfortunately, the incentives facing researchers and journalists are skewed toward this sort of misplaced emphasis. Scientists and other researchers are not immune to the lure of publicity and the promise of policy influence. Sensational point estimates have additional value if they support an agenda that is of interest to those making decisions about research funding. And journalists, who generally are not qualified to make judgements about the quality of scientific research, are always eager for a good story. Today, the spread of bad science, and bad science journalism, is all the more virulent as it is propagated by social media.

The degree of uncertainty underlying a research result just doesn’t sell, but it is every bit as crucial to policy debate as a point estimate of the effect. Policy decisions have expected costs and benefits, but the costs are often front-loaded and more certain than the hoped-for benefits. Any valid cost-benefit analysis must account for uncertainties, but once a narrative gains steam, this sort of rationality is too often cast to the wind. Cascades in public opinion and political momentum are all too vulnerable to the guiles of certainty laundering. Trends of this kind are difficult to reverse and are especially costly if the laundered conclusions are wrong.

Fraud-Free Voting Fallacy

26 Thursday Jan 2017

Posted by in Democracy, Voter Fraud

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I posted the following on December 1, 2016. It seems timely today. The bottom line: voter fraud is very unlikely to have swung the popular vote in favor of Hillary Clinton, but it is all too common.

Democrats have long asserted that voter fraud is rare. Recently, we heard from them that questioning the results of an election would “undermine democracy”. In fact, voter fraud is routinely characterized by the left as “fake news“, and even worse, as a racist narrative! How convenient. But in the wake of the Donald Trump victory, we’ve been hearing about electronic voter fraud from the same crowd that’s been imagining Ruskiis under their beds for months (to steal a phrase from Glenn Reynolds). Fear not: voting machines are not connected to the internet!

This week, however, Donald Trump stirred the pot once again by tweeting that he would have won the popular vote if not for the “millions” of illegal votes for Hillary Clinton. Hilarity ensued, and not only on the left. All the pundits say that Trump has no data to support his claim. He probably never looked for it, and he probably doesn’t care. As Ed Driscoll notes at Instapundit, perhaps “stray voltage” is simply part of his plan.

Trump’s claim really does sound outrageous, but a review of the recent history of actual and potential election fraud shows that it might not be as radically far-fetched as we’ve been told. DiscovertheNetworks.org (DTN) provides a three-part compilation of voter fraud research and cases spanning the last 30 years. Pertinent detail on each case or finding is provided, and each item is sourced. The cases span the country and include fraudulent voter registration efforts, dead and ineligible voters (including pets) on the rolls, multiple registrations across jurisdictions, homeless voters casting multiple votes, fraudulent absentee ballots, vote buying, voter impersonation, and failure to provide absentee ballots to deployed military personnel. ACORN, by the way, is well-represented on the list.

Many of the cases on DTN’s list involve anywhere from a handful of fraudulent votes to several hundred. Of course, it’s likely that only a small percentage of fraudulent votes are ever detected. But there are cases on the list of fraudulent registrations numbering in the thousands, and counts of ineligible voters appearing on voter rolls numbering in the hundreds of thousands and even millions.

One of the studies cited by DTN was commissioned by The Pew Center on the States, published in 2012. It found that there were 24 million invalid or “significantly inaccurate” voter registrations in the U.S. And just before every election, said the report, election officials are inundated with a flood of new and often questionable registrations.

Another study cited by DTN appeared in the journal Electoral Studies in 2014. It said “… based upon extrapolations from the portion of the sample with a verified vote … 6.4 percent of non-citizens voted in 2008 ….” The authors admit that there are reasons to think 6.4% is an under-estimate. That’s especially true given the focus on immigration policy in this year’s presidential campaign. But if that percentage was repeated in this year’s election, and given 24 million non-citizen residents in the U.S. (legal and illegal), then roughly 1.4 million non-citizen votes would be included to the 2016 popular vote total. The researchers acknowledge that this group tends to vote heavily for democrats. The overlap between these votes and those arising from the other kinds of voter fraud by Pew is certainly not complete, so the fraudulent vote total is likely to be well north of 1.4 million.

The electoral college was designed to discourage voter fraud in states dominated by a single party. Vote margins beyond a simple majority provide no incremental reward in the electoral college, the reasoning goes. That doesn’t mean election fraud doesn’t occur in those states or that it isn’t motivated in part by presidential politics. Moreover, state and local races can still be contested in so-called “one-party” states and may be subject to manipulative efforts. In such cases, presidential votes might well ride on the coattails of candidates for state and local offices.

The recent tide of republican success in congressional races and at the state level does not suggest that election fraud is benefitting democrats in more highly contested states. Perhaps it goes the other way or is roughly balanced between the parties in those states. But most people who believe Trump’s tweet would probably say that fraud must be concentrated in heavily “blue” states like California and New York. If so, it would be unbalanced fraud.

The magnitude of voter fraud in the presidential election is plausibly in the range of 1 – 2 million and it could be even higher based on the research and other information cited above. That total, however, is split between the parties. For the sake of argument, if 2 million fraudulent ballots are cast and republicans garner 30%, or 600,000 fraudulent votes, then the contribution to the democrat vote margin is just 800,000 (1,400,000 – 600,000). Hillary Clinton’s popular vote margin was 2.9 million (less than the margin in California alone). Given that total, Trump’s claim is a real stretch, but his “guess” at the number of fraudulent votes is probably well within an order of magnitude. That might be surprising to some detractors.

What should be obvious is that voter fraud is a major problem in the U.S., and it undoubtedly swings some races at state and local levels. I have been lukewarm with respect to voter ID laws, but I am persuaded that they are a necessary step in the quest for electoral integrity. (Whether IDs must be government-issued is a separate matter.) The argument that these laws are discriminatory is true to the extent that we wish to prevent ineligible individuals from voting. That’s a good thing. The argument that it is racist is sheer stupidity: citizenship should bring privileges. That is not a position on immigration policy. Voter ID laws place a simple burden on citizens to prove that they are legitimately entitled to full participation in the democratic process. If you can’t be troubled to identify yourself, you should expect multiple obstacles to sharing in the fruits of modern society.

Postscript: I just ran across this post, which makes some of the same points I’ve discussed above, but it says that there are roughly 20 million adult non-citizens in the U.S. today.

Fraud-Free Voting Fallacy

01 Thursday Dec 2016

Posted by in Democracy

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Democrats have long asserted that voter fraud is rare. Recently, we heard from them that questioning the results of an election would “undermine democracy”. In fact, voter fraud is routinely characterized by the left as “fake news“, and even worse, as a racist narrative! How convenient. But in the wake of the Donald Trump victory, we’ve been hearing about electronic voter fraud from the same crowd that’s been imagining Ruskiis under their beds for months (to steal a phrase from Glenn Reynolds). Fear not: voting machines are not connected to the internet!

This week, however, Donald Trump stirred the pot once again by tweeting that he would have won the popular vote if not for the “millions” of illegal votes for Hillary Clinton. Hilarity ensued, and not only on the left. All the pundits say that Trump has no data to support his claim. He probably never looked for it, and he probably doesn’t care. As Ed Driscoll notes at Instapundit, perhaps “stray voltage” is simply part of his plan.

Trump’s claim really does sound outrageous, but a review of the recent history of actual and potential election fraud shows that it might not be as radically far-fetched as we’ve been told. DiscovertheNetworks.org (DTN) provides a three-part compilation of voter fraud research and cases spanning the last 30 years. Pertinent detail on each case or finding is provided, and each item is sourced. The cases span the country and include fraudulent voter registration efforts, dead and ineligible voters (including pets) on the rolls, multiple registrations across jurisdictions, homeless voters casting multiple votes, fraudulent absentee ballots, vote buying, voter impersonation, and failure to provide absentee ballots to deployed military personnel. ACORN, by the way, is well-represented on the list.

Many of the cases on DTN’s list involve anywhere from a handful of fraudulent votes to several hundred. Of course, it’s likely that only a small percentage of fraudulent votes are ever detected. But there are cases on the list of fraudulent registrations numbering in the thousands, and counts of ineligible voters appearing on voter rolls numbering in the hundreds of thousands and even millions.

One of the studies cited by DTN was commissioned by The Pew Center on the States, published in 2012. It found that there were 24 million invalid or “significantly inaccurate” voter registrations in the U.S. And just before every election, said the report, election officials are inundated with a flood of new and often questionable registrations.

Another study cited by DTN appeared in the journal Electoral Studies in 2014. It said “… based upon extrapolations from the portion of the sample with a verified vote … 6.4 percent of non-citizens voted in 2008 ….” The authors admit that there are reasons to think 6.4% is an under-estimate. That’s especially true given the focus on immigration policy in this year’s presidential campaign. But if that percentage was repeated in this year’s election, and given 24 million non-citizen residents in the U.S. (legal and illegal), then roughly 1.4 million non-citizen votes would be included to the 2016 popular vote total. The researchers acknowledge that this group tends to vote heavily for democrats. The overlap between these votes and those arising from the other kinds of voter fraud by Pew is certainly not complete, so the fraudulent vote total is likely to be well north of 1.4 million.

The electoral college was designed to discourage voter fraud in states dominated by a single party. Vote margins beyond a simple majority provide no incremental reward in the electoral college, the reasoning goes. That doesn’t mean election fraud doesn’t occur in those states or that it isn’t motivated in part by presidential politics. Moreover, state and local races can still be contested in so-called “one-party” states and may be subject to manipulative efforts. In such cases, presidential votes might well ride on the coattails of candidates for state and local offices.

The recent tide of republican success in congressional races and at the state level does not suggest that election fraud is benefitting democrats in more highly contested states. Perhaps it goes the other way or is roughly balanced between the parties in those states. But most people who believe Trump’s tweet would probably say that fraud must be concentrated in heavily “blue” states like California and New York. If so, it would be unbalanced fraud.

The magnitude of voter fraud in the presidential election is plausibly in the range of 1 – 2 million and it could be even higher based on the research and other information cited above. That total, however, is split between the parties. For the sake of argument, if 2 million fraudulent ballots are cast and republicans garner 30%, or 600,000 fraudulent votes, then the contribution to the democrat vote margin is just 800,000. Hillary Clinton’s popular vote margin was 2.1 million (less than the margin in California alone). Given that total, Trump’s claim is a real stretch, but his “guess” at the number of fraudulent votes is probably well within an order of magnitude. That might be surprising to some detractors.

What should be obvious is that voter fraud is a major problem in the U.S., and it undoubtedly swings some races at state and local levels. I have been lukewarm with respect to voter ID laws, but I am persuaded that they are a necessary step in the quest for electoral integrity. (Whether IDs must be government-issued is a separate matter.) The argument that these laws are discriminatory is true to the extent that we wish to prevent ineligible individuals from voting. That’s a good thing. The argument that it is racist is sheer stupidity: citizenship should bring privileges. That is not a position on immigration policy. Voter ID laws place a simple burden on citizens to prove that they are legitimately entitled to full participation in the democratic process. If you can’t be troubled to identify yourself, you should expect multiple obstacles to sharing in the fruits of modern society.

Postscript: I just ran across this post, which makes some of the same points I’ve discussed above, but it says that there are roughly 20 million adult non-citizens in the U.S. today.

Fake News and Fake Virtue

28 Monday Nov 2016

Posted by in Free Speech, Propaganda

≈ 2 Comments

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Suddenly, since the election, “fake news” has become all the rage. Not that it’s a new phenomenon. All of us have come across it on social media. Most of us think we know it when we see it, and the recent election probably sensitized a great many of us to its cheap seduction. Some of it is satire, some is sincerely-held conspiracy theory, some is cooked-up, milli-penny click bait, and some of it is intended to drive an agenda.

Those forms of “fake news” are only the most obvious. I believe, for example, that the dangers of positively fake news are no greater than those posed by omission or demotion of news. It was rather obvious during the recent election campaign that news networks often ignored important stories that did not favor their own points of view. And since the death of the tyrant Fidel Castro, we’ve heard pronouncements that he was a “great leader” from a variety of sources who should know better; we’ve heard very little from them about his oppressive and murderous regime.

News as reported, and not reported, is often manipulated or mischaracterized to suit particular agendas. Reporters have their sources, and sources usually have agendas and stratagems in mind, which include rewarding reporters to get the coverage they desire. The manipulation even extends to news about science: grant-hungry and media-savvy members of the scientific community, and the pop-science community, know how to leverage it to their advantage.

Given the universal human capacity for bias, Roger Simon asks, only half in jest, whether all news is fake news. You can rely on so-called fact-checkers in an attempt to verify stories you find suspicious, but choose your fact checkers wisely because they are no better than the biases they bring to their duties. Let’s face it: facts are not always as clear-cut as we’d like. Simon makes his advisory on bias in reporting in the context of Mark Zuckerberg’s new-found passion to identify “fake news” and purveyors of “fake news”, and potentially to ban them from Facebook. No doubt his concern stems from accusations from angry Hillary Clinton supporters that Facebook failed to control the flow of “fake news” during the presidential campaign. He wants users to “flag” fake stories, but he knows that won’t always yield definitive conclusions. Simon quotes the Wall Street Journal:

“Facebook is turning to outside groups for help in fact-checking… It is also exploring a product that would label stories as false if they have been flagged as such by third-parties or users, and then show warnings to users who read or share the articles.

‘The problems here are complex, both technically and philosophically,’ [Zuckerberg] wrote. ‘We believe in giving people a voice, which means erring on the side of letting people share what they want whenever possible.’“

Well, that’s a relief! But what kind of chilling effect might be inflicted when the fact priests assign their marks? And what kind of fact-check/flagging escalation might be engendered among users? In the end, users and third-party “authorities” have biases. You can’t take any proscriptive action that will please them all. Better for hosts to keep their fingers off the scale, avoid censorship, and let users please themselves!

Zuckerberg should know better than to think that “facts” are always easily discerned, that “fake” news is solely the province of crank blogs and flakey “new media” organizations, or that “fake news” has any political affiliation. Consider the following examples offered by A. Barton Hinkle at Reason.com:

“The [New York] Times’ record for disseminating agitprop dates back at least to the early 1930s, when Walter Duranty won a Pulitzer for his reporting that denied the existence of famines in Soviet Russia—during a period when millions were dying of starvation.

More recently, The Times has given the nation the Jayson Blair fabrications—which it followed up with the infamous 2004 story, ‘Memos on Bush Are Fake But Accurate, Typist Says.’ It followed that up four years later with a story implying that GOP presidential candidate John McCain had had an affair with a lobbyist. (The lobbyist sued, and reached a settlement with the paper.)

Over the years other pillars of the media also have fallen on their faces. NBC News had to confess that it rigged GM trucks with incendiary devices for an explosive Dateline segment. The Washington Post gave up a Pulitzer after learning that Janet Cooke’s reporting about an 8-year-old heroin addict was false. In 1998 the Cincinnati Enquirer renounced its own series alleging dark doings by the Chiquita banana company. That same year, CNN retracted its story alleging ‘that the U.S. military used nerve gas in a mission to kill American defectors in Laos during the Vietnam War.’ The San Jose Mercury News had to denounce its own series alleging that the CIA was to blame for the crack cocaine epidemic. Rolling Stone just got hit with a big libel judgment for its now-retracted story about a rape at U.Va. And so on.“

Retractions are good, of course, but they aren’t always forthcoming, and they often receive little notice after the big splash of an initial report. The damage cannot be fully undone. Yet no one proposes to censor “the paper of record” or, with the exception of Fox News, the major television networks.

Edward Morrissey, writing at The Week, notes that the Trump election represented such a total breakdown in the accepted political wisdom that the identification of scapegoats was inevitable:

“Over the past week, the consensus Unified Theory from the media is this: Blame fake news. This explanation started with BuzzFeed’s analysis of Facebook over the past three months, which claimed that the top 20 best-performing ‘fake news’ articles got more engagement than the top 20 ‘mainstream news’ stories. …

There are also serious problems with the evidence BuzzFeed presents. As Timothy Carney points out at the Washington Examiner, the “real news” that Silverman uses for comparison are, in many cases, opinion pieces from liberal columnists. The top ‘real’ stories — which BuzzFeed presented in a graphic to compare against the top ‘fake’ stories — consist of four anti-Trump opinion pieces and a racy exposé of Melania Trump’s nude modeling from two decades ago.“

In Reason, Scott Shackford considers a proposed list of “fake news” sources compiled by a communications professor. Shackford says:

“… [Professor] Zimdars’ list is awful. It includes not just fake or parody sites; it includes sites with heavily ideological slants like Breitbart, LewRockwell.com, Liberty Unyielding, and Red State. These are not “fake news” sites. They are blogs that—much like Reason—have a mix of opinion and news content designed to advance a particular point of view. Red State has linked to pieces from Reason on multiple occasions, and years ago I wrote a guest commentary for Breitbart attempting to make a conservative case to support gay marriage recognition.“

Warren Meyer rightfully identifies the “fake news” outrage as an exercise in idealogical speech suppression, much like the left’s cavalier use of the term “hate speech”:

“The reason it is such a dangerous term for free speech is that there is no useful definition of hate speech, meaning that in practice it often comes to mean, ‘confrontational speech that I disagree with.’“

Worries about “fake” news are one thing, but perhaps we should be just as concerned about the “scourge of dumb news“, and the way it often supplants emphasis on more serious developments. Did the fracas over the Hamilton cast’s treatment of Mike Pence distract the media, and the public, from stories about Donald Trump’s potential conflicts of interest around the globe, which broke at about the same time? Here are some other examples of “dumb” news offered by Noah Rothman, the author of the last link:

“Colin Kaepernick, the Black Lives Matter movement, college-age adults devolving into their childlike selves, or pretentious celebrities politicizing otherwise apolitical events; for the right, these and other similar stories masquerade as and suffice for intellectual stimulation and political engagement. The left is similarly plagued by mock controversies. The faces printed on American currency notes, minority representation in film adaptations of comic books, and astrophysicists insensitive enough to announce feats of human engineering while wearing shirts with cartoon depictions of scantily clad women on them. This isn’t politics but, for many, it’s close enough.“

Okay, so what? We all choose news sources we prefer or discern to be reliable, interesting, or entertaining, and that’s wonderful. No one should presume to question the degree to which news and entertainment ought to intersect. I do not want protection from “fake news”, “dumb news”, or any news source that I prefer, least of all from the government. After all, if there is any entity that might wish to “control the narrative” it’s the government, or anyone who stands to gain from it’s power to coerce.