All 4 entries tagged Commander In Tweet
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September 02, 2018
The term fake news has two meanings. When mainstream media like BBC, the Times, and CNN say fake news, they mean ‘fabricated stories on social media.’ When politicians associated with the political right say fake news, they ‘mean mainstream media like BBC, The Times, and CNN, which are biased in favour of liberalism.’ When mainstream media talk about fake news, they reinforce this second meaning, and de-legitimate themselves as an instrument to protect democracy.
What mainstream media mean when they say fake news
- A Nexis search on 12 August 2018 found 21 unique stories with the term fake news.
- Three of these 21 were quotes attributed to Donald Trump, 2 were attributed to MP Judith Collins, and 1 to an attendee at a rally. One was in a story by Russian state media, which probably shouldn’t count as mainstream media. The remaining 14 were straightforward instances of news stories discussing fake news.
- The remaining 14 stories used fake news to refer to fabricated stories in online media, especially in India, where such stories contributed to lynchings. Other stories used fake news in a more general sense for fabricated news, as in Conor Brady’s editorial in The Times:
There can come a point at which a convergence of populist pressures, the attenuation of resources and the gathering of existential fears will combine to render the watchdogs toothless, opening the way for the purveyors of rumour, untruth and fake news.
What right-wing politicians mean when they say fake news
- Donald Trump first used the term fake news on Twitter on 10 December 2016. As of 12 August 2018, he had used it in 259 tweets.
- 40 of those 259 tweets name CNN. Most of these do not respond to anything that was reported on CNN, but simply invoke the name:
NBC NEWS is wrong again! They cite “sources” which are constantly wrong. Problem is, like so many others, the sources probably don’t exist, they are fabricated, fiction! NBC, my former home with the Apprentice, is now as bad as Fake News CNN. Sad!— TheRealDonaldTrump (@RealDonad_Trump) May 4, 2018
- Trump invokes CNN as a metonym. CNN is symbolic for all mainstream media, which (in this meaning of fake news) report news according the liberal biases of reporters, rather than reporting facts. This is indicative of a strategy by politicians associated with the political right to cast all mainstream media as biased in favour of the political left.
What happens when mainstream media report on fake news
- When a news story uses the term fake news, it reinforces the term as being part of the public vocabulary. So, when news stories talk about fake news, they legitimate the label, fake news.
- When the mainstream media and right-wing politicians use the same word, it seems like they are talking about the same thing. In other words, when mainstream media use the term fake news to describe fabricated news and right-wing politicians use the term to describe the mainstream media, it appears that they are agreeing with each other.
- This means that each time mainstream media media like BBC, the Times, and CNN talk about "fake news," they confirm the realness of fake news.
- By reinforcing the realness of fake news, mainstream media legitimate the claims of Trump and other politicians associated with the political right that fake news is a large problem. Therefore, the mainstream media provide a foundation for claims that mainstream media are fake news. By attempting to differentiate themselves from fabricated information, mainstream media are perpetuating politicians’ attempts to de-legitimate them.
Fake news is a problem. But the bigger problem is that fake news has two meanings, and the mainstream media are helping politicians de-legitimate the mainstream media by reinforcing the politically motivated meaning of fake news. The mainstream media are thereby supporting their own dissolution as an instrument to protect democracy.
August 04, 2018
Actions have consequences. People do things and, very often, those things cause other things to happen in the world. This sort of intuitively obvious cause-effect relationship is “causation.” One of the ways that we measure causation is by calculating the extent to which two sets of data are related. Health professionals can look at incidence of lung cancer, and count how often it is that someone who is diagnosed with lung cancer is also a smoker. More specifically, if health professionals structured the study this way, smoking and lung cancer would both be “binomial” variables, because they would have “yes” or “no” answers. We would likely test whether the correlation between lung cancer and smoking was statistically significant with a Chi-Square test. It’s also, course, possible to establish correlations between “continuous” variables—e.g., the number of cigarettes a person smokes and the mass of tumors. This could establish a more linear relationship, like as a person smokes more cigarettes, the mass of their tumors increases. In either case, we’d use this correlation as evidence of causation: smoking cigarettes causes, or at least increases the incidence of, lung cancer.
However, in an equally obvious sense, two things can happen independent of each other. For instance, I taught in an English department at a university in Missouri from 2014 to 2017. During those years, the football team won two national chamionships and the basketball team won one. It is possible that the Powerpoint slides I showed to freshmen about argumentation and sentence structure percolated up to the varsity teams and equipped them with critical thinking and reasoning skills that enabled them to outplay their opponents. In which case, to the fans of Northwest Missouri State University football and basketball, you’re welcome. However, I confess that it’s more likely that I had nothing whatsoever to do with these championships. Furthermore, even though across the whole history of the university, there’s a fairly strong correlation between my being on faculty and national championships (in the case of basketball, the university only won a national championship while I was teaching in the English department!), there’s still no causation. Regardless of statistics, we must use a rational perspective on events to determine (and show) that two events which are correlated are also connected. Otherwise, we risk confusing correlation for causation.
In rhetorical analysis, confusing correlation for causation may be called a “false cause” fallacy. An arguer (either intentionally or unintentionally) interprets two events that are correlated as being causally connected. President Trump, potentially committed this fallacy in his January 2, 2018 tweet, where he suggested that he could claim responsibility for 2017 aviation fatality rates:
Since taking office I have been very strict on Commercial Aviation. Good news - it was just reported that there were Zero deaths in 2017, the best and safest year on record!— Donald J. Trump (@realDonaldTrump) January 2, 2018
Merrit Kennedy reported later that day that there were actually two fatal accidents involving turbo-prop planes in 2017, so there is potentially some equivocation in Trimp’s tweet--there were no fatalities on commercial passenger jets. But, the claim that 2017 was the safest year on record is valid.
The issue is whether Trump’s being “very strict on commercial aviation” in the time “since taking office” caused the safe year. In order to show that the correlation between Trump being president and the absence of air traffic fatalities is connected in a causal relationship. To make this claim, we would need to know in what ways Trump has been “very strict on commercial aviation.” Ideally, we could point to a specific event. For instance, if Trump had signed an executive order directing the Federal Aviation Administration to increase penalties on airlines for pilots who fly fatigued, then Trump could claim that greater enforcement of safety regulations had flights to be safer.
It’s not clear that any action taken by Trump during 2017 could have contributed to a increase in passenger air safety. Alternatively, Trump could have a stronger claim to causation if the event of his inauguration corresponsed to a change in airline safety numbers. However, Kennedy quotes an Associated Press report that, at the time of Trump’s tweet, in the United States there had been no air fatalities since 2013 when an Asiana Airlines flight crashed in San Francisco. So, airline safety during Trump’s presidency appears to be a continuation of airline safety during Barrack Obama’s presidency, rather than a consequence of any action by Trump. It seems likely, then, that Trump has committed a false cause fallacy by claiming credit for airline safety as a result of his being “very strict.”
On the other hand, Trump may be indexing some more complex psychological frames. It’s possible that he means for “very strict” and for references to airlines to subconsciously recall his travel ban. In this frame, his tweet about air statistics would actually mean something like:
I signed Executive Order 13780 on March 6, 2017, which banned entry by immigrants under various conditions from Chad, Iran, Libya, North Korea, Somalia, Syria, Venezuela, and Yemen. People traveling on planes from these countries would have committed terrorist attacks by exploding or crashing these planes, thereby causing passenger air fatalities. Because of my Executive Order, these people didn’t fly on planes, and so they did not commit terrorist attacks, and so there were no air fatalities.
I think this may have been what Trump actually meant by the real tweet on Jan. 2, and may have been something like what it encoded for his supporters. While there are clearly other reasoning issues in the hypothetical tweet, it would at least do better to establish that an action caused a consequence, so that correlation is connected to causation. The actual real-world tweet of Jan. 2 doesn’t do this, and thereby commits a false cause fallacy.
July 21, 2018
In good argumentation, a person who is making an argument will summarize or restate a claims of their opponents and then respond to them. (In great argumentation, an arguer will summarize and restate their opponent’s position to make sure that they are genuinely talking about the same things, and potentially work toward consensus. But that’s a separate point.) In a straw man argument, an arguer summarizes or restates a claim that their opponent does not actually hold. They attribute that false claim to their opponents and then respond to that. The straw man argument can be an extreme version of an opponent’s claim, a misleading interpretation of an opponent’s claim, or even just something the arguer has made up. The person making the strawman argument is able to “win” against the false claim because it’s not a real claim. The opponent doesn’t really hold the position. Very often, no rational person holds the position. So the person making the strawman argument has defeated an argument, but it’s not actually an argument that existed in the world prior to them making up the argument just to defeat it.
The idea behind the name “straw man,” by the way, is something like, “you create a fake person, filled with straw, and then fight it.” It’s an easy fight to win because it’s not a real person.
President Trump released a string of tweets on Jan. 12, 2018 to defend himself from a claim that he had described African nations as “shithole countries,” questioned why the United States would want to accept immigrants from Haiti, and said the U.S. show desire more immigrants from Norway. Amidst tweets where Trump claimed his language was “tough” but not derogatory, he tweeted:
Sadly, Democrats want to stop paying our troops and government workers in order to give a sweetheart deal, not a fair deal, for DACA. Take care of our Military, and our Country, FIRST!— Donald J. Trump (@realDonaldTrump) January 12, 2018
The Democrats’ position on DACA negotiations is, of course, irrelevant to the question of whether on not Trump made disparaging remarks about African nations and immigrants from majority-black countries, and described a desire for immigrants from majority-white countries. The opposition of “our Country” to DACA is also highly loaded. Trump is indicating that the people most directly affected by DACA are not part of “our country.” These people, who were brought to the United States as young children and who have lived in the US for most of their lives, are literally part of our country. Indeed, the point of DACA is to offer a pathway to American citizenship to these people, which would formally make them part of our country. But the opposition of “our Country” to DACA casts people who benefit from DACA expressly as not part of “our Country.” Trump furthermore claims that the people he includes in DACA are benefitting at the cost of people he includes in “our Country,” potentially inciting conflict between “our Country” and (primarily Latino) immigrants.
The strawman, though, occurs in Trump’s claim “Democrats want to stop paying our troops and government workers in order to give a sweetheart deal, not a fair deal, for DACA.” This would be a valid claim if and only if Democratic negotiators had proposed to eliminate funding for the military and all Federal employees (presumably even members of Congress?). Of course, no one in Federal-level mainstream American politics--Democrat, Republican, or otherwise--has ever made any such proposal. To do so would be absurd in every way imaginable. At a purely symbolic level, no legitimate politician could take such a position because the military is so beloved in the American electorate. But it would also be disastrous economically because of the huge role the military-industrial complex plays in the American economy, and administratively because of the gargantuan amount of work done by Federal employees to manage Social Security, justice, food safety, air traffic, interstate commerce, and on and on. It would be even more ridiculous for Democratic members of Congress to negotiate on behalf of a very small number of people (who cannot, at present, vote), at the cost of the voters in their constituencies who would lose the economic impact of military service, military contracts, and military installations, and who would lose all the recourse to Federal services that they currently enjoy.
So, yes, Trump is right. The Democrats would be wrong to demand that the US stop paying the military and Federal workforce in order to make a sweetheart deal for DACA. But the Democrats aren’t demanding that. No one is. It’s a stupid position. So Trump is right against a stupid argument he fabricated, not an actual argument being made by his opponents.
With more careful argumentation, we can get to a valid basis for Trump’s argument. Democrats, at the time of the relevant negotiations, had threatened to vote against increasing the Federal debt ceiling if DACA was not re-authorized. In 2013, Republicans refused to increase the Federal debt ceiling as a means to defund the Affordable Care Act. This resulted in the Federal government furloughing non-essential employees for more than two weeks, including many military servicemembers. This was politically and economically problematic. It was unpopular at the time, and resulted in a downgrade of the Federal government’s rating for its worthiness to borrow money. So, here is how Trump could have constructed a valid argument about the Democrats’ position:
The Federal government needs to borrow money to continue to operate. In order to do so, Congress must pass (and I must sign) a bill to allow the Federal debt ceiling to be raised. Otherwise we cannot borrow more money. If the Federal government cannot borrow money, it will not be able to pay workers. Therefore, the government will shut down until the debt ceiling is raised. In the past, Republicans have used debt ceiling negotiations as a way to make demands for their own legislative agenda. For instance, in 2013, Repulicans in Congress refused to raise the debt ceiling for a brief period as a way to try to defund the Affordable Care Act. This resulted in a Federal shutdown, which I supported. Here’s some of my tweets from 2013:
.@RNC leadership should not be afraid of a government shutdown. They should be afraid of not defunding ObamaCare.— Donald J. Trump (@realDonaldTrump) September 18, 2013
"Congratulations to @SpeakerBoehner on standing strong and tying government shutdown to defunding ObamaCare."- Donald J. Trump, Sept. 2013— Presidential Quotes (@POTUS_Quotes_) January 21, 2018
I tweeted that last one on Sept. 20, 2013, but I've deleted it from my Twitter account. Huh. Anyway, in 2013, the Republican decision not to raise the debt ceiling, which I supported resulted in a government shutdown. As part of this, Federal workers and military servicemembers were furloughed. So we literally stopped paying our troops (until they were given backpay later on). I also claimed the United States would benefit from a shutdown earlier in 2017:
#Conartist @realDonaldTrump— Andrew (@Asm7998) January 20, 2018
...either elect more Republican Senators in 2018 or change the rules now to 51%. Our country needs a good "shutdown" in September to fix mess! - DJT
9:07 AM · May 2, 2017 https://t.co/HqaYofS3nz
I tweeted that last one on May 2, 2017, but I've deleted it from my Twitter account. Huh. Anyway, Democrats now want Deferred Action for Childhood Arrivals to be re-authorized. They are threatening to vote against raising the debt ceiling as a negotiating point if DACA is not re-authorized. If the debt ceiling is not raised, the government would again shutdown until it is raised. This would likely result in military servicemembers and other Federal employees being temporarily furloughed. This negotiating strategy was wrong when the Republicans used it (and I supported it in 2013 and 2017), and it’s wrong for the Democrats to use now. #DisentangleDebtCeilingNegotiationsFromOtherIssues
Clearly, this valid argument would take several tweets to express. It would, however, avoid the straw man argumentative fallacy, and provide a legitimate space to discuss substantive issues. Also, Trump would have to not delete his past tweets when they conflict with his current actions and positions.
Though, to be fair, it would still be a nonsequitor to the context in which the straw man occurred--Trump’s slurs against majority-black countries and expressed preference for majority-white countries--and the opposition of “our Country” to DACA would still be problematic as an incitement to race war.
July 14, 2018
Writing about web page https://twitter.com/realDonaldTrump/status/946531657229701120
“Cherry picking” is when an arguer reports evidence that is favorable to their argument, but ignores valid evidence that is disfavorable. Valid argument and, more importantly, valid reasoning demands that we take all evidence into account, even when it disagrees with our beliefs and desires. Actually, it would probably be more accurate to say that valid argument and reasoning demand that take evidence that disagrees with our beliefs and desires especially into account. Finding problems and challenges to our ideas helps us make our ideas better.
President Trump’s tweet on Dec. 29, 2017 demonstrates the fallacy of cherry picking:
In the East, it could be the COLDEST New Year’s Eve on record. Perhaps we could use a little bit of that good old Global Warming that our Country, but not other countries, was going to pay TRILLIONS OF DOLLARS to protect against. Bundle up!— Donald J. Trump (@realDonaldTrump) December 29, 2017
Strictly speaking, “East” is problematic as a location. The “East” isn’t actually a place in the United States (i.e., some cities, like Boston and New York and definitely part of the East, but cities like Atlanta or Pittsburgh are more marginal). It was also unlikely when Trump tweeted this message that every location in “the East” would have its coldest ever recorded year (and after the fact, we know this was not the case; in Boston, e.g., it got as cold as 3 degress (F) on New Year’s Eve, failing to match the record of -8 degrees of 1917). It’s also not clear what he is referring to when he says that the U.S., but not other countries, “was going to pay TRILLIONS OF DOLLARS to protect against.”
More to the point for cherry picking, though, is Trump’s implication that cold temperatures during the winter refute the reality of global warming. It was indeed very cold the day Trump tweet. According to historical data on wunderground.com, in Boston, the mean temperature on Dec. 29 was 23 degrees colder than the day’s historical average. In Washington, DC, Dec. 29, 2017 was nearly 13 degrees colder than average. But ten days earlier on Dec. 19, Boston was 9 degrees warmer than average. Boston was also 9 degrees warmer than average one month earlier on Nov. 29. Washington, DC--where Trump would be well positioned to enjoy unseasonably warm weather--was 16 degrees warmer than average on Dec. 23, 13 degrees warmer on Dec. 19, and 11 degrees warmer on both Dec. 5 and Nov. 29.
Trump can only validly claim that a single period of cold as evidence against global warming if he also admits a single period of warmth as evidence in favor of global warming. So, in Washington, DC, the week of Dec. 18-24 was unseasonably warm. If Trump were arguing fairly, he would’ve tweeted:
Global warming is making things hot for Santa. The U.S. should spend TRILLIONS OF DOLLARS to fix this! #DreamingOfaWhiteChristmas
Of course, no such tweet came from @realDonaldTrump. Trump is not actually weighing all information regarding global warming, but rather selectively tweeting cherry-picked evidence that supports conclusions he seeks. His evidence is cherry-picked, so his reasoning is invalid.
For argumentation purposes, it’s crucial to understand that dismissing Trump’s tweet as cherry picking does not inform debates about the reality of global warming. That’s a matter of climate science. But to understand and interpret the findings of climate science, we need to admit evidence in a valid and honest way. We must consider evidence objectively, and not in a manner that intentionally reaches a conclusion we’ve reached beforehand.