Ideology

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How do Latinos for Trump Look Like? (Updated)

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Although you won’t find a single word about Latinos for Trump in some quarters of the internet if your life depended on it, a part of the American media seems to have realised – shock! horror! – that not all Latinos look like Speedy González.

Yes, dear identitarian Leftists in the US and Australia: not all Latinos felt insulted when the Pussy Grabber in Chief called illegal immigrants rapists, nor did they all support the Black Lives Matter protests or see themselves as targets of racism; not all Latinos want minimum wages, for these Latinos aren’t working poor. Not all Latinos oppose American imperialism in America’s back yard.

Some Latinos learned the rules of the game in liberal democracies. They are savvy enough to organise themselves politically and are not beyond stocking fears in the public, fears they ultimately know are unfounded.

How prevalent are those surprisingly “atypical” Latinos? Frankly, I have no idea. I think there isn’t any reliable data, is there? But the knee-jerk reaction some pundits have when asked that question (i.e. that’s only Cubans or Venezuelans) is reckless.

How about Asians, or even blacks? And what if the Republicans decide to court those atypical POCs? For that matter, how about feminists and LGB+ people?

Eric Hobsbawm, of all people, saw that identity groups are for themselves, something identitarian Leftists appear blind to. Allies are not necessarily friends. Coalitions shift.

Even if the Dems make it past the 270 Electoral College votes, the disappointing results of the US elections will prompt the customary blaming exercise. The expected “blue wave” failed to materialise. Someone, other than themselves, will have to carry the guilt and Homer Simpson and Cletus the Slack-Jawed Yokel are by far the most convenient scapegoats, for no longer the identitarian Leftists remember Tom Joad: it’s politically correct to demonise the “(white) working class”; nobody will come to their defence and you can even feel good about yourself for doing that.

I am tired of that.

UPDATE:

06/11/2020. Basing himself on the Edison Exit Poll, Matt Bruenig says that “Trump did better in 2020 with every race and gender except white men.”

The peculiar circumstances of these elections (abnormally large number of early and mail-in voters plus the COVID19 restrictions) may have affected those results. Additionally, Bruenig didn’t report the margins of error.

Still, that’s the data we have. If we believe them, pretty much every single oppressed identity swung towards racist, xenophobic, misogynistic Trump.

Will the “(white) working class” – by which it’s normally meant “male blue collar workers” – never learn?

Ideological Tunnel Vision

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I rarely write about partisan politics on this blog. Today, though, I’ll make an exception. As the spectre of a second Trump term remains possible, here are some thoughts on the US election.

Avoiding democracy

A second Trump term is possible largely because the US electoral system is designed to avoid democracy. To be fair to the US, though, many of the world’s democracies have similar features.

In many democracies, government power is decided not in terms of the popular vote, but in terms of subregion plurality. Whoever wins a plurality of votes in a given district gets all the government representation (in the district). The result, often, is that government power has little to do with popular sentiment and more to do with the quirks of regional differences.

The US electoral college is just one example of this backwards system, though one that is admittedly bizarre. The electoral college creates a two-step process for electing presidents. Voters in each state technically vote for ‘electors’, and these ‘electors’ then vote for the president. The catch is that electors in each state are allotted by plurality. Whoever gets the most votes gets all the state’s electors. As Trump’s 2016 win (and Bush’s 2000 win before him) shows, this means that a candidate can win the election with a minority of votes.

The electoral college is uniquely bizarre only because state ‘electors’ are purely symbolic. They have no role after the election. But in all other ways, the electoral college is similar to the first-past-the-post system found in many democracies. This system often leads to minority rule.

In Canada, for instance, we suffered through a decade of rule by Stephen Harper. Throughout his time in power, Harper was disapproved of by the majority of Canadians. Yet he won three elections. How? Two reasons. First, Harper’s disapproval was spread out across the whole country. His approval, in contrast, was concentrated in the West. Second, the progressive vote (against Harper) was split between 4 parties, while the conservative vote (for Harper) was consolidated in a single party.

Interestingly, Stephan Harper eventually lost power to a party that promised to implement proportional representation. But once in power, it decide not to. It was a clever bait-and-switch that many keen observers saw coming.

Back to the US. With its state-biased senate and electoral college system, the US merely takes the problems of non-proportional representation farther than other democracies.

The ideological landscape

Much has already been said about the anti-democratic nature of the US electoral college. What gets less attention, though, is that a huge chunk of the US population still voted for Trump. To observers outside the country, this fact is inexplicable. How can Trump — with his incessant lying and near-criminal ineptness — possibly get so many votes?

This points to the importance of ideology. In ideological terms, the US is an outlier. Its devotion to free-market fundamentalism is extreme. If you live outside the US, you already know this. But what’s interesting is that many Americans have no idea that their country is such an outlier. They have ideological tunnel vision.

Many working class Americans simply can’t imagine having paid sick days, paid maternity leave, or paid vacation. And yet outside of the US, this is the norm. And then there’s healthcare. In no other industrialized country is healthcare so expensive and the outcomes so poor. And yet many Americans simply can’t imagine having free healthcare for all.

What’s at play here is the power of ideology. You can only see this power when you’re outside of it. The absurdity of feudal caste systems, for instance, is obvious to all modern observers. But given the ubiquity of such systems in the past, this absurdity is evidently not obvious to those inside the system.

The same is true for any ideology. When you’re surrounded by it, you can’t see it. I speak from experience. I lived in Texas for 4 years. When I first arrived (from Canada), what struck me was the oppressive media landscape. In the corporate media, the range of expressible opinion was tiny. I only noticed this because the US ‘Overton window’ was much smaller than in Canada. But over time, I forgot. The US media landscape became the new norm. I only (re)realized how oppressive it was when I started reading Noam Chomsky.

Free market ideology

The US is a good example of what happens when free-market ideology runs rampant. Talk about power is framed in terms of ‘freedom’. And corporate power is framed as ‘efficient’ and even ‘democratic’ (you vote with your money). Government power, in contrast, is framed as wasteful and corrupt (counting votes even gets called ‘stealing the election’).

To the outsider, this ideological landscape is bizarre — it’s right up there with the divine right of kings. And yet many Americans have evidently been hoodwinked.

If Trump does win a second term, there will be much soul searching on the left. Many people will blame the electoral system. Fewer will blame free-market ideology. But the fact is that both are to blame. And both are frustratingly hard to change.

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Deconstructing Econospeak

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It’s been 20 years, but I still remember the feeling. It was a mix of curiosity and unease. I was curious because I was learning something new. But I was uneasy because something didn’t sit right. The place was Edmonton, Alberta, circa the year 2000. The situation? My first encounter with economics: Econ 101.

Interestingly, I can’t remember much of the course content. Instead, what I remember is the feeling. As I grappled with the language spoken by the economics textbook (what I’m calling econospeak), I felt that something was missing. But I couldn’t put my finger on what … and I was too busy to think much about it. So I ignored the feeling, memorized the course content, and moved on.

Today I’m a PhD-trained political economist and I know why I had a bad feeling in Economics 101. It’s because the course wasn’t teaching me about the real world. It was indoctrinating me in an ideology.

I’ve spent much of the last decade trying to understand this ideology. A key part of its appeal, I believe is the language that it uses. Of course, many people recognize that the language of econospeak is part of its ideological potency. And many people have analyzed this language. But what nobody has done (as far as I can tell) is to quantitatively deconstruct econospeak. That’s what I’m going to do here.

I’ve created a word-counting bot that compares the language found in economics textbooks to the English language at large. I’m going to use this bot to analyze econospeak. The results (which I’m only beginning to unwrap) are fascinating. Let’s dive in.

A word-counting bot

Before we get to the specifics of my word-counting bot, I’ll give it some context.

When someone asks you to ‘think critically’ about a text, they want you to compare what the author has said (or not said) to what other people have said. Here’s an example. When I read an economics textbook and see the words ‘rational utility maximizer’, I think of Thorstein Veblen’s phrase ‘homogenous globules of desire’ — a satire of the utility maximizing human. I also think of the novels I’ve read, and how the characters are filled with emotions — emotions that are absent from economics textbooks. In short, I compare the words in the economics textbook to everything else I’ve read.

This example illustrates why critical reading is difficult. To read critically, you have to read widely. The problem, though, is that there’s too much to read — far more than any human could digest. And that’s got me thinking. Is there a way to automate the act of critical reading?

Enter my word-counting bot. No, my bot is not an AI literary critic. It’s far simpler. My bot counts words. The idea is that the words you use (or don’t use) tell us about what you’re thinking. To ‘read critically’, we compare your vocabulary to the vocabulary of other people. We see how frequently you use certain words relative to everyone else. If, for instance, you have sex on your mind, you’ll likely use the word ‘sex’ more than other people. And conversely, you might use the word ‘love’ less than everyone else.

When we (as humans) read a text, we get an intuitive sense for what’s there and what’s not. But my word-counting bot can take this a step further. It can quantify word frequency … and it can do it on a massive scale.

Now let’s get to the specifics. My word-counting bot takes a sample of writing and quantifies the frequency of each word found in the text. It then compares this frequency to what’s found in the English language at large. The bot returns the ratio of the two frequencies — what I’m calling relative word frequency:

$\displaystyle \text{relative word frequency} = \frac{\text{word frequency in sample text}}{\text{word frequency in English}}$

The bot can take any sample of text as an input. Here, I feed it undergraduate economics textbooks. From Library Genesis, I’ve downloaded 43 economics textbooks that are standard fare in economics pedagogy. (Details here.) I’ve fed these books to my bot, and it spits out the frequency of each word in the text.

To measure ‘word frequency in English’ I’ve used data from the Google books database. According to Google, this database is the world’s largest repository of full-text books. Conveniently, Google has created the Ngrams database, which reports word frequency in its books corpus. I use word frequency in the Ngram database (which I’m calling the ‘Google English corpus’) to represent ‘word frequency in English’. I will revert, at times, to calling this Google sample ‘average English’. That doesn’t mean it’s what the ‘average person’ speaks. It’s the average of a huge sample of English text.

To summarize, my word-counting bot eats economics textbooks and spits out relative word frequency, defined as:

$\displaystyle \text{relative word frequency} = \frac{\text{word frequency in economics textbooks}}{\text{word frequency in Google English corpus}}$

In my sample of economics textbooks, there are about 34,000 unique words. My bot calculates relative frequency for all of them. But before we look at the whole output, let’s get a feel for the data. Table 1 shows the frequencies of four words found in the textbook sample.

Table 1: Examples of relative word frequency

Word
Frequency in economics textbooks*
Relative frequency

price
13900
296
46.9

science
105
377
0.277

murder
3.65
81.8
0.0446

ditchdigger
0.13
0.015
8.71

* Frequency = occurrence per million words

The first thing to notice is that word frequency varies wildly. Economics textbooks use the word ‘price’ about 100,000 times more than they use the word ‘ditchdigger’. Now, for these specific words that frequency difference isn’t surprising. But the wild variation in word frequency is actually a feature of language in general. Some words (like ‘and’) get used a lot. Other words (like ‘mesonemertini’) are so rare that you’ve never heard of them.

This huge variation in word use is why looking at the absolute frequency of words in economics textbooks isn’t very useful. What matters is not absolute frequency, but relative frequency — word use relative to the average. And this relative frequency, it turns out, is not necessarily related to absolute frequency.

Table 1 illustrates this fact. Economists use the word ‘price’ a lot. And as you’d expect, they use it more than average — about 40 times more. Conversely, economists almost never use the word ‘ditchdigger’. You’d have to read about 10 million words of econospeak to see ‘ditchdigger’ once. And yet economists use the word ‘ditchdigger’ 9 times more than average. So even though ‘price’ and ‘ditchdigger’ have wildly different absolute frequencies, both are overused by economists.

Let’s continue. Economics textbooks use the word ‘science’ far more than the word ‘ditchdigger’. Yet it turns out that they’re using ‘science’ less than average. (Given economics’ pseudoscience state, I can’t help but laugh at this result.) And what about ‘murder’? Economics textbooks use it about 30 times more than ‘ditchdigger’. But this constitutes underuse. Economists use the word ‘murder’ 20 times less than average.

What’s important here is that a word’s absolute frequency (in economics textbooks) doesn’t predict its relative frequency. We’ll return to this fact later.

Now that you understand what my word-counting bot does, let’s dive into the data.

The ‘shape’ of econospeak

When we analyze language, most people are interested in the specific words that are used. (I will get to specific words, don’t worry.) The problem, though, is that my bot returns data for about 34,000 words. That’s far too many words to discuss individually. But what we can do is look at the ‘shape’ of these words. I’m calling this the ‘shape’ of econospeak.

I’ve plotted this shape in Figure 1. Here I show the distribution of relative word frequency in economics textbooks. The horizontal axis shows the ratio of textbook frequency to Google frequency. (Note that I’ve used a log scale, so each tick mark indicates a factor of 10). The vertical axis shows ‘word density’ — the portion of words with the given relative frequency.

Figure 1: The distribution of relative word frequency in economics textbooks. Here’s a histogram of relative word frequency in my sample of economics textbooks (plotted on a log scale). The vertical red line indicates ‘frequency parity’, which means that the given word has the same frequency in both the economic textbooks and the Google corpus. I’ve used color to show the most overused and underused words. [Sources and methods].

Let’s dissect this ‘shape’ of econospeak. We’ll start with the vertical red line that I call ‘frequency parity’. This line indicates that a word occurs at the same frequency in economics textbooks as it does in the Google corpus. (Its relative frequency is 1.) If the vocabulary in economics textbooks was identical to the vocabulary in the Google corpus, the distribution in Figure 1 would clump around the red line. But it doesn’t. That tells us that econospeak is different than average English. Hardly surprising.

Let’s talk about how econospeak is different. Notice that the peak of the econospeak distribution is to the left of frequency parity. That’s interesting. It suggests that economics textbooks use a large portion of English words less than average. I honestly didn’t expect this result, and am still trying to interpret it.

Here are two possibilities. First, the underuse of common English words could be a defining feature of econospeak. Alternatively, this underuse could be a feature of any branch of specialized writing. Either way, though, the result is important. It suggests that a key feature of econospeak is its underuse of a large chunk of the English language.

Let’s move on to the extremes of econospeak — the words that are most overused and most underused (relative to average English). These words live in the tails of the relative frequency distribution (shown in color in Figure 1). Notice that these tails are true extremes. In econospeak, some words are used 1000 times more than average. And other words are used 1000 times less than average.

I know you want to see these words. But before we get there, we need to do some statistics. Whenever we do empirical work, we need to make sure that our results aren’t caused by chance. We don’t want to get fooled by randomness. (Hat tip to Nassim Nicholas Taleb for this phrase). With randomness in mind, consider a thought experiment. Suppose that my econospeak data is actually a random sample of words taken from the Google English corpus. If this were true, what would the distribution of relative word frequency look like?

In statistics, this thought experiment is called the ‘null hypothesis’. To test the null hypothesis, we randomly draw words from the Google corpus and compare the result to our econospeak data. Figure 2 shows this comparison. Here, I’ve taken a random sample of 7.7 million words (the size of my econospeak sample) from the Google English corpus. For each randomly drawn word, I’ve calculated its frequency relative to the entire Google corpus. The red curve shows the resulting distribution of relative word frequency.

Figure 2: The distribution of relative word frequency — econospeak vs. the null hypothesis. The blue histogram shows the distribution of relative word frequency in economics textbooks — the same data as in Figure 1. The red distribution is the ‘null hypothesis’ — what happens when we randomly draw 7.7 million words from the Google English corpus. [Sources and methods].

Let’s dissect this result. The null hypothesis has a huge peak around frequency parity. That means that most words in our random sample occur at the same frequency as in the Google corpus. That’s unsurprising. (We are, after all, sampling from the Google corpus.) What is surprising, though, is that our random sample produces about the same number of overused words as found in econospeak. To see this fact, look at the right tails of the distributions in Figure 2. The right tail of the null hypothesis is similar to the right tail of the econospeak distribution. Does this similarity mean that economists are randomly overusing words? Yes and no. As you’ll see shortly, there’s more to the story.

What’s most important, in Figure 2, is not word overuse, but word underuse. Looking at the two distributions, we see that the left tail of the econospeak distribution far outreaches the left tail of the random sample. This tells us that econospeak’s underuse of many English words cannot be due to chance.

This result is fascinating, and I’ll return to it throughout the post. It suggests that econospeak is defined not by what it says, but by what it doesn’t say.

The most overused and underused words in econospeak

Now that we’ve looked at the ‘shape’ of econospeak, let’s get more concrete. Let’s look at the words that economics textbooks most overuse and most underuse. The results will surprise you.

We’ll start with the words that economics textbooks most overuse relative to average English. Figure 3 shows these words in a cloud. The larger the font, the more the word is overused.

Figure 3: The most overused words in econospeak. Here’s a wordcloud where font size indicates relative word frequency in economics textbooks. The larger the font, the more the word is overused. [Sources and methods].

If you’ve ever read an economics textbook, the words in Figure 3 are not what you’d expect. You’d think that the most overused words would be economics jargon — terms like ‘supply’, ‘demand’ and ‘market’. And yet this jargon is nowhere to be found. Instead, Figure 3 shows a collection of bizarre words. (‘Grasshopperish’ … seriously?) What’s going on here?

I’ll be honest. I didn’t anticipate that the most overused words in econospeak would be oddballs. But I understand (now) how it happens. Our intuition is that we overuse words by writing them many times. But this is only one path to overuse. The other path is to pick an extremely rare word and use it a few times. It’s this other path to overuse that explains why Figure 3 is filled with oddballs.

Take the word ‘outtell’. In the Google corpus, it appears once every 10 billion words. That’s so rare that you’d likely not see it in a lifetime of reading. The word ‘outtell’ is also rare in econospeak. It occurs just 4 times in my sample of textbooks. But that’s enough to constitute massive overuse. The same is true for many of the words in Figure 3. They’re rare words that got used a few times by economists.

Not all the words in Figure 3, however, are oddballs. Some of them are recognizable jargon (for instance, ‘loanable’, ‘monopolist’ and ‘oligopoly’). How do we distinguish this jargon from the quirks? We’ll get there shortly.

First, though, let’s look at the most underused words in econospeak. Figure 4 shows these words. Here, a larger font indicates that the word is more underused.

Figure 4: The most underused words in econospeak. Here’s a wordcloud where font size indicates the inverse of relative word frequency. The larger the font, the more the word is underused relative to the Google English corpus. [Sources and methods].

I could write an essay about the words in Figure 4. But I have other results to show you, so I’ll reflect on just a few of the words.

First, it seems that econospeak underuses many religious words (for instance, ‘jewish’, ‘jesus’, ‘god’, ‘gospel’, ‘islam’, ‘ritual’, etc.). This underuse is in some ways banal. We can think of English writing as having two sides — a secular side and a religious side. Secular writing will tend to underuse religious words. And religious writing will tend to underuse secular words. So what we’re seeing, in Figure 4, is that econospeak is secular. That’s no surprise.

Economics textbooks, however, are a very particular type of secular writing. They’re promoting a secular ideology. And that makes economists’ underuse of religious words more interesting. Framed this way, we can think of Figure 4 as showing two contrasting ideologies. The secular ideology of economics largely excludes the language used by religious ideologies. Fascinating.

Let’s move on to another important result. The most underused word in econospeak is … drum roll please … ‘anti’!

I didn’t expect this result. (Did you?) But I’ve had a few weeks to think about it, and I’ve realized that it’s quite revealing. Here’s why. The word ‘anti’ offers a succinct way of saying you’re opposed to something. As in:

Bob is anti slavery.

The near total absence of this word in economics textbooks speaks volumes about economics ideology. If you talk in econospeak, it’s difficult to voice opposition. That’s because economists frame opinions in terms of ‘preferences’. As in:

Bob has a preference for Cheerios.

Such banal opinions litter economic textbooks. What about more serious opinions? If you talk like an economist, it’s easy to voice support for something. For instance:

Bob has a preference for slavery.

But how do you use the language of ‘preferences’ to voice opposition? You must resort to a torturous double negative:

Bob has a preference for not having slavery.

Such indirect language, you’ll notice, defangs Bob’s opposition. Compare the turgid sentence above to the simple alternative:

Bob is anti slavery.

Now Bob’s opposition is clear. And that’s why it’s so revealing that econospeak almost never uses the word ‘anti’. Economic textbooks are selling an ideology that legitimizes the status quo. And the best way to do that is to mute any talk of opposition. Purge ‘anti’ from your vocabulary.

Now that we’ve looked at the most overused and underused words in econospeak, let’s look again at the big picture. The most overused words tended to be oddballs (Figure 3). How do we separate these quirks from more common economic jargon?

Figure 5 shows one way to do so. Here I’ve divided econospeak into four quadrants. Before we talk about each quadrant, let’s discuss the whole chart. In Figure 5, each point is a word. The horizontal axis shows the word’s frequency in economics textbooks. The vertical axis shows the word’s frequency relative to the Google corpus.

Figure 5: Quadrants of econospeak. In this plot, each point is a word. The horizontal axis shows frequency in economics textbooks. The vertical axis shows the word’s frequency relative to the Google corpus. [Sources and methods].

Now to the quadrants. What’s important about the quadrants is that they identify different types of overuse and underuse. ‘Quirks’ and ‘jargon’ are both overused relative to the Google corpus. But they take different paths. ‘Jargon’ is used frequently in economic textbooks. But ‘quirks’ appear rarely. (I’ve used 50 occurrences per million words as the dividing line between quirks and jargon.)

Let’s start with ‘jargon’. You can see, in Figure 5, that the ‘jargon’ quadrant contains familiar words like ‘price’, ‘market’ and ‘demand’. These are among the most common words in econospeak. And they’re overused relative to the Google corpus. That’s not surprising.

Now to the ‘quirks’ quadrant. This is where the oddballs live. Sure, there are some jargony words here (like nonmonopolistic). But the further left we go, the odder the words become (i.e. ‘cumquat’). These quirks are rare in economics textbooks, and yet still overused relative to the Google corpus.

Now to the different types of underuse. The ‘under-represented’ quadrant contains words that are used frequently in economics textbooks, but are still under-represented relative to the Google corpus. Here you’ll find many words related to social groups and human institutions. (More on this later.)

Last, we have the ‘neglected’ quadrant. These are words that economists use rarely. But unlike ‘quirks’ (which are rare outside of economics), ‘neglected’ words are common in average English. So in the ‘neglected’ quadrant, we find words that are massively underused. This quadrant is a goldmine for economics critics. If something is missing from economic theory, its vocabulary is probably in the ‘neglected’ quadrant.

I know you want to see more of the words in each quadrant. (Skip ahead if you’d like.) But first we need to do more statistics. Let’s again compare econospeak to the ‘null hypothesis’. The null hypothesis, to remind you, is what happens when we randomly draw words from the Google corpus. Figure 6 shows how econospeak stacks up against this random sample. Again, each point is a word. Blue points are econospeak. Red points are the null hypothesis.

Figure 6: Econospeak vs. the null hypothesis, plotted on quadrants. Here I’ve replotted the econospeak data from Figure 5 (blue dots). I’ve added data for the ‘null hypothesis’ (red dots). The null hypothesis, to remind you, is what happens when we randomly drew 7.7 million words from the Google English corpus. [Sources and methods].

Here’s what the null hypothesis tells us. Many econospeak ‘quirks’, it seems, can be chalked up to chance. We know this because in the ‘quirks’ quadrant, many of the red dots (the null hypothesis) overlap blue dots (econospeak). This means we shouldn’t make too much of economists’ overuse of words like ‘cumquat’ and ‘decafs’. It’s probably just a matter of chance.

What’s important, though, is that all the other forms of overuse/underuse cannot be caused by chance. The null hypothesis does not create jargon. Nor does it create under-represented words, or extremely neglected ones. So in statistical terms, econospeak is significantly different than average English. Of course, if you’ve ever read an economics textbook, you already knew that. But here’s a quantification of your intuition.

Econospeak Jargon

Let’s get concrete again and talk about actual econospeak words. Figure 7 shows the top econospeak jargon. These are the words in the ‘jargon’ quadrant that are the most overused relative to average English. There aren’t many surprises here — just typical econospeak jargon.

Figure 7: Econospeak jargon. Here’s a wordcloud of the top ‘jargon’ found in economics textbooks. The larger the font, the more the word is used relative to the Google English corpus. [Sources and methods].

Let’s use some of this jargon to make a paragraph of econospeak:

The loanable funds staved off deadweight losses, brought on by firms acting monopolistically. Demanders, however, were not aware of the diseconomies of scale that caused recessionary trends away from equilibrium. But microeconomists knew that, ceteris paribus, prices were not respecting mpl or mpc. So they ate bushels of inelastic pizza.

(jargon in bold)

OK, you’re unlikely to find such turgid writing in an undergraduate economics textbook. But this sentence is a fitting parody of the neoclassical economics literature. To the outsider, it’s incomprehensible gibberish. Actually, neoclassical economics is gibberish. The point of the jargon is to stop you from figuring that out.

Econospeak Quirks

Now to the top econospeak ‘quirks’, shown in Figure 8. These are words that economists use rarely, but still overuse relative to average English. Here, a larger font means that the word is more overused.

Figure 8: Econospeak quirks. Here’s a wordcloud of the top quirks found in economics textbooks. Font size indicates the inverse of relative word frequency. The larger the font, the more the word is underused relative to the Google English corpus. [Sources and methods].

Unlike ‘jargon’, ‘quirks’ don’t jump out when you read economics literature. In fact, many of them are unique to a single textbook — they’re a quirk of a particular author. Lots of quirks result from non-hyphenation of usually hyphenated words. Some quirks may be typos. And a few of them, I’ll admit, could be an artifact of my word-counting bot. To analyze the textbooks, the bot converts PDF files to text files. The conversion isn’t perfect, and can introduce random errors. These show up in the ‘quirks’ quadrant.

Of the four quadrants of econospeak, ‘quirks’ are the least important, so I won’t analyze them much. Still, let’s try out a quirky paragraph:

Despite their grasshopperish legs, the superathletes tended to be homebodies. Their frontierlike, nondepreciating overdiscounting led to an underofficial refrainer.

(quirks in bold)

This paragraph has the flavor of econospeak. But the quirks are mostly just oddballs. I won’t pay much attention to them here.

Under-represented in econospeak

Now we’re getting to the meat of the analysis. What’s most interesting about econospeak is not what it includes, but what it excludes. Economics textbooks underuse a large portion of the English language. Let’s have a look at this underuse.

We’ll start with the ‘under-represented’ quadrant. These are words that are used frequently in economics textbooks, but still less than in average English. Figure 9 shows the most under-represented words. Here, a larger font indicates more underuse.

Figure 9: Under-represented words in econospeak. Here’s a wordcloud of ‘under-represented’ words found in economics textbooks. Font size indicates the inverse of relative word frequency. The larger the font, the more the word is underused relative to the Google English corpus. [Sources and methods].

Let’s write a sentence with some of these words. Unlike before, though, this sentence won’t be a parody of what economists say. It will capture what they don’t say. Here’s try number one:

Before his death, the man went to court. His child asked about the fire … but he looked away. Hope had no purpose.

(under-represented words in bold)

This is a sentence you’d expect in a novel. It’s personal. It deals with a life or death situation. And it has emotion. These are things that econospeak tends to exclude.

Here’s try number two:

The woman’s status in the committee was a matter of history. The commission on professional organizations had decided that evidence-based administration was essential.

(under-represented words in bold)

This sentence picks out bureaucratic language. The fact that such talk is under-represented in economics is telling. Economists pays attention to competition between groups, but not to the bureaucratic dynamics within groups.

Neglected by econospeak

Let’s now look at words that are neglected by econospeak. These are words that economists almost never use — and this rarity constitutes massive underuse relative to average English. Figure 10 shows the most neglected words. The larger the font, the more the word is neglected.

Figure 10: Neglected words in econospeak Here’s a wordcloud of the most ‘neglected’ words found in economics textbooks. Font size indicates the inverse of relative word frequency. The larger the font, the more the word is underused relative to the Google English corpus. [Sources and methods].

I’ll try my hand at a paragraph with these words:

The Jewish man was anti Islam. He believed he was God’s servant. His submission to the scriptures was based on his counselor’s teachings. God was his commander and savior. This was his eternal ritual.

(neglected words in bold)

What we get, when we use these neglected words, is religous speak. If we treat mainstream economics as a science, then this result isn’t very surprising. It would be astonishing to find a science textbook that read like the Bible. But mainstream economics is not a science. It is an ideology. And so the fact that this ideology neglects religion is important. It highlights that there are two competing ideologies here.

There are many other neglected words (in Figure 10) worth discussing. But I have more results to show you, so onward.

The purpose of an ideology is, in large part, to legitimize the powers that be. In this regard, the ideology of economics is a bit odd.

Most ideologies legitimize power explicitly. They effectively say ‘this person is powerful, and you should obey their command’. Take, as an example, feudal ideology (i.e. religion). Feudal rulers boasted openly about their power, proclaiming that it stemmed from God. It’s no surprise, then, that religion is laced with terms like ‘commandments’ and ‘submission’. The devotion to justifying power is overt.

With economics, though, things are different. Economists don’t overtly praise the powerful. Instead they hardly talk about power at all. That leads some people to conclude that economics isn’t an ideology. But that’s a mistake. Economics is an ideology, but it wraps its justification for power under a pretense — namely ‘freedom’. In capitalism, corporate rulers don’t have the ‘power’ to command. They have the ‘freedom’ to command.

I’ve written about this subterfuge in The Free Market as a Double Lie. I showed how free-market speak became more popular at the same time that corporate power became more concentrated. If you take free-market speak literally, this trend makes no sense. But if free-market speak is subterfuge for justifying power, then the pieces fit together.

Here I want to look at the flip side of the equation — not speaking about power. What defines econospeak is that power is conspicuously absent. It’s a linguistic turn that George Orwell noticed almost a century ago. Politicians of the time, Orwell observed, had started to speak in torturous euphemisms. When militaries committed massacres, politicians call it pacification. Today, we’re so used to this euphemistic language that we hardly notice it. What we would notice is if a politician spoke plainly. Imagine a politician proclaiming:

Let the slaughter begin! The sons of this king will die because of their ancestors’ sins. None of them will ever rule the earth or cover it with cities.

This morbid passage, if you’re wondering, is from the Old Testament. It’s the ‘Good News’ translation of Isaiah 14:20. Surrounded by the euphemisms of modernity, we forget that people ever spoke so plainly. They did so, presumably, because the justification for power was overt. God was on their side.

Today, God is (mostly) off table. And that means power is justified through subterfuge. Instead of praising power, you leave it unsaid. As the dominant secular ideology, economics reflects this subterfuge. In economics, talk about power is conspicuously absent.

If you’re a good critical reader, you can notice this absence. But here I’ll go a step further and quantify it. I’ve gone through the thesaurus and picked words that relate to wielding and submitting to power. Figure 11 shows their frequency in econospeak.

Figure 11: Not speaking about power. Here’s a sample of words related to wielding and submitting to power. I’ve plotted their frequency in economics textbooks on my econospeak quadrants. [Sources and methods].

The results, in Figure 11, are fascinating. The majority of words about power fall in the neglected quadrant. This speaks volumes about economics ideology. Economists don’t talk openly about power. That would ruin the subterfuge.

In simpler times, rulers boasted of their power. British imperialists, for instance, celebrated openly as they conquered the world. (For them, ‘imperialism’ was a good word.) But today, rulers talk in econospeak euphemisms. It’s not imperialism … it’s ‘free trade’!

Missing from econospeak

So far we’ve discussed words that are overused in econospeak, and words that are underused. Now let’s talk about words that are absent.

My sample of econospeak contains about 7.7 million words. In such a large sample, it’s no small feat for a word to be missing entirely. Unless the word is utterly obscure, its absence is important.

So what words are missing from econospeak? Many, obviously. But to frame the question, ask yourself — what is the most popular English word that economists don’t utter?

I’ve asked people on Twitter to take a guess. (See the responses here, here and here.) I’ve plotted these guesses in Figure 12. Notice that this is plot of words that are present in econospeak. That’s because almost no one managed to guess an actual missing word. Instead, the Twitterati were good at guessing neglected and under-represented words.

Figure 12: Twitter guesses for words that are missing from econospeak. I asked people on Twitter to guess the most popular English word that’s absent from economics textbooks. Nobody got the right answer. And most guesses weren’t actually missing words. Still, the guesses are interesting. I’ve plotted them here on my econospeak quadrants. [Sources and methods].

As with many of the plots in this post, I could write an essay about the words in Figure 12. But I have more results to show you. So let’s move on.

Let’s talk about the words that are actually missing from economics textbooks. I know you want to see the words themselves. (Skip ahead if you want.) But I first want to look at the structure of these missing words.

To understand this structure, it helps to have an analogy. Let’s think of the English language as a fully stocked buffet. The different foods represent words. Eating a food represents speaking a word. What we’re interested in here are the leftovers. These are the words that remain unspoken after economists finish talking.

Figure 13 shows one way of visualizing these ‘uneaten’ words. We start with the ‘English-language buffet’ (the red box). These are all the words in the English language (or in this case, a list of about 430,000 words from the Google English corpus). Before you’ve spoken anything, the language buffet is a square. The horizontal axis shows a word’s popularity, as indicated by its percentile in the Google corpus. The vertical axis is the portion of these words that you haven’t used.

Before you talk, the unused portion is 100% everywhere (you haven’t said anything). As you ‘speak’, you eat away at the buffet. If you speak in obscure prose, you eat away at the left side of the buffet. If you use only common words, you eat away at the right side.

What we’re interested in here are economists’ leftovers. When they speak (by writing textbooks), what words do they leave behind? Figure 13 shows the structure of these econospeak leftovers.

Figure 13: The shape of econospeak leftovers. Here’s one way of visualizing the words that are missing from economics textbooks. I represent the English language as a square. The horizontal axis indicates word popularity — the word’s percentile in the Google English corpus. The vertical axis indicates the portion of words not used. The dashed red square is the ‘whole’ English language (a list of about 430,000 words). The blue region shows what economists leave behind. [Sources and methods].

According to Figure 13, economics textbooks leave behind most of the English language — almost everything in the bottom 80% of words. The question is — what does this mean?

To interpret the econospeak leftovers, we’ll turn again to the ‘null hypothesis’. Recall that this is what happens when we randomly draw 7.7 million words from the Google corpus. Here, we’ll look at what the null hypothesis leaves behind. Figure 14 shows how the null hypothesis leftovers compare to what economists leave unspoken.

Figure 14: The shape of econospeak leftovers vs. null hypothesis leftovers. As in Figure 13, I represent the English language as a square. The horizontal axis indicates word popularity — the word’s percentile in the Google English corpus. The vertical axis indicates the portion of words not used. The dashed red square is the ‘whole’ English language (a list of about 430,000 words). The blue region shows what economists leave behind. The red region is what the null hypothesis leaves behind — the words not found in a random sample of 7.7 million words drawn from the Google corpus. Unlike the null hypothesis, econospeak leaves behind many words found in the top 10%. [Sources and methods].

Like econospeak, the null hypothesis leaves behind most of the English language. (The bottom 70% of words remain largely unused.) So the fact that economists don’t use obscure words is unremarkable. It’s a basic feature of language. What makes words obscure, after all, is that few people use them.

There is, however, an important difference between econospeak and the null hypothesis. Econospeak leaves behind many popular words found in the top 10%. In contrast, the null-hypothesis leaves behind virtually none of these top words. So the fact that economists leave many popular words unspoken is statistically significant. (That said, it’s not clear if this is a distinguishing feature of econospeak, or if it’s found in all types of specialized writing. Figuring that out will take more digging.)

Let’s have a look at econospeak’s top 10% leftovers. Figure 15 zooms in on this part of the distribution. The histogram shows the shape of some 16,000 words that economics textbooks omit. That’s far too many words to discuss. But to give you a sense for what words are there, I’ve labelled some examples (of my choosing). These words appear at their corresponding percentile in the Google corpus. (Their vertical position doesn’t mean anything — it’s purely aesthetic.)

Figure 15: Econospeaks’ top 10% leftovers. This figure plots the same data as in Figure 14, but zooms in on unused words in the top decile. I’ve labelled some words of my choosing. Their horizontal position represents their popularity. (Vertical position is aesthetic.) [Sources and methods].

From the examples in Figure 15, I think you’ll agree that there are many important words that economists don’t utter. And what the statistics tell us is that this non-utterance is a choice. It cannot be chalked up to chance.

What’s interesting — and worth looking at more rigorously — is the absence of words about conflict. I’ve shown some of these words in Figure 15. (I’m sure there are many others.) It seems that economists don’t speak about ‘racism’, ‘defiance’, ‘patriarchy’, ‘treachery’, ‘sexism’, or ‘dispossession’. The absence of these conflict words is fascinating. Far from being random, I believe it’s a core part of economics ideology. Economics legitimizes power relations by pretending they don’t exist.

The top missing words

Now to the results that many of you have been waiting for. Let’s look at the most popular English words that are missing from economics. Figure 16 shows these words. The larger the font, the more popular the word.

Figure 16: The most popular words that are missing from econospeak. Font size is proportional to word frequency in the Google corpus. [Sources and methods].

The most popular word that’s absent from economics is … ‘Christ’. That’s an interesting result. But it says more about culture outside of economics than it does about econospeak. Economics is a secular ideology, so it’s no surprise that the last name of a Christian prophet goes unmentioned. What’s interesting is that outside of economics, the word ‘Christ’ is hugely popular. Again, this is a sign of religion’s lasting influence. In capitalist societies, religion may not be the dominant ideology, but its influence remains significant. (It’s informative that no one in my Twitter circle guessed the word ‘Christ’. It suggests that I live in a bubble of atheists.)

There’s much to be said about the other words in Figure 16. But I’ll conclude with just one observation — a fitting irony. We can use words that are absent from econospeak to describe economics ideology:

Economists are the high priests of capitalist society who worship at the altar of the free market. But their doctrines are not based on evidence. Instead, economics is a type of secular theology based on scripture.

(absent words in bold)

Ideology as the unsaid

I started this word-counting project after skimming Gregory Mankiw’s textbook Principles of Economics. I noticed that he used the word ‘distort’ a lot. Peppered throughout his book were whoppers like this:

Almost all taxes distort incentives, cause people to alter their behavior, and lead to a less efficient allocation of the economy’s resources.

(Mankiw in Principles of Economics)

Mankiw’s love for the word ‘distort’ got me thinking — how much does he use this word compared to the average? And so my word-counting bot was born. My initial focus was on the words that were overused. This overuse, I thought, would quantify economics ideology. (FYI: Mankiw does say ‘distort’ a lot. He uses it about 50 times more frequently than average.)

As I started to crunch the numbers, though, I realized that what is most interesting about econospeak isn’t what is overused. What’s interesting are the words that are underused or left unsaid. It’s this (relative) absence, I now believe, that’s key to understanding the ideology of economics.

It reminds me of George Lakoff’s book Don’t Think of an Elephant! If you want somebody to not think about something, the last thing you should do is tell them so. (You’re thinking of an elephant, aren’t you?) Herein lies the genius of economics ideology. Its purpose is to legitimize the status quo. It does so by getting you to think about a free-market fairy tale. While that’s got your attention, you don’t notice that power (and its many injustices) aren’t discussed.

To deconstruct economics ideology, in turn, entails talking about these absences. That’s difficult. What’s in a text is obvious. What’s not there is harder to see. Hence my unease when I took Economics 101. My gut was telling me that something was missing. But exactly what eluded me. Now I know. … because I ran the numbers. The data shouts loud and clear that a large part of the English language is absent from economics textbooks. It’s ideology through the unsaid.

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Keep me up to date

I know that many of you want to explore my econospeak data. To quench your thirst, I’ve included lists of the top 500 overused, underused, and missing words. See them here. I’ve also provided links (below) to my whole econospeak dataset. Lastly, I’m going to make an interactive chart that let’s you explore the structure of econospeak. Stay tuned for that.

Sources and methods

Economics textbooks

Table 2 shows my sample of economics textbooks. Although not exhaustive, this sample contains most of the standard textbooks used in undergraduate economics courses. When creating the sample, my restriction was that the textbooks should be published within roughly the same decade (here, 2004–2014) and that the books are available on Library Genesis. When possible, I tried to get the ‘micro’, ‘macro’ and ‘general’ versions of each book.

The resulting sample of econospeak contains about 7.7 million words, with a vocabulary of roughly 34,000 words.

Table 2: The sample of economics textbooks

Author
Title
Year

Arnold
Economics
2008

Arnold
Macroeconomics
2008

Arnold
Microeconomics
2011

Blanchard & Johnson
Macroeconomics
2012

Case, Fair & Oster
Principles of Microeconomics
2008

Case, Fair & Oster
Principles of Macroeconomics
2011

Case, Fair & Oster
Principles of Economics
2012

Cowen & Tabarrok
Modern Principles of Economics
2011

Frank & Bernanke
Principles of Economics
2008

Frank & Bernanke
Principles of Macroeconomics
2008

Frank & Bernanke
Principles of Microeconomics
2008

Hubbard & O’Brien
Economics
2009

Hubbard & O’Brien
Macroeconomics
2011

Hubbard & O’Brien
Microeconomics
2013

Krugman & Wells
Macroeconomics
2005

Krugman & Wells
Economics
2009

Krugman & Wells
Microeconomics
2012

LeRoy Miller
Economics Today: The Macro View
2011

LeRoy Miller
Economics Today: The Micro View
2011

LeRoy Miller
Economics Today
2011

Mankiw
Principles of Economics
2008

Mankiw
Principles of Macroeconomics
2011

Mankiw
Principles of Microeconomics
2011

McConnell, Brue & Flynn
Macroeconomics
2006

McConnell, Brue & Flynn
Economics
2008

McConnell, Brue & Flynn
Microeconomics
2011

Nicholson & Snyder
Microeconomic Theory
2004

Nicholson & Snyder
Microeconomic Theory
2007

Nicholson & Snyder
Microeconomic Theory
2011

Parkin
Microeconomics
2011

Parkin
Macroeconomics
2011

Parkin, Powell & Matthews
Economics
2005

Perloff
Microeconomics
2011

Perloff
Microeconomics
2014

Pindyck & Rubinfeld
Microeconomics
2012

Pindyck & Rubinfeld
Microeconomics
2014

Rittenberg & Tregarthen
Principles of Economics
2009

Rittenberg & Tregarthen
Principles of Microeconomics
2009

Rittenberg & Tregarthen
Principles of Macroeconomics
2009

Samuelson & Nordhaus
Economics
2009

Varian
Intermediate Microeconomics
2005

Varian
Intermediate Microeconomics
2010

Varian
Intermediate Microeconomics
2014

Notes: I downloaded the textbooks as PDFs and extracted the text using the Linux function pdftotext. This conversion can sometimes induce errors (often due to non-standard fonts). It’s possible that some of the quirks in econospeak are caused by faults in the PDF-to-text conversion.

I’ve used Google’s 2020 1-gram corpus, which measures the text frequency of one-word phrases in the Google Books database. You can download the data here. (Warning: the 1-gram dataset is about 46 GB).

If you’re interested in working with Ngram data, I’ve written a post about my data-wrangling experience. I’ve also written some custom R code for importing Ngram 2020 data. It’s available at Github.

I use Ngram data over the years covered by the textbooks (2004-2014). For each word, I calculated its mean frequency over these years, weighted by the portion of the textbook sample published in each year.

Dictionary

I restrict both the econospeak sample and Google English sample to words that are in a predetermined ‘dictionary’. My dictionary consists of the following:

From this word list I remove/change the following:

• remove words with fewer than 3 letters
• remove common first names (using R lexicon function freq_first_names)
• remove common last names (using R lexicon function freq_last_names)
• remove prepositions (using R lexicon function pos_preposition)
• remove English numerals from 1 to 100 (i.e. one, two, three …)
• remove ‘stop words’ (using R tm command stopwords)
• change British spellings to American (as in labour → labor)
• convert all words to lower case
• remove acronyms (words containing ‘.’)
• remove contractions (words containing apostrophes)
• remove hyphenated words
• remove words containing numbers 0-9

The resulting ‘dictionary’ contains about 500,000 words.

Econospeak word lists

Browse the top 500 overused, underused and missing words:

Top 500 overused words

Word
Frequency relative to

nondissipated
2612.5

latinian
1553.0

instrengthen
1466.1

refrainer
1281.9

outtell
1093.2

nonmonopolistic
1003.8

993.1

reisted
973.0

underofficial
947.1

superathlete
819.3

inpayments
760.0

pretariff
734.2

outpayment
703.2

willingnesses
694.3

inworked
656.9

reveto
642.9

debitable
609.0

idahoes
573.1

condimented
558.4

monopolistically
552.9

grasshopperish
545.0

nondepreciating
528.0

nonrival
448.4

loanable
441.2

monopsonist
436.7

checkable
431.9

recessionary
406.0

srac
405.7

overdiscounting
384.1

monopsony
383.4

msbus
361.3

demanders
353.2

upsloping
342.5

dissaved
337.0

underproduces
311.1

theftproof
303.4

300.7

kinetophonograph
297.0

yuckers
290.9

contractionary
288.4

macroeconomists
286.4

oligopolist
283.4

monopolist
267.6

mobilia
267.1

xed
258.9

groland
257.4

macroeconomist
247.2

avc
237.5

monopsonies
233.4

undersupplies
232.4

superstrain
225.8

slumpflation
223.7

noncollusive
222.9

nonrecession
222.1

nonsatiation
216.8

superathletes
216.1

oversale
214.6

hyperinflations
212.6

mrts
210.8

overallocation
206.0

dissaving
203.9

overprovide
202.8

oligopoly
198.3

diseconomies
197.1

expansionary
195.8

equiproportional
191.7

rightward
184.3

frictionally
183.0

microeconomics
182.9

nonprohibitive
179.5

repaves
178.2

restep
175.7

pfennings
175.1

finking
175.1

longrun
171.9

nonstrategically
170.4

regovernment
169.0

snowboards
168.0

ditchdigging
164.2

homothetic
161.2

inpayment
161.0

nonlabor
160.5

gardol
157.7

nonunionized
156.9

overfishes
154.5

leftward
153.0

debudded
152.8

ploughwright
152.4

underproduce
152.1

traylike
144.5

monopsonistic
144.4

duopolist
140.8

nairu
137.4

dissaves
135.4

monetarists
134.9

shlu
131.3

bananaland
130.9

marginal
129.2

overprovision
129.0

misestimating
128.4

oligopolies
128.4

noncredibility
127.6

macroeconomics
126.9

externality
126.9

inappropriable
126.2

nonmoney
125.7

epts
125.4

oversales
122.0

monopolistic
121.5

lossa
121.3

mpl
121.2

intercharge
119.2

mrsr
118.5

disinflation
117.8

hapte
117.3

berck
117.3

overproviding
116.7

repairperson
114.4

dissave
109.7

nonexportable
109.5

109.4

underproduction
108.3

caff
108.1

isoelastic
107.9

tangencies
106.2

tangency
105.2

inelastic
102.4

nonlibrarian
101.9

homebodies
100.5

underproduced
100.0

elasticity
99.1

duopoly
99.1

overinformed
98.9

elasticities
98.7

98.0

paribus
93.9

unionizes
93.0

ceteris
92.0

prepriced
91.5

monopolists
90.9

noneconomists
90.7

switchgears
90.6

misallocated
90.6

monetarist
90.6

coalmaster
90.1

oligopolistic
88.2

quasilinear
87.7

oligopsonies
87.4

overinsure
86.9

cartelize
86.3

mpc
85.7

gerik
84.9

forgone
84.3

externalities
84.2

curve
84.2

mrp
83.5

noninflationary
83.2

stagflation
83.0

noneconomist
82.6

hoisters
79.9

depreciates
79.7

disinflations
79.5

takeaways
79.5

atc
79.1

demander
78.7

potterville
77.5

prot
77.1

recessions
76.8

diversifiable
76.5

multiplier
76.4

bushels
73.5

ungreat
73.2

underbids
72.2

dominiums
72.1

exhaustible
71.8

economists
71.6

dissavings
71.6

productivities
71.4

gien
71.4

netbooks
71.3

flyswatters
71.3

snowblowers
71.1

imperfectively
70.9

intis
70.4

telebanking
69.8

misallocations
69.7

quantity
69.0

seignorage
68.5

untillable
68.4

actuarily
68.3

kamika
68.0

superduper
67.6

gdp
67.5

nonprofitability
67.4

aggregate
67.3

underconsumed
67.0

windsurfs
66.9

antimerger
66.8

pizzas
66.6

overprovided
66.2

noncompeting
66.0

marketa
65.6

monopoly
65.3

inefficiently
65.3

mpp
65.1

deflator
64.9

monetarism
64.7

overproduces
64.4

nonexclusion
64.1

redeposits
64.0

tollbridge
64.0

dxt
63.8

tfc
63.7

undermeasured
63.6

logrolling
63.3

costlessly
62.9

surplus
62.9

nondiscount
62.8

disinflate
62.6

dcor
62.0

noncompulsive
61.9

rtsl
61.7

equilibrium
60.8

peasouper
60.8

oer
60.3

gristly
58.9

featherbedding
58.5

overplanting
57.6

nonreversibility
57.5

scalpers
57.4

prefreeze
57.3

inflation
57.1

microeconomic
56.6

keynesian
56.3

cornland
56.3

outfish
55.6

maximizes
55.1

autarky
54.7

precontrol
54.6

misallocates
54.3

collude
54.2

monopsonists
53.9

relends
53.7

retexturing
53.6

cartelizing
53.1

nautica
53.0

nonstandardization
52.7

nonsatisfaction
52.6

burritos
52.6

noncredible
52.6

superexpensive
52.5

shirking
52.5

stayover
52.4

bushel
52.4

minishing
52.3

noncooperative
52.3

marginalism
52.1

unrecoverably
52.1

decafs
51.8

nondiscriminating
51.6

earns
51.1

aggeration
50.9

xms
50.6

gonzlez
50.6

dowment
50.5

superfunction
50.4

demand
50.2

maximization
50.1

genos
50.0

grinches
49.7

calzones
49.3

49.1

stairlike
48.7

duopolies
48.1

coconuts
48.0

precommit
47.8

hyperinflation
47.8

keynesians
47.5

averter
47.3

suers
47.2

price
46.9

remint
46.6

underpower
46.6

overinvest
45.9

overdifferentiation
45.8

costless
45.7

undertaxed
45.6

submarket
45.5

wahoo
45.5

misallocation
45.3

rms
45.3

collusive
45.2

repractice
45.1

kumquats
45.0

msb
44.5

cutto
44.5

inflationary
44.2

disinflationary
44.1

preannounce
44.0

korunas
43.9

peso
43.7

oligopsony
43.6

overcompensates
43.5

nonoptimal
43.5

djt
43.4

trillions
43.1

cappuccinos
43.0

dnx
43.0

cartelized
43.0

antipollution
42.8

deflation
42.6

sellers
42.5

thrifts
42.4

42.0

unemployment
41.9

supersaver
41.7

antitheft
41.5

afc
41.4

excludability
41.1

cartel
41.0

inelasticity
40.7

indifference
40.6

carpetmaking
40.4

diminishing
40.3

postponable
40.2

backflows
40.1

preemergency
39.9

pesos
39.9

ricardian
39.9

39.9

excludable
39.9

chunnel
39.8

multiproduct
39.7

rebating
39.7

autoworker
39.5

postcontract
39.4

misestimated
39.2

mcpo
39.1

perfectively
39.0

payoffs
38.9

carlena
38.9

misestimate
38.8

haircutters
38.7

noncontrollable
38.6

overexpand
38.3

speat
38.0

cartelization
37.9

belion
37.7

redistributes
37.7

bailbond
37.6

rises
37.6

macroeconomic
37.5

overutilize
37.4

toyotas
37.2

overutilized
37.0

disposable
37.0

overvalued
37.0

hamburgers
36.9

bolivias
36.8

cpi
36.5

substitutes
36.4

curves
36.2

mpb
36.1

guilders
36.1

onethe
36.1

luters
35.9

subsidizes
35.9

dvc
35.8

reengineers
35.7

multiplant
35.7

overbook
35.7

vlor
35.4

poolers
35.4

macks
35.4

savers
35.3

preloan
35.2

pareto
35.2

righties
35.2

35.1

firms
35.1

nonindexed
35.0

cokie
34.9

substitutability
34.7

kinked
34.7

summar
34.6

intersects
34.5

complier
34.5

rebegin
34.5

clich
34.4

proprietorships
34.4

rationing
34.3

monopolies
34.3

recession
34.2

lattes
34.1

depreciate
34.0

output
33.6

overconsumed
33.5

supply
33.5

wage
33.4

unforecasted
33.3

safekeeper
33.3

bundling
33.0

33.0

ringgits
33.0

inframarginal
33.0

disinvesting
32.9

quintile
32.9

32.7

equals
32.7

billfolds
32.6

posttax
32.6

seigniorage
32.5

sml
32.5

qmc
32.5

pricefixing
32.3

inflations
32.2

antigrowth
32.1

underproducing
31.9

contraltos
31.9

countersue
31.8

starvers
31.7

overbidding
31.6

autoworkers
31.4

incomes
31.2

utility
31.2

decontrolling
31.2

frictional
31.2

mux
31.1

nominal
31.0

surpluses
31.0

uninsurable
31.0

ppc
31.0

snowboard
30.8

unexploited
30.8

overgraze
30.8

chevrolets
30.8

decontrolled
30.6

echikson
30.6

hyperrational
30.4

overutilizing
30.4

smoothies
30.4

yens
30.3

inefficiency
30.2

entres
30.1

diseconomy
30.0

randomizes
29.9

trustbusters
29.9

payoff
29.9

commercializes
29.8

bepress
29.8

nonlocals
29.7

29.7

29.7

nonneutrality
29.6

elysburg
29.4

contestable
29.3

supercompetitive
29.2

litterbugs
29.1

29.0

shiftability
29.0

damager
28.9

retime
28.7

overissuance
28.7

disutility
28.5

cleanings
28.4

propecia
28.4

hubbard
28.4

nonmarket
28.3

salsas
28.1

depletable
28.1

prices
28.0

maximized
28.0

haircuts
28.0

entrep
28.0

kiloliter
27.9

arbitrager
27.8

spendable
27.7

quintiles
27.6

edgeworth
27.5

substitution
27.4

outproduce
27.3

lobstermen
27.3

truckful
27.2

pengos
27.2

overprice
27.1

earfuls
27.0

complements
27.0

unrented
26.9

trilemma
26.9

prilosec
26.9

economizes
26.9

pepsi
26.8

substitutable
26.6

intramarginal
26.6

atter
26.5

colluding
26.5

nonstriking
26.3

birthrates
26.2

taxicabs
26.2

reselling
26.2

Top 500 underused words

Word
Frequency relative to

anti
0.0009

jewish
0.0010

proteins
0.0018

god
0.0018

tumor
0.0019

neck
0.0020

damn
0.0023

gospel
0.0024

jesus
0.0024

islam
0.0024

paused
0.0026

bent
0.0026

renal
0.0026

0.0027

acids
0.0028

ritual
0.0028

servant
0.0028

poems
0.0030

moses
0.0030

wounded
0.0030

lips
0.0031

pursuant
0.0032

finger
0.0033

neural
0.0033

darkness
0.0033

hebrew
0.0033

chem
0.0033

ass
0.0034

enzyme
0.0034

soul
0.0034

atomic
0.0035

hello
0.0036

multi
0.0037

doi
0.0038

dare
0.0038

narrative
0.0039

sins
0.0039

activated
0.0040

stakeholders
0.0040

divine
0.0040

psychiatric
0.0040

sexuality
0.0041

physiological
0.0042

hormone
0.0042

warmth
0.0042

pathways
0.0042

prayer
0.0043

grin
0.0043

rape
0.0043

gods
0.0044

genre
0.0044

abdominal
0.0044

brave
0.0044

markers
0.0046

template
0.0046

cerebral
0.0047

pastor
0.0047

hypertension
0.0047

gay
0.0047

negro
0.0048

bishop
0.0049

archeological
0.0049

teaspoon
0.0050

clinical
0.0050

palace
0.0050

dysfunction
0.0050

echo
0.0051

supper
0.0051

elbow
0.0052

bibliography
0.0052

amplitude
0.0052

deployment
0.0052

organism
0.0053

gratitude
0.0053

hallway
0.0054

shining
0.0054

lord
0.0054

lit
0.0054

poets
0.0054

antibodies
0.0055

non
0.0055

murdered
0.0055

aloud
0.0056

ideals
0.0056

cheek
0.0057

eternal
0.0057

sofa
0.0058

thickness
0.0059

smiles
0.0059

waiver
0.0059

afterwards
0.0060

catholic
0.0060

tumors
0.0061

chest
0.0062

boiling
0.0062

mediation
0.0062

swear
0.0062

counselor
0.0062

grabbed
0.0062

gaze
0.0063

heavens
0.0063

salvation
0.0063

bleeding
0.0063

teachings
0.0063

naval
0.0064

manners
0.0064

christians
0.0064

yeah
0.0064

spirituality
0.0065

muscle
0.0065

stairs
0.0065

prose
0.0065

tissues
0.0065

kissing
0.0066

greeks
0.0066

whilst
0.0066

insertion
0.0067

hon
0.0067

serum
0.0067

sophie
0.0067

pillow
0.0067

commander
0.0067

delete
0.0067

0.0068

luke
0.0068

holy
0.0068

monk
0.0068

cheeks
0.0069

fairy
0.0069

glory
0.0069

goodbye
0.0069

scriptures
0.0069

gown
0.0070

gland
0.0070

sanctuary
0.0070

forgive
0.0070

detector
0.0070

prophet
0.0070

cave
0.0071

christianity
0.0071

amino
0.0071

winding
0.0071

breath
0.0071

textual
0.0071

mortal
0.0071

slept
0.0072

spine
0.0072

savior
0.0073

sensor
0.0073

sip
0.0073

biomass
0.0073

rebel
0.0074

bandwidth
0.0074

nausea
0.0075

appearances
0.0075

intellect
0.0076

biopsy
0.0077

herbs
0.0077

sensation
0.0077

superintendent
0.0077

font
0.0077

mentor
0.0077

acta
0.0077

sect
0.0077

mama
0.0078

dedication
0.0078

trauma
0.0078

muslim
0.0078

snapped
0.0078

patches
0.0079

0.0079

lust
0.0079

appl
0.0079

semantics
0.0079

visualization
0.0079

marsh
0.0080

ribbon
0.0080

empowerment
0.0080

grammar
0.0080

soc
0.0080

int
0.0080

confidentiality
0.0081

fiction
0.0081

calibration
0.0081

asleep
0.0081

flung
0.0081

eur
0.0082

bible
0.0082

encoding
0.0082

antenna
0.0082

beloved
0.0083

twisted
0.0083

neurological
0.0083

upstairs
0.0083

smile
0.0084

0.0084

dreaming
0.0084

sleeve
0.0084

intravenous
0.0084

heel
0.0084

knocked
0.0085

parted
0.0085

collaboration
0.0085

glowing
0.0085

verse
0.0086

memoirs
0.0086

polymer
0.0086

faint
0.0086

olivia
0.0086

submission
0.0087

der
0.0087

frowned
0.0087

annex
0.0087

habitats
0.0087

absorption
0.0087

disgust
0.0088

jaw
0.0088

preacher
0.0088

latino
0.0088

softly
0.0088

sensations
0.0088

pale
0.0089

apologize
0.0089

tense
0.0089

torture
0.0089

mourning
0.0089

deposition
0.0089

sexual
0.0090

impairment
0.0091

morrow
0.0091

beam
0.0091

0.0091

staring
0.0092

topical
0.0092

porch
0.0092

nerve
0.0092

sodium
0.0092

offenses
0.0093

kiss
0.0093

aye
0.0093

protocols
0.0094

cute
0.0094

eng
0.0094

horn
0.0095

farewell
0.0095

shone
0.0095

colonization
0.0095

pray
0.0095

inquiries
0.0095

glasgow
0.0095

remembers
0.0095

theatrical
0.0095

pity
0.0095

elder
0.0096

smiling
0.0096

activate
0.0096

screamed
0.0097

imperialism
0.0097

texture
0.0097

utmost
0.0097

irritation
0.0097

self
0.0097

battlefield
0.0098

jerusalem
0.0099

disbelief
0.0099

spiritual
0.0100

pulses
0.0101

humility
0.0101

colonel
0.0101

dna
0.0101

legitimacy
0.0101

policeman
0.0101

hum
0.0102

curtis
0.0102

believer
0.0102

tidal
0.0102

hesitated
0.0103

bristol
0.0103

viral
0.0103

aroused
0.0103

fungi
0.0103

laughing
0.0103

marching
0.0104

vessel
0.0104

feminist
0.0104

emergent
0.0105

thoracic
0.0105

pulse
0.0106

islamic
0.0106

rue
0.0106

sang
0.0106

signatures
0.0106

laughs
0.0106

implicated
0.0106

0.0106

prophetic
0.0106

bodily
0.0107

epilepsy
0.0107

vols
0.0107

dances
0.0108

cowboy
0.0108

neuron
0.0108

ovarian
0.0108

endurance
0.0108

nos
0.0108

interpreter
0.0108

tel
0.0109

architecture
0.0109

unconscious
0.0109

consciousness
0.0109

synthesized
0.0110

rituals
0.0110

drowned
0.0110

glorious
0.0111

hereditary
0.0111

buddhist
0.0111

fraser
0.0111

cos
0.0111

sorrow
0.0111

modal
0.0111

shaft
0.0111

shrugged
0.0111

exile
0.0111

churches
0.0112

mythology
0.0112

0.0112

porous
0.0112

intermittent
0.0113

tugged
0.0113

peeled
0.0113

inquired
0.0113

memorandum
0.0113

mouth
0.0114

comp
0.0114

teasing
0.0114

treasures
0.0114

downstairs
0.0114

della
0.0114

upright
0.0114

brook
0.0114

gonna
0.0115

commandments
0.0115

diagnosis
0.0116

homosexuality
0.0116

heroes
0.0116

jessie
0.0116

seminars
0.0116

exquisite
0.0116

0.0117

mortar
0.0117

startled
0.0118

hague
0.0118

kidding
0.0118

mutation
0.0118

sword
0.0119

youthful
0.0119

roared
0.0120

thyroid
0.0120

longed
0.0120

univ
0.0120

tongue
0.0120

travis
0.0120

cooler
0.0120

decoration
0.0120

legs
0.0120

shoulders
0.0121

muddy
0.0121

chin
0.0121

juvenile
0.0121

welcoming
0.0121

missionary
0.0121

singh
0.0122

cinnamon
0.0122

tone
0.0122

brow
0.0122

oath
0.0122

sequencing
0.0122

eyed
0.0123

accent
0.0123

bedside
0.0123

rifles
0.0123

sediment
0.0123

arterial
0.0123

relieved
0.0124

affirmation
0.0124

breasts
0.0124

indigenous
0.0124

charming
0.0124

coll
0.0125

tang
0.0125

surrendered
0.0125

canyon
0.0125

workflow
0.0125

leaped
0.0125

collaborative
0.0125

stationed
0.0125

charleston
0.0125

liaison
0.0125

grande
0.0126

prophets
0.0126

tick
0.0126

temperament
0.0126

girl
0.0126

pupils
0.0126

biochemistry
0.0127

beard
0.0127

counsel
0.0127

gill
0.0127

stat
0.0127

obstruction
0.0128

contempt
0.0128

amusing
0.0128

stout
0.0128

connor
0.0129

parkinson
0.0129

toes
0.0129

baptist
0.0129

companions
0.0129

angel
0.0129

muslims
0.0130

climax
0.0130

poem
0.0130

thou
0.0130

evelyn
0.0130

mater
0.0131

yelled
0.0131

neurology
0.0131

subdivision
0.0131

cicero
0.0131

skinny
0.0131

baltic
0.0131

intently
0.0131

romans
0.0132

cognitive
0.0132

reconstructed
0.0132

cranial
0.0132

knees
0.0132

paralysis
0.0132

dear
0.0132

dialog
0.0132

eyebrows
0.0133

skin
0.0133

trainer
0.0133

tcp
0.0133

psychiatry
0.0134

liberation
0.0134

gently
0.0134

expelled
0.0134

testament
0.0134

thee
0.0134

respectful
0.0134

rehabilitation
0.0134

categorical
0.0135

chased
0.0135

detention
0.0135

limp
0.0135

architectural
0.0135

symbolism
0.0135

backup
0.0135

savannah
0.0136

conquer
0.0136

recollection
0.0136

infiltration
0.0136

chronicles
0.0136

0.0137

oppressive
0.0137

screw
0.0137

affinity
0.0137

che
0.0137

organisms
0.0137

censorship
0.0137

isaiah
0.0137

bless
0.0138

statutory
0.0138

learner
0.0138

celtic
0.0138

irene
0.0138

sounded
0.0138

legion
0.0138

incidents
0.0138

disciples
0.0138

termination
0.0138

jewel
0.0138

majesty
0.0139

orient
0.0139

tears
0.0139

posture
0.0139

church
0.0139

rusty
0.0140

handler
0.0140

molecular
0.0140

exhibitions
0.0140

monument
0.0140

alison
0.0141

genesis
0.0141

dialogs
0.0141

compassionate
0.0141

darcy
0.0141

0.0141

delegation
0.0141

Top 500 missing words

Word
Percentile

christ
0.998

smiled
0.997

nodded
0.997

laughed
0.996

jews
0.995

stared
0.995

throat
0.994

glanced
0.994

whispered
0.994

leaned
0.993

membrane
0.993

electron
0.993

worship
0.992

theology
0.992

lateral
0.992

receptor
0.992

kissed
0.992

activation
0.992

sighed
0.991

pulmonary
0.991

shit
0.991

para
0.991

shaking
0.991

laughter
0.991

lieutenant
0.990

lesions
0.990

verb
0.990

anterior
0.990

ieee
0.990

glucose
0.989

theological
0.989

retrieved
0.989

folder
0.989

scripture
0.989

cfr
0.989

sensory
0.989

proc
0.989

mediated
0.989

vascular
0.989

supra
0.989

alien
0.989

fuck
0.989

receptors
0.989

spinal
0.988

geog
0.988

waist
0.988

priests
0.988

learners
0.988

pathway
0.988

covenant
0.988

grinned
0.988

clin
0.988

fragments
0.988

subpart
0.988

rhythm
0.988

que
0.988

phys
0.988

metabolism
0.988

fracture
0.988

fatigue
0.988

cir
0.988

substrate
0.988

waved
0.988

inflammatory
0.987

narratives
0.987

fucking
0.987

ref
0.987

prayers
0.987

binary
0.987

0.987

metabolic
0.987

urine
0.987

flame
0.987

chapel
0.987

belly
0.987

nucleus
0.987

shear
0.987

noun
0.987

specimens
0.987

custody
0.987

corpus
0.986

wounds
0.986

freud
0.986

biol
0.986

rna
0.986

0.986

hurried
0.986

stare
0.986

muttered
0.986

specimen
0.986

swallowed
0.986

enzymes
0.986

kant
0.986

hips
0.986

seq
0.986

meditation
0.986

silently
0.986

anglo
0.986

butler
0.986

anthropology
0.986

fetal
0.986

parliamentary
0.986

murmured
0.986

regiment
0.986

infantry
0.986

tribunal
0.986

inhibition
0.986

toxicity
0.986

saints
0.986

arabic
0.986

inflammation
0.986

skull
0.986

oxidation
0.985

scattering
0.985

rubbed
0.985

racism
0.985

maggie
0.985

meta
0.985

0.985

satan
0.985

carcinoma
0.985

enlightenment
0.985

chambers
0.985

altar
0.985

lily
0.985

vitro
0.985

ventricular
0.985

vapor
0.985

parish
0.985

genome
0.985

spectral
0.985

feminine
0.985

spectra
0.985

prayed
0.985

modernity
0.985

sql
0.985

trustee
0.985

relational
0.985

cemetery
0.985

pathology
0.985

verses
0.985

mistress
0.984

verbs
0.984

artifacts
0.984

lodge
0.984

reactive
0.984

motions
0.984

cock
0.984

antibody
0.984

resurrection
0.984

luther
0.984

congregation
0.984

hindu
0.984

mol
0.984

distal
0.984

instructional
0.984

cathedral
0.984

nod
0.984

0.984

neo
0.984

lesion
0.984

goddess
0.984

cervical
0.984

reg
0.983

burial
0.983

inhibitors
0.983

ventilation
0.983

praying
0.983

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Joe Biden Will Be a Republican President

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Past performance is no guarantee of future returns but there are few more reliable ways to predict what comes next than to examine the historical record because, most of the time, history really does repeat.

What kind of president would Joe Biden be? His centrist supporters assure progressives that he will be one of them, pushing an aggressive legislative agenda reminiscent of FDR’s New Deal. His Republican opponents portray him as a socialist. But Biden hasn’t actually promised anything ambitious.

The last two Democratic presidencies provide a good indication of what a Biden Administration would look like. Like Biden, Bill Clinton and Barack Obama hail from the centrist party establishment. If personnel is policy, the three men hang out with many of the same advisors, businesspeople and elected officials. They’re not identical: Clinton is a charismatic retail politician, Obama is aloof and professorial, and Biden is an LBJ-style buttonholer minus Johnson’s secret idealism. But they’re ideologically and temperamentally similar to a remarkable extent.

I remembered Clinton and Obama as deeply disappointing to voters with traditional liberal Democratic values. I remembered that most of their major legislative accomplishments would not have been out of place under a Republican administration.

When I checked the historical record recently, however, it was even worse than I remembered.

Clinton used his political capital to push through free trade deals like NAFTA and the WTO, which killed manufacturing jobs and drove the final nails into the coffin of big labor. He “ended welfare as we know it,” making it even more difficult for people who lost their jobs to get back on their feet and adding the chronically poor to the ranks of the homeless. Clinton signed Joe Biden’s now infamous 1994 crime bill into law, codifying a racist judicial system that disproportionately punishes black men for relatively minor offenses.

Clinton repealed the 1930s-era Glass-Steagall Act, banking deregulation set the stage for banks to wallow in the reckless predatory lending practices that tanked the global economy in 2008-09.

His most impressive achievement was balancing the federal budget and paying off the deficit, but he didn’t do it by raising taxes on the rich. He imposed austerity on social programs—just like a Republican would do.

I searched hard for Clintonian achievements that could credibly be called liberal or at least left of center, but aside from a few minor regulations here and there, there aren’t any. “So we liberals and radicals searched the Clinton administration for vast new programs to applaud. But nothing loomed into view,” Paul Berman wrote in The New Republic at the end of Clinton’s presidency in 2000. Clinton was a moderate Republican president.

In some ways—especially foreign policy—Obama was even worse. Clinton bombed with the bloody relentlessness of a Reagan or a Bush: Bosnia, Sudan, Afghanistan and, forgotten now, Iraq so much and so often that pilots dumped their bombs in the desert to cover for the fact that they were running out of fresh targets. His sanctions stopped everything, including medical supplies, from entering Afghanistan. But he had nothing on Obama.

After Col. Muammar Gaddafi signed a peace deal with Bush that ended Libya’s nuclear program, Obama assassinated him with a drone, plunging that nation into a bloody civil war. Thanks to Obama, Libya, formerly the most literate and prosperous country in Africa, is now a failed state where slavery has been restored. Obama similarly wrecked Syria, where he also funded and armed jihadi extremists against secular socialist leaders. Obama radically expanded Bush’s drone program, kept Gitmo open, effectively pardoned Bush’s torturers, expanded the USA-Patriot Act and NSA spying on your phone calls and emails.

With Democrats like these, you don’t need Republicans!

For liberals, there is one relatively bright spot in these 16 years of Democratic rule: the Affordable Care Act. Obamacare was the first major health-sector reform in decades and brought coverage to tens of millions of patients, most beneficially via Medicaid expansion.

Let’s face it. The last two Democratic presidents didn’t really govern like Democrats. Compare the ACA to the achievements of Republican presidents like Ronald Reagan, George W. Bush and Donald Trump. Republicans push through huge changes when they are in office.

And I’m not even going to point out—well, yes I am—that Obamacare was conceived by the right-wing Heritage Foundation.

As I wrote at the beginning of this essay, what happened under Clinton and Obama won’t necessarily be replicated by Joe Biden. But it almost certainly will be.

There’s a reason Biden considered picking a Republican running mate and a reason Republicans are endorsing him and a reason he gave Republicans more speaking time at the Democratic National Convention than AOC—he’s one of them, not one of us.

(Ted Rall (Twitter: @tedrall), the political cartoonist, columnist and graphic novelist, is the author of the biography “Political Suicide: The Fight for the Soul of the Democratic Party.” You can support Ted’s hard-hitting political cartoons and columns and see his work first by sponsoring his work on Patreon.)

Never Trump, Never Biden: the Progressive Case for Voting Third Party or Boycotting the Election

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Republicans will vote for Trump no matter what. Democrats will vote for Biden no matter what. This column is for progressives weighing the pros and cons of succumbing to the two-party trap, and voting for Biden.

Unless you’ve been sucking through a ventilator in a COVID-19 ward for the last few months, you know the argument in favor of swallowing your disappointment that neither Bernie Sanders nor Elizabeth Warren are the Democratic nominee, resisting the temptation to punish the DNC for rigging the primaries, and forgetting Joe Biden’s right-wing voting record and Kamala Harris’ penchant for locking up innocent people of color and throwing away the key: Trump is a monster, his second term will bring fascism to America, Biden will be more amenable to pressure from the left than Trump.

Except for the part about Trump being a terrible human being, the call to sell out is all based on nonsense.

Reelecting Trump would send a nasty symbolic signal to the world but his actual presidency will almost certainly be characterized by the plagues of lame duckery. Second terms are worthless. Presidents don’t get anything done during their second term. Even FDR floundered. Whatever you think of Trump, does this president strike you as a brilliant Machiavellian tactician who has been holding back his most extreme instincts for four years? Smarter than Reagan, Clinton or Obama? Should Trump be reelected, he will almost certainly be impeached again. Allies like Mitch McConnell will drift away. He may face prosecution.

Some progressives are vulnerable to the argument that, though far from ideal, a neoliberal warmonger like Joe Biden nevertheless represents an improvement over Donald Trump. That argument fails.

Left-of-center electoral politics in the United States is not like football, a game in which a team moves the ball down the field in incremental steps. Mainstream corporate-owned Democratic Party politics is not on the same continuum as progressivism. Neoliberalism isn’t watered-down progressivism; progressivism isn’t a more robust form of neoliberalism. They are opposing ideologies. Progressives and centrists are enemies. When neoliberal centrists achieve power, progressives find themselves in the political wilderness. Obama didn’t have a single progressive in his cabinet. Biden doesn’t have any progressive top advisors.

Corporate Democrats ignore progressives. They crush them. Two major protest movements emerged under Obama, Occupy Wall Street and Black Lives Matter. Obama deployed the surveillance state to eradicate both. Ask Julian Assange and Edward Snowden how amenable corporate Democrats like Obama are to progressive demands for change. It would be idiocy to expect anything different from Biden, who just appointed an out-of-control former prosecutor during a period of unprecedented protest against police brutality.

Would Biden be better than Trump? Only in temperament. Qualitatively, Biden presents a friendlier face for a pro-business domestic agenda that features few substantial differences with the Republicans. Under his proposed Democratic administration, we can expect to see a continuation of a tax structure that favors wealthy individuals and corporations, shrinking union power and rising income inequality, a horrible for-profit healthcare system, and systemic police violence directed disproportionately against people of color and the poor.

Understandably, there is trepidation about the possibility of Donald Trump naming a successor to Supreme Court Justice Ruth Bader Ginsberg, who is ailing. Even if Democrats control the Senate after January, and Biden pushes through a liberal—which, given his record, is unlikely—the overall balance of the court will not change. It is a conservative court and it will remain one.

In foreign policy, there is far less cause for optimism. From Bosnia to Afghanistan to Iraq to Libya to Syria, Joe Biden has enthusiastically voted for and convinced his fellow legislators to support brutal foreign interventions. Though disgusting, Trump’s record is nevertheless far better than Biden’s. Trump has expanded Obama’s drone wars and supports the bloodthirsty Saudi regime in the proxy civil war in Yemen. Yet he also negotiated a deal for total U.S. withdrawal from Afghanistan and repeatedly expresses his willingness to negotiate with such adversaries as North Korea and Iran without pre-conditions.

Neither Trump nor Biden will do anything that progressives really care about. Neither will support the Green New Deal or, for that matter, doing anything real about climate change. Neither is in favor of student loan forgiveness. Neither will take the profit incentive out of healthcare.

Some progressives worry about “wasting their vote” on an outfit like the Green Party. What could be more of a waste than voting for someone who is against everything you care about?

In high school civics class they told you that a single vote can make a difference. They lied. Not in a national election. Not at the state level of a national election. In the closest battleground state of 2016, New Hampshire, Clinton beat Trump by 2,701 votes. Sure, if you and thousands of other folks vote the same way, outcomes can change. But you have no control over other people. You have one vote. That’s all. Even if you live in Ohio, you personally can’t change anything. So live free.

On the other hand, withholding your vote from the Democratic Party can have a positive impact. Several million primary voters cast ballots for Bernie Sanders in 2016 but stayed home in the general election. Primary voters are fanatics—only 12% turnout compared to about 55% in the general election—so when they don’t show up it’s a boycott, not apathy. After Hillary lost, party insiders concluded they would have to move left in order to motivate progressive base voters. Many contenders in the 2020 Democratic primaries espoused elements of Bernie Sanders’ platform. Without the 2016 progressive boycott, that never would have happened.

If you are trying to send a message with your vote, voting for a third party is likelier to register with analysts than staying home on election day.

Voting for Biden sends only one message: you approve of him and his politics. Why, after getting the milk for free, would he pay attention to any of the cow’s complaints?

(Ted Rall (Twitter: @tedrall), the political cartoonist, columnist and graphic novelist, is the author of the biography “Political Suicide: The Fight for the Soul of the Democratic Party.” You can support Ted’s hard-hitting political cartoons and columns and see his work first by sponsoring his work on Patreon.)

The Road to Hell is Paved with Good Intentions.

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Source: The Saturday Paper.
Imagine a capitalist who, needing two new workers, publishes an advertisement asking for applications. After receiving 470 applications for the two positions, the capitalist feels disappointed. Unemployment benefits are to blame, the capitalist says, because they are too generous. More people should have applied.

What would you say about that person? Would it make any difference if the capitalist were skinny or bald?

Let’s add details. Although the capitalist pays the wage rates prevailing in the labour market for the two positions, that industry pays the lowest wage rates. Say, the legal, prevailing median and  average weekly wages in that industry are the lowest in the land. Would that explain why many other workers, perhaps less desperate than those 470, did not apply for those two positions?

Further suppose one were to reduce unemployment benefits or even eliminate them altogether, so as to increase the number of applicants, in accordance with the capitalist’s wishes. Would that improve in any way the situation of the 470 original and more desperate applicants?

That capitalist needed two additional staff. Let’s say another 470 applicants were pushed to apply for those two positions. Would him/her hire any more employees because the number of applicants doubled?

Let’s stop here. Think well your answers to those questions before going any further. Take your time.

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I’ve presented that scenario as a hypothetical. It’s not. That story appeared last Saturday in the Daily Mail Australia under the byline of Zoe Zaczek. There is a capitalist who really says that.

That, I’m sure, will not surprise Left-leaning readers. The Daily Mail Australia is the local edition of the ultra Right-wing British rag of the same name. To screw workers is in their DNA. That’s how the likes of Zaczek make a living.

But there are two details that may surprise Left-leaning readers, particularly those of a Liberal/Leftish persuasion. Go ahead, here’s the link to that article. Look at the photos.

That man is our capitalist.

That’s the first detail. Capitalists, just like Australian citizens and permanent residents, don’t need to be white. It’s not the colour of one’s skin that makes one a capitalist. Similarly with foreigner: foreigner doesn’t necessarily mean non-white.

That’s the other side of the racial equality coin the Liberal/Leftish stubbornly refuse to accept and need to be reminded of.

Yes, my friend, I don’t know what thoughts crossed your mind when I presented that story as a hypothetical. What I do know is that whatever you thought of that capitalist before seeing the photos, you must keep thinking after seeing the photos.

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Allow me a digression.

Source: 6333.0 - Characteristics of Employment, Australia, August 2019Source: 6302.0 - Average Weekly Earnings, Australia, Nov 2019.
They may be already a bit dated, but the latest data available all show that accommodation and food services, where restaurants are included, is the lowest paying industry.

To give readers an idea how poorly paid restaurant/hospitality workers are: the highest pay grade in the Restaurant Industry Award [MA000119], corresponding to 20+ yo permanent Cook Grade 5 attracts an hourly rate of $24.77 (Monday to Friday, between 6 am and 10 pm, penalties excluded). Its weekly wage (38 hours) is$941.10 (assuming he/she isn’t underpaid, in an industry where wage theft is endemic). To consistently make the average for accommodation and food services ($1,179.20) he/she needs to do overtime, work weekends or nights or a combination and after all that effort, his/her wages would still be about half the median weekly wage for mining ($2,300).

Those people work hard for their money, as the old song had it. They don’t get much for their efforts. Would a newly unemployed journalist be eager to take on an Introductory Grade position/kitchenhand ($19.49 an hour or$740.80 a week) at a restaurant?

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Last March 22 it was announced that the JobSeeker scheme (ranging between $530.40 and$670.05 per week, depending on the circumstances of the applicant) was made available to the unemployed until September. Although it was a great improvement relative to its previous incarnation (the NewStart Allowance) it wasn’t a fortune.

The top JobSeeker rate paid was 90.4% of the lowest pay in the lowest paying industry: kitchenhand. If you were a Cook Grade 5 you were already at least $271.05 short every single week, but your expenses did not shrink correspondingly. However, on July 21 a cut in JobSeeker was announced (apparently, from September the rates will range between$380.40 and $520.05 per week): that ratio was reduced to 70.2%. By then, our Cook Grade 5 will be at least$421.05 per week short.

And that leaves aside the notion of “mutual obligation”: the recipient of the JobSeeker allowance is forced to perform a series of tasks at the Government’s discretion, or the payment will be suspended. Among other things, he/she will have to apply for at least 4 positions under threat of payment suspension. If for whatever reason he/she decides to decline a job offer, no more money.

In Australia, when dealing with the unemployed the Government use the stick and the stick approach. No carrots here.

Anyway, that second announcement was expected. Scotty from Marketing and the Murdoch press-titute had already been busily selling the “job snobs” furphy.

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Madeleine Morris published that same day a strikingly similar piece (so much so that she even believes Zaczek “completely rip [sic] off” her story).

Morris is a ABC journalist (Zaczek, I imagine, could say that the ABC is a cultural Marxist propaganda outfit).

But her story wasn’t meant as a hatchet job on JobSeeker recipients, as Zaczek’s evidently was. I doubt Morris wants JobSeeker to be further cut down, as Zaczek may want. Or, more precisely, those weren’t Morris’ main goals. She isn’t a Right-wing nutter (Zaczek could say she is a Social Justice Warrior: more or less what I call a Leftish/Liberal with a strong identitarian bent).

Morris’ main goal was to highlight the plight of “visa workers” (i.e. foreign workers on temporary residence visas: international students, sponsored workers and working holiday-makers – aka backpackers) who received no support whatsoever from the COALition Government.

I have no objection to that. Her intentions are good. Indeed I share her concern. Much more importantly, the ACTU has done its level best to extend assistance to those workers.

But our agreement ends there. An example among others where we disagree: Morris’ presenting a capitalist as champion of visa workers, skin colour notwithstanding. While I find it appalling that she apparently can’t see anything odd in a capitalist “speaking up” for workers, I won’t insist on the subject.

What I really can’t let pass is Morris’ denigrating the unemployed – through a capitalist no less – as a means to boost – by contrast – the case of visa workers. In her effort to help the latter, she is willing to make the former collateral damage.

It’s not just the unfairness of it all, or that it won’t help visa workers, for they need assistance, not that others share in their misery. Nor is it just a matter of the sheer absurdity of the situation: those kids apply en masse to those shitty jobs out of despair, not because they are workaholics whose lifelong ambition is to wash dishes and take crap from entitled customers (assuming theirs is a decent boss).

It’s that it pits workers against workers. That’s irresponsible. That’s dangerous. It may make Morris feel good inside and look good to her peers, but it’s madness.

The fact that Zaczek and Morris used the same materiel should speak for itself. Must I draw a picture? Really?

What’s in a Name?

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Dedicated to Tahlea Aualiitia.

(source)
I seldom write about myself. I suppose you can say I’m a fairly private person (either that, or I’m a boring old bloke; take your pick).

Let me give you an idea what I mean. Blogger tells me that, since my first post (November 11, 2009), I have published 908 posts in this blog, over a variety of topics. Out of that number, only 11 contain personal references (this is the eleventh).

So, here goes. I am among the 49% of all Australians who, according to the 2016 Census, are either born overseas or have at least one parent born there. Coming from continental Europe, my surname, as you might suspect, is not common in Australia. Suffice it to say it is one of those family names full of unusual combinations of consonants, oddly arranged :-)

More to the point: being an uncommon name, Australians of all origins have a tendency to misspell and mispronounce it in random ways. Like the ABC’s Tahlea Aualiitia, I find that can be annoying.

Let me give you a well-known example (by Australians, at any rate): surnames of Armenian origin, like Berejiklian. The emphasis should be placed in the last syllable. Something like Berejikli-Anne.

Another example coming from a popular former SBS anchor-woman: Tegucigalpa (the capital of Honduras). In spite of her interest in fashion, that town has nothing to do with Gucci. It isn’t The-goo-tchi-galpa, it’s The-goo-c-galpa.

A last, more personal, example. For years a friend called me by a name that wasn’t mine. He must have thought it was common for people of my background. He wasn’t alone at that.

He only learned my name after introducing me to another person. I extended my hand to shake that person’s hand and told her my name.

“But I have been calling you such and such for years”, surprised, my friend said. “Why didn’t you tell me?”

I guess I never did because to teach people my name can be a bit of a bother, not worth the effort. Pace P.T. Barnum, I don’t find names that important anyway. In fact, in my friend’s case, the whole thing was rather amusing.

He, by the way, was born in Syria.

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You know how I definitely learned to overlook that kind of thing? Annastacia Palaszczuk taught me. If it weren’t for the Google autocompletion feature (see what I mean by unusual consonant combinations, yes?) I could not spell either name (I doubt Pala-che, the common pronunciation, is accurate).

Moreover I have exactly the same hard time with the names Bassingthwaighte (an Aussie celeb’s surname) and Schwarzenegger as I have with Soutphommasane (a local scholar). I may be a slow learner, but I apply equal opportunity.

If I tried hard I could learn, I suppose. After all, I can spell Ludwig van Beethoven. Why the difference? I am not sure. Perhaps because Beethoven’s fame has endured through the centuries, while the others’, with all due respect and for all their personal virtues, which I’m sure they have, may not.

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Tahlea Aualiitia feels much more strongly than I about that.

Not being a person of colour myself (and not being either young nor woman), I won’t presume to understand her. She may have her reasons. Her experiences may differ from mine.

What I can say is that I can’t cast the first stone on those who can’t spell my name.

And I can promise I’ll do my best to learn hers. I can’t promise I’ll succeed, however. If I fail, please think of that as a peculiarity of a silly old man, not as something deeper.

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Incidentally, the facts that (1) half of Australians were either born overseas or have at least one parent born overseas, and (2) more than a third of Australian media articles reflect negative views of minority communities, which Aualiitia highlights, raise some questions.

Is it possible that some of those media articles could have been written by persons with an overseas background? Could some of their authors even be persons of colour or members of minority communities?

Is Cruelty Required?

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Is it possible to have a society without cruelty?

That’s really the fundamental political question. (Economics, as you know, is a subset of politics, not different from it. So it’s also the fundamental economic question.)

It’s fair to say that there has never been a major society without cruelty baked into it, at least not since the rise of agricultural kingdoms about three thousand years after the invention of agriculture. Previous societies often had a lot of violence, but it’s not clear they all did, and some hunter gatherer band level societies seem to have had little cruelty.

But every major agricultural civilization has been cruel, and so has every major industrial society, though some are less cruel than others (insert reference to Scandinavia). Even those, however, are enmeshed in a system of industrial production that is, at best, exploitative, as in the case of conflict minerals, low paid workers, killed union organizers, and so on. Because it is not possible to run a decent society in the modern work in autarchy, even relatively kind societies are enmeshed in economic arrangements that cause great suffering hundreds to thousands of miles from them.

Cruelty is endemic even in good societies in the sense that our fundamental economic relationships are based on coercion; if you don’t work for someone else, probably doing something you wouldn’t do without the whip of poverty at your heels, and under supervision, well, you will have a bad life. School is based on coercion; do what you’re told when you’re told, or else, and so is work for most people.

That’s just the way our societies work, and while details vary, it’s more or less how they’ve worked since agriculture. Oh, the peasant may not have had close supervision, but they gave up their crops, labor, and lives under threat of violence, and they knew it well.

Even positive incentives are coercive. Get good grades and you’ll get a good job, etc… Please the mast… er, I mean, boss, yes, boss, and you may get a raise.

But a great deal of real cruelty lies behind the positive coercion in our major societies. American jails are startlingly cruel, filled with violence, rape, and fear. Chinese prisons aren’t so nice either. Police exist to throw you out of your house if you fail to pay the rent, which some double digit percentage of Americans are about to experience, because their society has mishandled an epidemic.

Sell cigarettes without the sanction of the state and your last words may be, “I can’t breathe.”

Our societies are based on positive and negative incentives. The amount of each varies with time and place. Finland right now has a lot more positive, and a lot less negative and a lot less consequences for disobeying. 50 years ago, the US put a lot less people in jail and gave those it allowed good jobs (white males) much better, nicer lives.

But there’s still always that threat in the background. And it’s always based on cruelty: “Bad things will happen to you, either actively or passively if you don’t go along.”

Now there are things we need to get done, collectively, in society. Build and maintain housing, grow and distribute food, keep the internet running (these days), but how much cruelty and coercion is required to do those necessary things? How much do you have to threaten people to get them to do those things? How cruel do you have to be to them if they don’t do them?

But another problem is that most of the coercion and cruelty in our societies has nothing to do with creating necessities like food and shelter and medicine and internet.

It has to do with making sure that some people have far more than they need, and others have far less. That some people have good lives with little coercion, while others live in constant fear. One problem with the boss, you lose your job, and you wind up homeless or in prison, and then even more terrible things happen.

Terrible things that are meant to happen, of course. We could lock up a lot fewer people and treat those few far better. We have more empty homes than homeless people and throw out at least a third of our food. No one need go hungry or homeless, and as for the internet, well, ISPs make close to 100 percent profit, so yeah, I’m pretty sure there’s no reason anyone should go without basic internet access.

So the cruelty in our societies is a choice. We can feed and house everyone, give everyone health care and have plenty left over, but we want billionaires and huge militaries or something, so we’re cruel. We’re cruel in the small details of everyday life (those maste…, er bosses) and we’re cruel in how we structure life, and it’s all a choice we’ve made.

Is it necessary? Must we be cruel? If we must be cruel, how cruel? What cruelty is actually needed, how much is just a preference or only required because we want very unequal societies?

Are we cruel of necessity?

Or desire?