Short answer: yes. Long answer: the rest of this post. Linguistics is a science; but there are some parts of linguistics that don’t really act like people expect sciences to act, and that tends to confuse people.
Before I go over why linguistics is a science, I think it’s worth saying that I’m not arguing (and I am arguing; there are linguists who I know personally and by reputation who argue passionately linguistics is not a science) that linguistics is a science because sciences are “better”. I’m arguing because there is an inherent difference between how you do science and how you study the humanities. Your aims are different and what you need to do to accomplish those aims are different. I’m arguing that the ultimate aims of linguistics are science-type and not humanities-type or plant-typeand therefore our methodology should match those aims.
Today, I’m going to introduce you to two of my very good friends in linguistics: “metalinguistic” and “recursive“. They’re not that closely related, but they tend to get asked if they’re sisters a lot. Why?
Well, metalinguistic knowledge is knowing about language, and the fact that you can read this shows that you must have some metalinguistic knowledge. But this blog (and the field of linguistics as a whole) is concerned with knowing about what you know about language, i.e. meta-metalinguistic knowledge. And just just talking about that, I’m adding another level. My discussion of what we know about linguistics gets us all the way to meta-meta-metalinguistic knowledge. And by talking about that… You get the picture.
The picture is also recursive. One of my favorite examples of recursivity is PHP. Originally, the acronym stood for “Personal Home Page”, but it now stands for “PHP: Hypertext Preprocessor“. What does the PHP in that stand for? Why, for “PHP: Hypertext Preprocessor”, of course. (Repeat ad nauseum, or at least ad getting-punched-in-the-arm.) Or, wait, maybe it’s cats looking at cats looking at cats looking at cast looking at cats…
So you can see how they’re related, right? They’re both all about making you feel dizzy and then fall down, or maybe puke if you get motion sickness.
But what you may not know about recursivity is that it’s a very important process in linguistics as well. How so, you might ask? Well, remember in the days of yore (yesterday was totally a day of yore) when I told you all about generativity? Recursivity is a great example of one of those generative processes. You can have a recursive sentence that just goes on forever. How about when you’re describing where you learned something?
I heard it from Jen.
Well, what if Jen heard it from someone else?
I heard it from Jen who heard it from Ian.
And then you find out that Ian wasn’t the originator either.
I heard it from Jen, who heard it from Ian, who heard it from Zach, who heard it from Nick, who heard it from Clarice…
And so on and so forth.You can pretty much keep going on infinitely. You can do it with other types of phrases to.
Get the butter from the fridge by the stove behind the water buffalo next to the peat coal kiln…
Chomsky argued that recursion is the fundamental characteristic of human languge, and this has been the cause of some debate. (Pirahã may be the most argued-about Non-Indo-European language ever.) So recursion has two main uses in linguistics. The first is as a generative process that allows speakers to form infinitely long sentences, and the other is to use language about using language about using language about using language about using language about using language about using language…
This is obviously a question that I, as someone who’s going to shortly hold such a degree, get asked a lot. Fortunately, there are a lot of possible answers! I’m going to start with the obvious ones and then start surprising you.
Obvious answer #1: Get another degree in linguistics!
If you’re really in love with the subject, getting a doctorate and competing for the tiny number of teaching positions in the field is certainly an option. Imma be straight with you, though: it’s very, very hard work; very, very competitive and very, very low paying for the amount of specialized training you need. (A PhD usually takes between four and six years…if you manage to finish at all.) Oh, and did I mention that you’ll be expected to do original, groundbreaking research and consistently get it published in addition to your teaching load? Yeah… unless you’re 100% sure that’s what you want to do, you should probably keep reading.
Obvious answer #2: Teach computers how to language!
Do you like computers? Do you like linguistics? Do you like the thought of eventually having a job and making money? Holy balls of yarn, do I have a career for you. Super-high employment rates, cutting edge research, making all the best and newest toys… yeah. Plus, if you have a good background in both computer science and linguistics (a surprisingly large number of people only have a computer background) you’ll be a very competitive candidate.
Obvious answer #3: Help children and adults overcome speech problems!
If you’ve always wanted a career where you help people, you should look into Speech-Language Pathology. Sometimes, someone doesn’t acquire language correctly, or they develop a problem with language. Speech pathologists work with patients to help them acquire language or to relearn language. You’ll need at least a masters, but most people find it to be a very rewarding career.
Obvious answer #4: Work as a translator!
So I wrote earlier about the difference between a linguist and a translator, but being a linguist can really help you with translation as well, particularly if you’re interested in working on bilingual dictionaries. Of course, demand for translators varies from language to language, and you do have to be fluent in at least two languages.
Obvious answer #5: Teach languages!
If you’re interested in teaching anyone to acquire a second language, whether it’s English or something else, having a linguistics background can be very, very helpful. Think back to any foreign language classes you might have taken. Wouldn’t it have been better if your teacher had been able to tell you exactly what you were supposed to be doing with your mouth, instead of vaguely telling you what letters it was like and then that “You’re doing it wrong”? With a background in linguistics, you can really explain how things work in the second language, and that will really help your students.
So those are the biggies. You’ll need other skills for most of them, but linguistics will help you a lot. And, hey, linguistics classes are fun! But what other careers can linguistics help you with? Well…
Be a lawyer! A background in linguistics is actually a really strong choice for someone heading to law school. Why? Well, law is all about using language really, really carefully and communicating effectively. An academic background in linguistics will help you do that.
Make up languages! Now, this is a bit of a niche, but there is more than oneperson who has been paid for designing “alien” languages for flims. You’ve heard of Na’vi and Klingon, I presume? They’re actually legit artificial languages with grammars and everything.
Write standardized tests! If you’re American, you’ve probably taken or will take the SAT’s at some point. Fun fact: most of those language-based questions were written by linguists, who know how to ask questions designed to get at very specific pieces of linguistic knowledge.
Do anything you like! Really, linguistics training gives you a great set of skills. You can analyze large sets of data, deduce the rules that would generate them and then write about them in a clear way. That’s a really useful thing to be able to do.
If you answered “Einstein’s less famous brother, Einbert?” you wouldn’t actually be too far from the truth. It’s Noam Chomsky. He’s so famous his name comes pre-installed in Microsoft Word’s spell checker. (Did you mean “chomp sky?”)
If you’ve got a good history or government background, you may be thinking, “Oh yeah, the anarchy guy.” He may be, but his greatest intellectual achievement has nothing to do with anarchy and everything to do with linguistics. That achievement would be generativity.
Gen-er-a-tiv-i-ty. Write it down, it will be on the test.
Generativity was a game-changer for linguistics. Before that point, linguistics was basically phrenology, which I’ve mentioned before. Phrenology is to modern linguistics what naturalism is to modern biology. Phrenologists collected knowledge about languages haphazardly, without a whole lot of underlying theoretical structure. I mean, there was some, (I’ll talk about what the brother’s Grimm did on their weekends off later) but it was pretty confined. And a lot of it, let’s be honest, was about proving that Europe was best. The monumental Oxford English Dictionary is a good example of that mindset. They wanted to collect every single word in English language and pin it neatly to the page with a little series of notes about it and a list of sightings in the wild. It was, and remains, a grand undertaking and a staggering achievement… but modern linguists aren’t collectors anymore.
That’s because the end goal of modern linguistics is to solve language. The field is working to put together a series of rules that will actually describe and predict all human language. Not in the mind reader, fortune teller sense of predict. I mean that, with the right rules, we should be able to generate all possible sentences. In a generative way. By using generativity.
So why is this important?
Lots of reasons! Here, let me list them, because lists are fun to read.
This turned linguistics from an interesting hobby for rich people into a science. If you have rules, you can make predictions about what those rules will produce and then test those predictions. Testing predictions is also known as science. It’s also something that linguistics as a whole has been a little… hesitant to adopt, but that’s another story.
Suddenly computers! Computer programming is, at its most basic level, a series of rules. Linguistics is now dedicated to producing a series of rules. Bada-bing, bada-boom, universal translator. (It doesn’t work that way, but, in theory, it eventually can.)
Now we have a framework that we can use to figure out how to ask questions. We have a goal. Things are organized.
Now for the promised test.
What term is used to describe the current goal of linguistics; i.e. to generate a set of rules that can accurately describe and predict language usage? (Seriously, I’m not going to give you the answer. Just scroll up.)
It’s not just that language is continuous, it’s that language that’s discrete is actually impossible to understand. I ran across this Youtube video a while back that’s a great example of this phenomenon.
What the balls of yarn is he saying? It’s actually the preamble to the constitution, but it took me well over half the video to pick up on it, and I spend a dumb amount of time listening to phonemes in isolation.
You probably find this troubling on some level. After all, you’re a literate person, and as a literate person you’re really, really used to thinking about words as being easy to break down into “letter sounds”. If you’ve ever tried to fiddle around with learning Mandarin or Cantonese, you know just how table-flippingly frustrating it is to memorize a writing system where the graphemes (smallest unit of writing, just as morpheme is the smallest unit of meaning, phoneme is the small unit of sound and dormeme is the smallest amount of space you can legally house a person in) have no relation to the series of sounds they represent.
Fun fact: It’s actually pretty easy to learn to speak Mandarin or Cantonese once you get past the tones. They’re syntactically a lot like English, don’t have a lot of fussy agreement markers or grammatical gender and have a pretty small core vocabulary. It’s the characters that will make you tear your hair out.
But. Um. Sorry, got a little off track there. Point was, you’re really used to thinking about words as being further segmented. Like oranges. Each orange is an individual, and then there are neat little segments inside the orange so you don’t get your hands sticky. And, because you’re already familiar with the spelling system of your language, (which is, let’s face it, probably English) you probably have a fond idea that it’s pretty easy to divide words that way. But it’s not. If it were, things like instantaneous computational voice to voice translation would be common.
It’s hard because the edges of our sounds blur together like your aunt’s watercolor painting that you accidently spilled lemonade on. So let’s say you’re saying “round”. Well, for the “n” you’re going to close off your nasal passages and put your tongue against the little ridge right behind your teeth. But wait! That’s where you tongue needs to be to make the “d” sound! To make it super clear, you should stop open up your nasal passages before you flick your tongue down and release that little packet of air that you were storing behind it. You’re totally not going to, though. I mean, your tongue’s already where you need it to be; why would you take the extra time to make sure your nasal passages are fully clear before releasing the “d”? That’s just a waste of time. And if you did it, you’d sound weird. So the “d” gets some of that nasally goodness and neither you or your listener give a flying Fluco.
But, if you’re a computer who’s been told, “If it’s got this nasal sound, it’s an ‘n'”, then you’re going to be super confused. Maybe you’ll be all like, “Um, ok. It kinda sounds like an ‘n’, but then it’s got that little pop of air coming out that I’ve been told to look for with the ‘p’, ‘b’, ‘t’ ‘d’, ‘k’, ‘g’ set… so… let’s go with ‘rounp’. That’s a word, right?” Obviously, this is a vast over-simplification, but you get my point; computers are easily confused by the smearing around of sounds in words. They’re getting better, but humans are still the best.
So just remember: when you’re around the robot overlords, be sure to run your phonemes together as much as possible. It might confuse them enough for you to have time to run away.
All right, first I’d like to apologize for the title. The opposite of discrete is not indiscreet, but continuous, and continuous is what language, especially speech, is. By continuous, I mean that it doesn’t come out in separable chunks; it’s more like a stream of water than a stream of ice cubes. In fact, English itself discriminates between things that are discrete and continuous; discrete things are called count nouns because (gasp!) you can count them, and continuous things are called mass nouns. You can count ice cubes and words, but you can’t count water or language unless you assign them units.
“But wait,” I can hear you protest. “Language is discrete. I’m speaking in sentences, that are made up of words that are made up of letters.” And you’re right. For you, your language is made up of units that are psychologically real to you. Somewhere between the speaker vocalizing the words and you parsing them, you segment them using the rules that you’ve mastered. It’s a deeply complex process and one that we still don’t completely understand. If we did, we’d be able to write speech recognition programs that wouldn’t give us errors like “the wells were gathered and planning” for “the walls were dark and clammy”. (True life. I got that very error not that long ago.)
Here, let’s look at some data. Here’s the waveform that shows the wave intensity, or loudness, of a native speaker of English saying “I am an elephant.”
Can you pick out the part of the speech signal for each of the words? Here, let me help you.
So… if speech really is discrete, wouldn’t expect four separate bumps in loudness for the words, with silence in between? (Maybe with a couple extra bumps on the end for the laugher.)
Instead, what we get is pretty much a constant rush of noise that you rely on the vast amount of knowledge you have about your language to decode accurately. Take out that knowledge and you get something completely incomprehensible. And there’s a really easy way to show this, just listen to someone speaking a language you aren’t familiar with.
That’s Finnish and if you speak it well enough to understand everything he just said, I’d like to extend some mad props unto you; Finno-Ugric languages are as hard as ice-cream from a deep freezer. But to get back to the point, what observations can you make about what you just heard?
The speaker was speaking super-quickly.
There didn’t seem to be any pauses between words
Basically, it was like standing in front of a language fire hose.
For people who don’t speak your native language, you sound very similar. They’re not speaking any more quickly in Hindi or Mandarin or Swahili or German than you are in English, you just don’t have a metalinguistic framework to help you cut the sound-stream into words, slap it up on a syntactic framework and yank meaning out of it.
To figure out why you lose your voice, let’s start by covering what happens when your voice is acting normally.
All sound is vibration. Like a bunch of people standing in loosely-spaced crowd, air molecules are pretty much doing their own thing. Then the source of the sound, like a big bully, or maybe a bunch of bulls, pushes some people in the back of the crowd, and they push the people in front of them, etc. etc., until the last person jumps in your ear and bounces off your eardrum. Kinda like this:
So if all sound is vibration, something has to start it off. In a violin, it’s the friction between the bow and strings that causes the strings to vibrate. In a tuba or trumpet, it’s the vibration of the musician’s lips against the mouthpiece; if you just blow into a tuba without a proper embouchure (funny music-playing face), you’re not going to get any sound out of it. In you, it’s the vibration of your vocal cords that produce sound.
That’s them. But it’s actually a two-step process.
Step one: Tighten the vocal folds. This is like tuning a guitar; you can change the pitch of your voice based on how taut your vocal cords are. If you put your hand on your throat and sing a low note and a high one in quick succession, you can actually feel your muscle rotating as it adjusts the length of your vocal cords.
Step two: Vibrate those vocal folds. Now, you might think, based on step one, that you use your muscles to wiggle them back and forth really fast. Nope. You vibrate your vocal cords by blowing air through them. The more air, the louder the sound, the sooner you have to take a new breath.
So based on this, there are two possible ways to lose your voice. You can run out of air–which, unless you’ve had the breath knocked out of you, is a pretty straightforward problem to fix–or your muscles can crap out. And that’s generally why you lose your voice. The muscles in your larynx are just like any other muscles. If you use them hard enough, long enough, they’ll strain and, bam, you’ll lose your voice. Of course, this is just for run-of-the-mill I’ve-been-screaming-at-a-football-match type voice loss. Anything that messes with those muscles will cause you to lose your voice, and that can include things like aging, smoking (seriously, don’t smoke), damage to the larynx during surgery or even a tumor.
But unless you’re at risk for one of those things, your voice will come back once the strained muscles have had time to heal. In the meantime, I recommend carrying around a small whiteboard and whiteboard marker (It’s got good visibility, you can write easily and quickly, and you can write large enough that people not directly next to you can read it.) and learning how to finger spell.