It nearly broke my heart to hear that maths may be a required thing in linguistics, maths has pulled me back from a few opportunities in the past before linguistics, I'd been interested in engineering, marine biology, etc. I was just wondering if there was any work around, anything that would help me with linguistics that didn't require maths. Just. any advice at all, for getting into the field of linguistics with something as troubling as dyscalculia.The reader makes a good point I hadn't thought about. I remember my phonetics teacher telling us that she often recruited students into linguistics by telling them that it's one of the few fields that teach non-mathematical data analytics. That was something that appealed to me.
I'm not familiar with dyscalculia so I can't speak to how it impacts the study of linguistics directly. But even linguists who don't perceive themselves as "doing math" often still are, in the form of complicated measurements and such, like in phonetics and psycholinguistics. Generally though, I think that there are still many opportunities to do non-mathematical linguistics, especially in fields like sociolinguistics, language policy, and language documentation. Let us not forget that the vast majority of the world's languages remain undocumented so we need an army of linguists to work with speakers the world over to record, analyze, and describe the lexicons, grammars, and sound systems of those languages. We also need to understand better child language acquisition, slang, pragmatic inferences, and a host of other deeply important linguistic issues. It still requires a lot of good old fashioned, non-mathematical linguistics skills to study those topics.
Unfortunately, those are woefully underpaid skills as well. One of the reasons math is taking over linguistics is simple economics: that's where the money is. Both the job market and the research grant market are trending heavily towards quantitative skills and tools, regardless of the discipline. That's just a fact we all have to deal with. I didn't go to grad school in order to work at IBM. That's just where the job is. I couldn't get hired at a university to save my life right now, but I can make twice what a professor makes at IBM. So here I am (don't get me wrong. I have the enviable position of getting paid well to work on real language problems, so I ain't complaining).
Increasingly, the value of descriptive linguistic skills is in the creation of corpora that can be processed automatically with tools like AntConc and such. You can do a lot of corpus linguists these days without explicit math because the software does a lot of the work for you. But you will still need to understand the underlying math concepts (like why true "keywords" are not simply frequency searches). For details, I can highly recommend Lancaster University's MOOC "Corpus linguistics: method, analysis, interpretation" (it's free and online right now)
The real question is; what do you want to do with linguistics? Do you want to get a PhD then become a professor? That's a tough road (and not just in linguistics. The academic market place is imploding due to funding issues). There aren't that many universities who hire pure descriptive linguists anymore. Those jobs do exist, but they're rare. SUNY Buffalo, Oregon, and New Mexico are three US schools that come to mind as still having descriptive field linguist faculties. But the list is short.
If you want to teach a language, that's the most direct route to getting a job, but you'll need the TESOL Certificate too and frankly, those tend to be low paid, part-time jobs. Hard to build a secure career off of that.
That leaves industry. There are industry jobs for non-quantitative linguists, but they're unpredictable. Marketing agencies occasionally hire linguists to do research on cross-linguistic brand names and such. Check out this old post for some examples.
I hope this helps. I recommend asking this question over at The Linguist List too because I have my own biases. It's smart to get a wide variety of perspectives.
12 comments:
I find the premise bizarre. It's like asking if there are academic areas I could study that don't require that I know how to read.
If someone can't read, we recognize it as a critical weakness that has to be fixed. Inability to handle math should not be considered any different.
Anonymous, I understand your point. there are certain skills that are required to produce good research. That's fair. but it's also fair that certain skills are overemphasized. Math is important for modeling and analysis, but the majority of linguistics research is not math.
Since I actually know what dyscalculia is, I'd take a different perspective. Somebody with dyscalculia has no internal concept of number. They can learn to count by rote but have no feeling as to whether they're right or wrong due to an inability to estimate. So if a miscalculation of 23*43 will yield 17,210, someone with discalculia may not find that immediately strange. This makes maths very difficult to do - particularly when numbers are used.
However, to suggest that someone with this impairment could not be a good linguist strikes me as discriminatory for no good reason. Equally, a person with dyslexia or a person who is blind (Talmy) can be a good linguist.
Even a person who does not speak any English can be a good linguist. 100 years ago, if you didn't speak French, German, English, Latin, Greek (and possibly one or two more languages) you could not be a linguist...
We try to support learners with visual difficulties or English as a second language, why not those with dyscalculia?
But on the more general point of math and linguistics. You can absolutely do excellent linguistics with no math whatsoever. Functional and construction grammarians or even traditional philologists spring to mind. Sociolinguistics not so much really but discourse analysis is available.
You may have to deal with some formalisms to be able to use the tools of linguistics such as a corpus which is where some numbers are unavoidable (but a good buddy can help with checking those).
There's always some numbers floating about and some formalisms but I don't see why one should take an intro to calculus or even statistics to handle those.
The problem is that these requirements are introduced without thinking by people who never had to go through them. They then come up with syllabi that are full of irrelevant and off putting junk.
I'd say that if math is so important, why not have every single linguistics faculty member pass the exam before it is introduced for the students. I think we'd see some rapid reevaluation of such policies.
Dominik, LOVE IT! Asking faculty to pass the exams they give students would cause heart attacks across the academic world.
Your general point is very important. I see math as a skill, and one that is currently valuable, but not a necessary and sufficient condition for being a good linguist. I was a student of Len Talmy's, so your analogy really hit home.
I wish I could teach again because these kinds of issues are basic to a teacher's mission, but the fog of industry clouds the value of caring about what each person brings to a team.
I always tell students and potential students that one of the best things about linguistics is that it straddles both what we think of as traditional humanities and sciences, as you mention in your post. If a student wants to get into some high level applied linguistics and study acoustic phonetics, or do micro-level discourse analysis then it's up to them where they choose to settle on the spectrum.
A large number of linguistics I know who have jobs outside the academy have more or less crafted them for themselves - whether working in language centres of as consultants on commercial projects. I'd say the ability to self-motivate and create opportunities for yourself are far important skills in linguistics if you want to make some kind of career out of it - and of course there's no reason why you can't study linguistics to enhance your skills in another area, be it language teaching, editing, copy writing etc.
Dyscalculia should not automatically prevent anyone from pursuing linguistics, but it does perhaps require finding a department with staff who are attentive to learner needs, and an institution that provides a necessary level of student support.
The math you need for science very often very unlike what is taught in schools. Often it is not about numbers at all, but about other, richer worlds.
There are some things where number sense supported by clear thinking helps. For example, if you are a linguistic typologist, and are familiar with the fact that the number of different ways of shuffling a 50 card pack is a VERY BIG NUMBER, and you have a theory of language that says that there are 50 important settings in the language device, each with 10 or so different possible values, you will immediately see that the number of languages that are possible according to your theory vastly exceeds the number of different human languages that have ever existed, or that ever will exist before the sun explodes. Which alerts you immediately, to the weakness of the argument "This is not a possible human language, because we have never seen one like that". If your theory is right, there are going to be lots of languages that are possible but which never in fact happen. So yes, quantitative thinking is useful, but often you can get the insight without doing exact calculations. The people who are good at thinking like this may also have been good at doing sums in high school, or not.
Of course you can do linguistics without knowing
much math. Equally, you can, as I do, do linguistics without having any serious knowledge of non-indo-european languages. In both cases you run the risk of making elementary mistakes, and would be wise to get things checked by someone who has the skills that complement your own.
It is a fact of life that modern language technology is done mainly by people who have the kind of scientific and mathematical training that comes with an undergraduate degree in science or engineering. If that is the area you aspire to, you may wish to spend effort learning a little about the tools and ideas that they rely on. Not because you expect to become a full-scale expert, but because it helps in communication. And if this turns out to be prohibitively hard for you, you may decide to find an alternative way of contributing.
Equally, if you want to be a formal semanticist, it probably will help to know something of the non-numerical math and logic that people often get by taking philosophy classes, and if you want to be a psycholinguist, you will be hanging out with people who have psychology training, so you might want to take some classes to learn how they think.
In my experience phoneticians (such asKeith Johnson, Mary Beckman, Rob Fox, Cynthia Clopper, in particular, who all are or were at Ohio State) are particularly good at teaching people from diverse backgrounds the material they need in order to do good experimental work. From where I sit this material looks a lot like difficult maths, stats and physics, so I am impressed that the phoneticians are able to put it across to students who would never dream of taking an engineering class.
It is certainly true that the experience of 'being bad at maths' is a problem when you are in a class taught by some engineer or scientist who has never met anyone like that. But if you are not discouraged, and find a more patient and tolerant mentor, none of this is insurmountable.
Wow! This was an eye opening blog for me. I am an applied linguistic student right now and never really gave any thought to the math aspect of this career but you provided some very truthful insight about how to be successful with a job in this field.
Wow! I am a applied linguistic student and never thought about math being included in the field. But you provided some very truthful insight into how to be successful with a career in linguistics. This was very eye opening for me as I venture into finding a job in this field.
Lockhart's Lament: https://www.maa.org/external_archive/devlin/LockhartsLament.pdf
Read this if you "hate math".
quantumlinux: nice! I hadn't seen this before. Formal education has been a boon and a curse for many education disciplines, but perhaps none more so than math. Thanks!
Wow Chris, this is a great post! I am about to graduate with my bachelor's in Applied Linguistics and have been thinking about going into computer programming next. You've reaffirmed my inclinations. Just out of curiosity, as a linguist with only a four year degree, military experience (which imparts some technical skills) and fluent in Mandarin Chinese and Spanish (English is my first language), what kind of additional education would I need to start in a job like you've described (IBM)? I don't have the technical experience, though I know my way around the basics and understand some programming language. Do I need another degree in computers or are just the skills important?
As for the math, I think life is about perception. Math, just like language and science, is part of everything. I wonder if just perceiving something to be math causes the problem. I am very interested in the idea of dyscalculia and linguistics, because there are some that would say all language can be displayed using math, so would someone with dyscalculia be able to communicate properly, would there be any bleed over, and if not, it seems that there should be some connection to language and fixing the number problem? I do think you can do linguistics without math, personally, but, as you pointed out, if you want to get paid, you may need the math and technology.
Anyway, thanks and great post!
Anonymous,
Skills are critical. The best thing you can do is build something. Build a little tool that analyzes language in some way. Or integrate existing tools into pipeline. Take the Stanford NLP tool and create an app that lets people input 500 words of text and your tool displays Named Entities, parts of speech, dependency links. That sort of thing. These web apps already exist, but demonstrate that you can do it too. You could compete in a Kaggle competition, but that’s more machine learning/data science focused.
The connections between language and math are deep (as are those between language and music, BTW).
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