Some thoughts, as an academic mathematician who got his Ph.D. three years ago:
First of all, the author is right in one aspect, in that bad writing -- and also bad speaking -- are too widely tolerated in mathematics. Most departments have a regular colloquium, where the entire point is to listen to a talk to mathematicians outside your specialty. Many speakers do a good job, but there are some who will start out with "Let M be a symplectic manifold, let omega be the associated bilinear form, let X be the ring of differentials, ..." [ugh.]
And yet I think there is more pressure to write and speak well than there is to do so poorly. Certainly as a graduate student I was pressured by my advisor to explain things clearly, to add examples and exposition to my papers, to omit technical details from talks, and in general to keep in mind the perspective of the non-expert. The author complains, "Submit a paper with two consecutive sentences of exposition and watch how quickly the referee gets on you for it." But I have not experienced this myself, nor heard this complaint from anyone until this article.
Moreover I can think of lots of well-known books that are loaded with exposition. Representation Theory by Fulton and Harris comes particularly to mind. Of course, there are many books which are notoriously terse as well. (Any HN'ers tried to hack their way through Baby Rudin?)
Indeed, there are many mathematicians who make quite an effort to write and speak well, and largely succeed, and the author seems unable to identify any mathematical writing which he does approve of. If we are doing a bad job, please give us specific examples of what you would like to see instead.
The fact is that learning new math is just damn hard, even from well-written papers. I think that we could do a much better job of explaining our work to others. But, IMHO, this article overstates the problem, and omits to propose any practical solutions.
"Any HN'ers tried to hack their way through Baby Rudin?"
Yup. Been there; done that!
Yes, it needs some 'explanation':
Q. Why do we care about metric spaces?
A. Eventually they are important, e.g., in Hilbert and Banach spaces. For now, they are the vanilla case of a topological space.
Q. Why do we care about topological spaces?
A. Because they are the nicest way to describe continuity. So a function from one topological space to another is 'continuous' iff (from Halmos: if and only if!) for each open set in the range space its inverse image under the function is an open set in the domain space. That's a nicer, and more general, definition than converging sequences (which are not quite as powerful, but examples are a bit bizarre) or epsilon-delta arguments from limits in calculus.
Q. An 'open' set?
A. A 'topology' is defined as a collection of sets it calls 'open'. So, really the topology is defined just by some open sets. A good and easy example of an open set is an open interval, say, (0,1) on the real line. That set is 'open' in the 'usual' topology (in principle there can be others) for the real line.
Q. Why do we care about continuity?
A. As in G. Simmons, the two main pillars of the 'analysis' part of math are linearity and continuity. They are assumptions that commonly hold in practice and that give some of the most powerful and useful results. In particular, in Baby Rudin, if a real valued function of a real variable is continuous on a closed set, then the function is also uniformly continuous, is bounded, actually achieves its upper and lower bounds, and its Riemann integral exists and is finite. All nice stuff.
Continuing, all such functions form a vector space (a 'linear' space); the difference to two such functions is again such a function; and the maximum value of the difference forms a norm. So, those functions form a normed linear space. If a sequence of such functions converges in this norm, then the limit is also such a function -- i.e., a uniform limit of continuous functions is continuous. So, the space is 'complete' in this norm. So, we have the leading example of a Banach space (a complete, normed linear space). Then we can show the Hahn-Banach result and see the tasty, ice cream and cake dessert examples in Luenberger, 'Optimization by Vector Space Methods' including Kalman filtering, results for 'least action' in physics, more in deterministic optimal control, etc. So, these are some of the coming attractions of those first chapters in Baby Rudin on metric spaces, topology, open sets, continuity, etc.
Q. A 'closed' set?
A. Back to the real line where (0,1) is an open set, [0,1] is a closed set, So, it's closed and bounded. Presto: It is the leading example of a 'compact' set, which is almost as nice to work with as a finite set. In particular, any infinite subset of a compact set has a limit point in the set which is the key to uniform continuity, the existence of the Riemann integral, and more. The nicest definition of a compact set is that each open cover has a finite subcover, and this definition works also in metric spaces and topological spaces.
So here is an explanation of what the first chapters of Baby Rudin are all about. Print a copy and pin it to the wall in any math department that teaches a Baby Rudin course!
>Sadly, the rot extends to math textbooks as well, which, with very few exceptions, are simply horrible. I mean really, really bad. It is commonly considered a great faux pas to actually explain what you're doing. You will be accused of being overly wordy if you do anything other than produce an endless sequence of definition-theorem-proof. Mathematicians too often seem to take absolute delight in being as opaque as possible. I can't tell you how many times I have heard friends and colleagues praise for their concision textbooks which, to my mind, are better described as harbingers of the apocalypse. If, as a textbook author, you place yourself in the student's shoes and try to anticipate the sorts of questions he is likely to have approaching the material for the first time, a great many of your colleagues will say that you have done it wrong.
As someone who only ever encounters math as a tool rather than a a great passion or source of intellectual stimulation, it makes me really happy to see this said out loud.
Ugh, I had a physical chemistry textbook like that. All math, very little explanation of why or how to apply the math. I remember reading one chapter over and over again, desperately attempting to glean what shreds of meaning I could from the bare minimum of information presented. It was like trying to solve a puzzle.
>As someone who only ever encounters math as a tool rather than a a great passion or source of intellectual stimulation, it makes me really happy to see this said out loud.
From the perspective of a mathematician, I'd like to see textbooks strike a happy medium between page after page of explanation and absolute terseness.
When I'm taking an intermediate level course, I know that the math I encounter may rarely be useful on its own. It should be sufficient to say "you won't even think about this until you take analysis!"
I think the biggest mistake universities make is to offer one type of math instruction. I still remember taking a linear algebra class that had mathematics majors, engineers, and secondary education majors(!) all in the same class! The professor taught it in a way that I very much appreciated -- a large focus on theory and concepts, and much less focus on application & concrete problems. Of course, I and the math majors loved this, while the education majors & engineers detested it.
It might've been more difficult, but I believe that everyone would've benefited from instruction that was tailored to what people would need & could appreciate -- the engineers could learn applications of linear algebra, the secondary education majors could learn how to teach linear algebra, and the mathematicians could learn the theory behind linear algebra. Instead, we had one class that a subset was guaranteed to hate.
Jargon is a necessity in all fields. Otherwise we would have to use only existing words to explain all of our new concepts.. Math - and some physics - necessarily deal with things that we don't have an intuition for. I think that those subjects are going to be inherently less approachable for people outside of those sub-disciplines because their prior knowledge is much less help.
Now, with that said, it's probably true that some math papers could be improved with more exposition. But I think that excluding the layman from new math research is probably an inherent problem, not an accidental one. Improved exposition would be to help other mathematicians who are not in that sub-discipline to understand the broader field.
(which I learned about from a comment here on HN, thanks) does a good job of demonstrating how a mathematician who makes new discoveries has to invent a new language for describing those discoveries. Then the mathematician has to relentlessly practice communicating those results first to other professional mathematicians, helping them to see the connections between their research and the new research results. Mathematicians who work hard at communicating with other mathematicians, Thurston says, can help greatly with the progress of mathematical research.
After edit: Paul Halmos, quite a well regarded mathematician who by his own self-evaluation was not in the same league as Fields medalists, wrote in his "automathography"
that he learned a lot of mathematics as he continued his career after his Ph.D. degree by "reading the first ten pages of a lot of mathematics books." Sometimes he could only get ten pages into a book by another mathematician before he was lost, but by reading dozens and dozens of books, ten pages each, he gained more conceptual foundations in more areas of mathematical research and could gradually apply what he self-learned to advance his own research. I strongly encourage students I know to follow that same strategy of reading at least the introductory portion of many books on subjects they desire to know. Don't just read what your professor assigns you to read. Go to the library and read widely. Read as far as you can before you get stuck, and then find another book and start reading it from the beginning until you get stuck again. Eventually, you will find that you can read harder books, and go farther before getting stuck.
About Halmos, that is quite scary. I happened to be reading "Finite-Dimensional Vector Spaces" the last few days and while the material is pretty elementary, Halmos is obviously very good, and the idea that there are people leagues ahead of him is amazing...
tokenadult, you're the only other person I know who read that book. I found it dusty in a university library years ago while I was pursuing my PhD and it was an eye opening read. I'd love to buy a copy ,but it is so expensive. But thanks for reminding me of it.
While it is true that there are many examples of bad writing in mathematics, it is not true that unclear writing is glorified over clear exposition. To the contrary, authors like Paul Halmos are rightly celebrated as great expositors, e.g. see his books like Naive Set Theory, Finite Dimensional Vector Spaces, Measure Theory etc. and his expository writing such as "How to Write Mathematics" and "How to Talk Mathematics":
Some other books I like are Sheldon Axler's Linear Algebra Done Right, Real Mathematical Analysis by Charles Pugh, and the three books on manifolds (Topological Manifolds, Smooth Manifolds and Reimannian Manifodls) by John Lee, but there are many other well-known books that are clear in their exposition.
Edit: Part of the issue is also the approach of the reader, i.e. is s/he there to learn mathematics, where the goal is to explore the mathematical world, or is s/he there to use the mathematics to explore the physical world? That should guide questions like "What is the point of studying vector spaces?" The motivation to study vectors spaces (and other mathematical topics) may need to come from other courses, e.g. on mechanics, and the course/book on vector spaces would serve to give in-depth knowledge of the particular topic.
For me, at least, once I understand it, the notation makes perfect sense and I find it far more expeditious and precise to express my idea in the domain language of the field. The problem is that getting to the point of becoming proficient in the formalism of a field can take an extremely long time (for me), and has the unfortunate side effect of making me feel like a total idiot for not understanding it sooner, once I understand it.
The fact is, mathematics deals with constructs with extremely specific properties. These properties can be completely and soundly stated without ambiguity quite succinctly in the formalism of the field. Once I'm comfortable with the formalism, trying to express it in English is awkward, imprecise, and generally just extremely verbose. It can then be a frustrating experience going back and convey the idea to colleagues or others in prose.
When I come across some academic mathematics paper, even if I'm somewhat familiar with the field, I generally find other things far more interesting, like the coffee stain on the floor. Effectively reading a mathematics paper requires a print out and a pencil to work through some of the definitions and take notes for yourself, and maintaining laser-like focus for a sustained period of time (more intense than programming a rather difficult problem, imo).
That paper referenced is WAY beyond most people, as the article noted. To understand what the person is going to say, you had better already know what those terms mean, and be able to explain them. If you can't, then you have no basis for the rest of the paper anyhow.
Why on Earth would a common joe want to read that paper anyhow? What could it possibly do for them?
I don't see toning down the jargon as being advantageous to the common Joe, but it could be advantageous to mathematicians outside the extremely immediate field. For instance I'm guessing that any mathematician will understand "immersed surfaces in 4-manifolds" and maybe even "homology cylinder" even if the layman won't. However, how many mathematicians know "Whitney move" and "Whitney tower" and "Arf invariant" and "Milnor invariant" and "Sato-Levine invariant" and so forth? Some tiny fraction. A little less jargon could make your paper accessible to ten or a hundred times as many people.
Of course, quoting the abstract is a little unfair. The abstract needs to be short so there's no time to explain what the hell a Sato-Levine invariant is. Perhaps the actual paper is a lot clearer.
I wish the author had, as a PoC, taken one of the papers in his career as a maths PhD, and rewritten it so that a non-mathematician (say, one with only a CS or physics degree) can immediately understand it.
I don't say it's impossible, but it should make visible all the difficulties on the way.
i wrote a few 'transl(iter)ation' from math/physics papers to be understandable by a CS degree, and yes, the jargon is in the way for a CS student. The biggest leap is to associate a greek letter with a definition. a CS student, in my experience, wants the letter (short variable name) to be a meaningful word (longer descriptive variable names). i am not a mathematician. physicists, in my experience, had no problem though.
I'm of two minds about this. On the one hand, I think it's a misconception to think that a nothing-but-the-proofs-and-definitions approach makes it any harder to understand math. Math is just freakin' hard. Making it fluffier only makes it seem easier if you confuse page rate with learning rate. On the other hand, knowing the motivation and context for a piece of mathematics is very pleasant, makes it easier to focus and work hard on the math itself, and occasionally can be as important as knowing the math itself. My ideal math text would contain a lot of exposition at the beginning of each chapter and then the traditional dry presentation of the mathematics itself. I wouldn't want the exposition and the mathematics mixed too finely.
Couldn't they spend a little more time and write an expository background on papers? Certainly it would be the easiest part for an expert to write.
I was reading several papers in the EE field the other day. Most of them all spend the first page restating the problem in practical terms and then have a substantial section reviewing the prior techniques. I found this darned helpful, especially since the primary material was often not online.
Are they worried about wasting paper, or do they actually want to be uninviting?
As long as mathematicians are dependent upon finding a small clique to work with, there are no pressures to make themselves understood by more than a small number of people who have a lot of common knowledge. Thus jargon will proliferate.
One of the reasons that I prefer the reprints of much older texts by the great mathematicians is that in most cases (all?) the writing meets the conditions that are listed as desired. The previous sentence clearly doesn't---sorry! The books from Chelsea and for that matter Dover may be old, but they are accessible.
I had a stint where I bought and tried to read a few dozen cheap $8-$14 Dover math books. There is a reason most of these books were not revised and republished before their copyright expired and they became Doverable, and it is not because they were perfect originally. Poor 1940s typesetting, only the barest sketches of images, and linguistic quirks that are not present in modern language.
The recommended booms from my high school and college courses were much better.
Of course, 90% of everything is crap, so
there logged be a few gems in there.
The $3 copies of Plato et al were better than the math books.
Without jargon, it would be roughly impossible to talk about compound mathematical structures. But I certainly agree that more exposition and a greater number of worked-out examples are a great help when trying to understand abstract math.
It would also be great to have papers written in a hyperlinked format (after so many years of the web...) so that when you click on a jargon term, you get something like a Wikipedia article about that concept with a few examples and some exposition. Wikipedia itself would be fine with me, though academics might want more official peer review (see Scholarpedia).
Often the jargon is unavoidable because "common sense" definitions are actually subtly incorrect. This does not mean that examples and motivation have no place, but there is definitely a chicken/egg problem and starting by stating definitions is an easy and expedient way to overcome it.
Also, the best examples usually link seemingly disparate fields. If you can't assume the reader has a background in these fields, it can be difficult to even state the link. I sometimes find myself writing "readers unfamiliar with X can think of it as [intuitive but imprecise definition]".
I can't stand technical jargon or people who use without regard for their audience.
The only purpose of jargon is to make a conversation exclusive to only those who know the language. If your purpose is to educate or collaborate or truly communicate, then jargon is harmful.
Jargon is just a time-saving and precision measure. Try doing without it sometime - it's painful.
It is totally unavoidable as long as people keep communicating with words. The better solution is not to complain about it, but to ask for definitions (recursively) - and then you can reap the time-saving and precision benefits of the terminology, too.
In an overwhelmingly important sense, pure math has the least 'jargon' of any field. The reason is, math exposition has an absolute requirement: Each use of a word not the same as just its dictionary meaning becomes a 'term' and just MUST be defined, and 'well-defined', before it is used. So, what the article is calling 'jargon' is just such terms, but in well written pure math they all have rock solid definitions, and math is the unique field where this precision is true.
For the rest of the complaints about 'jargon', these are essentially just necessary given that math, due to its precision and age, is now by far the deepest field of study. So, there are a LOT of terms defined.
If the article wanted to claim that for each math result or paper there is a 10,000 foot intuitive view that can be explained in 90 seconds to just anyone on a street, then okay, but the article did not do this. This claim is not quite true, but it is close enough so that some such explanations, maybe with some pictures, and some connections with more elementary topics, can be useful, even in research papers. But the article didn't make this claim, either.
[+] [-] impendia|15 years ago|reply
First of all, the author is right in one aspect, in that bad writing -- and also bad speaking -- are too widely tolerated in mathematics. Most departments have a regular colloquium, where the entire point is to listen to a talk to mathematicians outside your specialty. Many speakers do a good job, but there are some who will start out with "Let M be a symplectic manifold, let omega be the associated bilinear form, let X be the ring of differentials, ..." [ugh.]
And yet I think there is more pressure to write and speak well than there is to do so poorly. Certainly as a graduate student I was pressured by my advisor to explain things clearly, to add examples and exposition to my papers, to omit technical details from talks, and in general to keep in mind the perspective of the non-expert. The author complains, "Submit a paper with two consecutive sentences of exposition and watch how quickly the referee gets on you for it." But I have not experienced this myself, nor heard this complaint from anyone until this article.
Moreover I can think of lots of well-known books that are loaded with exposition. Representation Theory by Fulton and Harris comes particularly to mind. Of course, there are many books which are notoriously terse as well. (Any HN'ers tried to hack their way through Baby Rudin?)
Indeed, there are many mathematicians who make quite an effort to write and speak well, and largely succeed, and the author seems unable to identify any mathematical writing which he does approve of. If we are doing a bad job, please give us specific examples of what you would like to see instead.
The fact is that learning new math is just damn hard, even from well-written papers. I think that we could do a much better job of explaining our work to others. But, IMHO, this article overstates the problem, and omits to propose any practical solutions.
[+] [-] rudiger|15 years ago|reply
[+] [-] NY_USA_Hacker|15 years ago|reply
Yup. Been there; done that!
Yes, it needs some 'explanation':
Q. Why do we care about metric spaces?
A. Eventually they are important, e.g., in Hilbert and Banach spaces. For now, they are the vanilla case of a topological space.
Q. Why do we care about topological spaces?
A. Because they are the nicest way to describe continuity. So a function from one topological space to another is 'continuous' iff (from Halmos: if and only if!) for each open set in the range space its inverse image under the function is an open set in the domain space. That's a nicer, and more general, definition than converging sequences (which are not quite as powerful, but examples are a bit bizarre) or epsilon-delta arguments from limits in calculus.
Q. An 'open' set?
A. A 'topology' is defined as a collection of sets it calls 'open'. So, really the topology is defined just by some open sets. A good and easy example of an open set is an open interval, say, (0,1) on the real line. That set is 'open' in the 'usual' topology (in principle there can be others) for the real line.
Q. Why do we care about continuity?
A. As in G. Simmons, the two main pillars of the 'analysis' part of math are linearity and continuity. They are assumptions that commonly hold in practice and that give some of the most powerful and useful results. In particular, in Baby Rudin, if a real valued function of a real variable is continuous on a closed set, then the function is also uniformly continuous, is bounded, actually achieves its upper and lower bounds, and its Riemann integral exists and is finite. All nice stuff.
Continuing, all such functions form a vector space (a 'linear' space); the difference to two such functions is again such a function; and the maximum value of the difference forms a norm. So, those functions form a normed linear space. If a sequence of such functions converges in this norm, then the limit is also such a function -- i.e., a uniform limit of continuous functions is continuous. So, the space is 'complete' in this norm. So, we have the leading example of a Banach space (a complete, normed linear space). Then we can show the Hahn-Banach result and see the tasty, ice cream and cake dessert examples in Luenberger, 'Optimization by Vector Space Methods' including Kalman filtering, results for 'least action' in physics, more in deterministic optimal control, etc. So, these are some of the coming attractions of those first chapters in Baby Rudin on metric spaces, topology, open sets, continuity, etc.
Q. A 'closed' set?
A. Back to the real line where (0,1) is an open set, [0,1] is a closed set, So, it's closed and bounded. Presto: It is the leading example of a 'compact' set, which is almost as nice to work with as a finite set. In particular, any infinite subset of a compact set has a limit point in the set which is the key to uniform continuity, the existence of the Riemann integral, and more. The nicest definition of a compact set is that each open cover has a finite subcover, and this definition works also in metric spaces and topological spaces.
So here is an explanation of what the first chapters of Baby Rudin are all about. Print a copy and pin it to the wall in any math department that teaches a Baby Rudin course!
[+] [-] nothis|15 years ago|reply
As someone who only ever encounters math as a tool rather than a a great passion or source of intellectual stimulation, it makes me really happy to see this said out loud.
[+] [-] TillE|15 years ago|reply
Please, please don't write textbooks like that.
[+] [-] owenmarshall|15 years ago|reply
From the perspective of a mathematician, I'd like to see textbooks strike a happy medium between page after page of explanation and absolute terseness.
When I'm taking an intermediate level course, I know that the math I encounter may rarely be useful on its own. It should be sufficient to say "you won't even think about this until you take analysis!"
I think the biggest mistake universities make is to offer one type of math instruction. I still remember taking a linear algebra class that had mathematics majors, engineers, and secondary education majors(!) all in the same class! The professor taught it in a way that I very much appreciated -- a large focus on theory and concepts, and much less focus on application & concrete problems. Of course, I and the math majors loved this, while the education majors & engineers detested it.
It might've been more difficult, but I believe that everyone would've benefited from instruction that was tailored to what people would need & could appreciate -- the engineers could learn applications of linear algebra, the secondary education majors could learn how to teach linear algebra, and the mathematicians could learn the theory behind linear algebra. Instead, we had one class that a subset was guaranteed to hate.
[+] [-] bitwize|15 years ago|reply
[+] [-] scott_s|15 years ago|reply
Now, with that said, it's probably true that some math papers could be improved with more exposition. But I think that excluding the layman from new math research is probably an inherent problem, not an accidental one. Improved exposition would be to help other mathematicians who are not in that sub-discipline to understand the broader field.
[+] [-] tokenadult|15 years ago|reply
http://www.ams.org/journals/bull/1994-30-02/S0273-0979-1994-...
(which I learned about from a comment here on HN, thanks) does a good job of demonstrating how a mathematician who makes new discoveries has to invent a new language for describing those discoveries. Then the mathematician has to relentlessly practice communicating those results first to other professional mathematicians, helping them to see the connections between their research and the new research results. Mathematicians who work hard at communicating with other mathematicians, Thurston says, can help greatly with the progress of mathematical research.
After edit: Paul Halmos, quite a well regarded mathematician who by his own self-evaluation was not in the same league as Fields medalists, wrote in his "automathography"
http://www.amazon.com/I-Want-Be-Mathematician-Automathograph...
that he learned a lot of mathematics as he continued his career after his Ph.D. degree by "reading the first ten pages of a lot of mathematics books." Sometimes he could only get ten pages into a book by another mathematician before he was lost, but by reading dozens and dozens of books, ten pages each, he gained more conceptual foundations in more areas of mathematical research and could gradually apply what he self-learned to advance his own research. I strongly encourage students I know to follow that same strategy of reading at least the introductory portion of many books on subjects they desire to know. Don't just read what your professor assigns you to read. Go to the library and read widely. Read as far as you can before you get stuck, and then find another book and start reading it from the beginning until you get stuck again. Eventually, you will find that you can read harder books, and go farther before getting stuck.
[+] [-] lliiffee|15 years ago|reply
[+] [-] kenjackson|15 years ago|reply
[+] [-] ubasu|15 years ago|reply
[PDF] http://www.math.uh.edu/~tomforde/Books/Halmos-How-To-Write.p...
http://www.math.northwestern.edu/graduate/Forum/HALMOS.html
collected in his Selecta of expository writing.
Some other books I like are Sheldon Axler's Linear Algebra Done Right, Real Mathematical Analysis by Charles Pugh, and the three books on manifolds (Topological Manifolds, Smooth Manifolds and Reimannian Manifodls) by John Lee, but there are many other well-known books that are clear in their exposition.
Edit: Part of the issue is also the approach of the reader, i.e. is s/he there to learn mathematics, where the goal is to explore the mathematical world, or is s/he there to use the mathematics to explore the physical world? That should guide questions like "What is the point of studying vector spaces?" The motivation to study vectors spaces (and other mathematical topics) may need to come from other courses, e.g. on mechanics, and the course/book on vector spaces would serve to give in-depth knowledge of the particular topic.
[+] [-] lurker19|15 years ago|reply
Overview page: http://research.microsoft.com/en-us/um/people/simonpj/papers...
PDF slideshow: http://research.microsoft.com/en-us/um/people/simonpj/papers...
[+] [-] pjscott|15 years ago|reply
[+] [-] vbtemp|15 years ago|reply
The fact is, mathematics deals with constructs with extremely specific properties. These properties can be completely and soundly stated without ambiguity quite succinctly in the formalism of the field. Once I'm comfortable with the formalism, trying to express it in English is awkward, imprecise, and generally just extremely verbose. It can then be a frustrating experience going back and convey the idea to colleagues or others in prose.
When I come across some academic mathematics paper, even if I'm somewhat familiar with the field, I generally find other things far more interesting, like the coffee stain on the floor. Effectively reading a mathematics paper requires a print out and a pencil to work through some of the definitions and take notes for yourself, and maintaining laser-like focus for a sustained period of time (more intense than programming a rather difficult problem, imo).
[+] [-] wccrawford|15 years ago|reply
Why on Earth would a common joe want to read that paper anyhow? What could it possibly do for them?
[+] [-] hugh3|15 years ago|reply
Of course, quoting the abstract is a little unfair. The abstract needs to be short so there's no time to explain what the hell a Sato-Levine invariant is. Perhaps the actual paper is a lot clearer.
[+] [-] limmeau|15 years ago|reply
I don't say it's impossible, but it should make visible all the difficulties on the way.
[+] [-] peterbotond|15 years ago|reply
[+] [-] dkarl|15 years ago|reply
[+] [-] marshray|15 years ago|reply
I was reading several papers in the EE field the other day. Most of them all spend the first page restating the problem in practical terms and then have a substantial section reviewing the prior techniques. I found this darned helpful, especially since the primary material was often not online.
Are they worried about wasting paper, or do they actually want to be uninviting?
[+] [-] btilly|15 years ago|reply
See http://bentilly.blogspot.com/2009/11/why-i-left-math.html for more.
[+] [-] hsmyers|15 years ago|reply
[+] [-] lurker19|15 years ago|reply
The $3 copies of Plato et al were better than the math books.
[+] [-] cyrus_|15 years ago|reply
It would also be great to have papers written in a hyperlinked format (after so many years of the web...) so that when you click on a jargon term, you get something like a Wikipedia article about that concept with a few examples and some exposition. Wikipedia itself would be fine with me, though academics might want more official peer review (see Scholarpedia).
[+] [-] jedbrown|15 years ago|reply
Also, the best examples usually link seemingly disparate fields. If you can't assume the reader has a background in these fields, it can be difficult to even state the link. I sometimes find myself writing "readers unfamiliar with X can think of it as [intuitive but imprecise definition]".
[+] [-] pas|15 years ago|reply
[+] [-] br1|15 years ago|reply
[+] [-] blake8086|15 years ago|reply
[+] [-] Wickk|15 years ago|reply
[+] [-] sdh|15 years ago|reply
The only purpose of jargon is to make a conversation exclusive to only those who know the language. If your purpose is to educate or collaborate or truly communicate, then jargon is harmful.
Legal jargon is probably the worst example.
[+] [-] to3m|15 years ago|reply
It is totally unavoidable as long as people keep communicating with words. The better solution is not to complain about it, but to ask for definitions (recursively) - and then you can reap the time-saving and precision benefits of the terminology, too.
[+] [-] NY_USA_Hacker|15 years ago|reply
For the rest of the complaints about 'jargon', these are essentially just necessary given that math, due to its precision and age, is now by far the deepest field of study. So, there are a LOT of terms defined.
If the article wanted to claim that for each math result or paper there is a 10,000 foot intuitive view that can be explained in 90 seconds to just anyone on a street, then okay, but the article did not do this. This claim is not quite true, but it is close enough so that some such explanations, maybe with some pictures, and some connections with more elementary topics, can be useful, even in research papers. But the article didn't make this claim, either.