publications - Is there an affordable way for non-students to subscribe to multi-journals/archives?

As a student I had free access to thousands of scholarly articles through my universities in databases/archives such as JSTOR, EBSCOhost, Google Scholar, Econlit, PubMed, etc, etc.

With no subscription, glancing at the full text of any 1 article costs anywhere from $20 to $60.

For any one project or paper I'd use at least five to ten papers and I'd skim over the full text of many more. For a meta-analysis of the literature, I'd go over dozens and perhaps even over a hundred papers.

As a non-student the cost is extremely prohibitive to continue reading past the free abstracts. I don't want to pirate the papers or give up reading them, but I can't find any reasonable alternatives.

Does anyone know of any monthly subscription I could sign up for to give me student-like/institutional access to papers?

Note:
A community wiki answer has been added to this question to provide a list of solutions to the problem.

Answer

A month after asking this question I randomly stumbled onto the type of solution which I was originally seeking -- open-market subscription based access to multiple journals and full-text article links from sources such as Google Scholar, PubMed, EconLit, etc.

While searching for full text access to an article on Manufactured Environmental Toxins in umbilical cords I noticed that one of the full text options was through a service called DeepDyve.

It claims to be the "Spotify of Academic articles" (Spotify is a popular Internet radio app that lets you download and play music at will if you subscribe). Here is a somewhat dated review from Ohio State's TechTip a la 2009. It's a $40/mo subscription plan for non-students like the institutional access you get within academia. I'm on a 2-week trial of it now.

Of course, I'm still going to continue to make use of many of the other good suggestions and I'm on the lookout for other services like this to select from.

USE WITH ADDITIONAL SOLUTIONS

In addition to the service I found, I'm taking advantage of several other solutions offered. Even with the subscription-based service there are many papers and journals to which I do not have access and the follow suggestions remain vital:

• Many papers are freely available on authors' websites, and pre-print servers (use search engine to find those).


• Write to the authors, asking for copies. Majority of academics are happy when their work is read, and will send you a copy.


• Your public library might subscribe to more than you suspect. Check it out.


• Many institutions grant library privileges to alumni, which might include remote access to the university's online subscriptions. You might get in touch with the librarian at your alma mater and ask if they offer such a thing. (In some cases you might be required to join the alumni association and pay dues, but this would probably be on the order of US$10-$100 per year.)


• Many universities open their libraries to the public. If you live near any university or college that has appropriate subscriptions, you may be able to just walk into their library, sit down at a computer, and download the articles you want. Then just put them on a USB drive, upload them to a cloud storage account, or email them to yourself. For older articles that aren't online, the library may have them in bound volumes; they may not let you check them out, but you can photocopy or scan any article you want.

LIMITATIONS OF THIS SOLUTION

The subscription-based service isn't a perfect solution. @J.Zimmerman points out that, unlike institutional access, you do not have the right to print or download papers. It's "read-only" access.

The selection of journals is quite large, but still limited. My feeling is that it directly provides access to about the same selection you'd have with most universities, but unlike universities there's no inter-library loan or other work-around for when you do not have access.

AFTERWORD

As I use this solution more over the course of the next few days I'll update this solution with further limitations and I'll better integrate it with the other useful solutions which have been posted. I will also take a suggestion from the comments to make this a Community Wiki solution.

Finally, I will also be on the look-out for any competing services like DeepDyve. Please update this solution if you know of any, so that we're not inadvertantly providing an advertisement for one arbitrary commercial service.

research process - What to do when you spend several months working on an idea that fails in a masters thesis?

How shall a masters student deal with the complete failure to meet the expected results when working on a master's thesis?

For example, in the field of machine learning a masters student might spend 4-5 months developing a method that turns out not be useful, not even being comparable to benchmark datasets.

Should the student quit it? Should you at least take a break from academia to avoid harming your career ? Or should you work on a different idea and risk another few months which is also not guaranteed? Given the fact that the advisor is simply asking you to try new things

Answer

Step 1: Don't panic

I was in a similar situation halfway through my MSc. I was in a panic, sure that my academic career was in ruins. My supervisor calmed me down, reminded that a negative result was still a result, and and told me that a for a master's degree, it was not strictly required that I make a scientific contribution or have a publication. In the worst case, in my thesis I would present my negative results, explain why this technique didn't work, and suggest what could be done differently by future researchers. (Once I was relaxed enough to think clearly, I came up with new things to try, and everything worked out grand.)

I suggest you discuss the "worst case scenario" with your supervisor; you'll probably find out it's not as bad as you think. Remember that this is research: positive results are not guaranteed.

Step 2: Think about why this technique isn't working.

I'm sure you've learned something about why your technique isn't working. That should give you some ideas for what to try next. If you're out of ideas, sit a friend down and explain everything to them. The friend doesn't need to know anything about machine learning; they're just a sounding board. The naive questions they ask may give you ideas. Maybe you need a week off to recharge your batteries.

Step 3: Try something new.

Take those new ideas you got in step 2, and apply them. But now that you're more experienced, think about how you could find out more quickly if the idea is feasible, so you can change tack again if needed.

Why do admissions committees consider the Statement of Purpose to be important?

Why do admissions committees consider the Statement of Purpose to be important? Anyone with a command of English should be able to write a Statement of Purpose, in principle, so it seems a poor way to compare applicants' research potential. If I were to judge an applicant (obviously I've never been in this position), I would much sooner at grades than at their Statement of Purpose, simply because grades cannot (in general) be 'faked'.

publications - Found an error in a paper that I already presented at a student engineering conference; what should I do now?

I completed my undergraduate (in engineering) earlier this year and I am working in a company now.

My senior design project involved me developing a different and cost-effective method for something. So I decided to document everything in a research paper.

I ended up submitting the paper to a national level student engineering conference. The paper was accepted. I presented it. And in fact ended up getting the award for the 2nd best paper.

However I was going over my paper the other day and I found out a mistake in my algorithm. My concept (discussed in the paper) and actual code are both correct. But since I didn't put the code in the paper and just the algorithm I made an error in converting my code to the algorithm for the paper.

The error can be easily corrected however the algorithm in its current state will cause the device to not work properly. The paper also discusses 2 other algorithms for 2 other tasks; both of them are correct but everything is interdependent.

The paper hasn't been published (and can't be found online) but it is printed in the conference proceedings. I am also ashamed to have won the 2nd prize with an error in my paper.

My question is, how do I approach this?

interview - Cheated on an exam when I was eight years old. Should I tell graduate admissions?

I cheated at a language exam when I was eight years old. I finished early and noticed that I had accidentally left a dictionary in my drawer. I double-checked my answers and promptly got caught. The incident is probably unverifiable at this point: The physical evidence is long gone; the teacher probably retired; the school probably didn’t keep records or has already destroyed it. I might be the only person on the planet who still remembers it.

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  Should I mention this incident when being asked about academic integrity in job interviews or similar?

  
  


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  Should I tell graduate admissions?

  
  

I suspect the answer is no since it was so long ago and I was eight years old, but I’m afraid I might be rationalizing.

Answer

As noted in the comments, actions committed long ago as a child are (and should be) entirely irrelevant to graduate admissions.

It is well understood that children do not have same ability as adults to comprehend the consequences on their actions. As a result, many legal systems wipe a child's record clean of most or all juvenile offenses upon reaching adulthood.

I would thus similarly argue that any academic offense predating your undergraduate education should generally neither be reported nor considered in an application for graduate school.

thesis - Is it common for a managing editor of a University Press to solicit book proposals from PhD students at a conference?

I am a PhD candidate in the very early process of writing my dissertation, and I'm presenting my first chapter at an international humanities conference soon. I received an email from the managing editor of a well known University Press that was impressed by my topic and wants to meet to discuss possibilities. How common is this?

Is it quite common for University Presses to solicit meetings with PhD students? Or is this a rare opportunity? His interest was so unexpected (because I always assumed you approached editors if you wanted to publish) that I'm not sure if this is a promising opportunity.

So how often do managing editors of University Presses solicit authors that are ABD?

Answer

I'll note that the question was changed (not by the OP) to focus on books. I'll answer that first.

I think it is unlikely that publishers, often represented by senior (acquisitions) editors, to solicit books from students, but very common for them to talk to professors about book ideas. In some cases, the professors might send them to students who have some interesting work. Some of my books were solicited, but I'd established a reputation by then.

Book chapters are a bit different. Beware that some predatory publishers are on the prowl among the unsophisticated to get materials for less-than-reputable publications, but really good publishers will do this also.

In my opinion (note: opinion), the best such books have been suggested by some senior researcher who has some, but not enough, material for a book and has convinced a good publisher to help put it together, perhaps by going on the prowl for submissions. But here, the senior researcher, not just an editor has some control over the book, which should guarantee both success and quality. In such a book, the sponsoring professor or researcher will probably write the introduction and have one or more of the major contributions. The contributions may all be recent or the intent may be to bring an historical consolidation of some topic.

Other meetings of publishers and doctoral students are more likely to be just informational, with no commitments being made. The publisher is saying "We Exist - consider us for your next paper". The discussions will be informational in nature, mostly: This is what we want to print (or not). But you wouldn't' get any commitment to publish even a completed paper at a conference if the journal has any credibility. The paper will still need to be reviewed by subject matter experts with an eye to improvement.

That said, it is good to establish such relationships with journals, even if they are very tentative.

graduate school - Do exercises in a theoretical reference book need to be solved when doing research?

I am a first year graduate student in a computational math program. Based on my background (I just finished a one-semester graduate real analysis course), instead of reading a specific textbook, my supervisor suggested me starting reading papers. And if I find unclear concepts, I can refer to some books in library, learn the specific knowledge and come back to the paper.

In general I agree with this method since I think this is the most effective way to learn a new technique, that is, applying the new knowledge directly to my research. But I am not sure what I should do if it's a pure math concept, instead of a numerical scheme. For example, say the existence of weak solution of a particular PDE. After reading the relavant chapter or chapters of a classic book which I borrowed from the library, should I try to do the exercise after those chapters before moving back to the paper? Based on the suggestions here, I should try to solve as many as exercises in that book to make sure I understand the theorems and techniques, and this is what I usually do in my undergraduate study.

But I have several concerns about this approach. Firstly, it may be time-consuming and may delay the research process. Secondly, unlike reading an undergraduate textbook, I started the reference book in the middle, while the exercises may require some previous chapters' techiniques, which I may not know and may not be directly related with my current research.

So may you share your experience about how to deal with this senario? Do you come back to the paper immediately (say after knowing the statement of a theorem) or do you spend some time solving exercises? If the exercises involving previous chapters' concepts, do you usually read previous chapters as well or do you just skip those exercises? I know it's good to learn more things, but given the time constrains and tons of things I need to learn, sometime it may not be practical.

Answer

I wanted to put in a word that mathematics really is hard and takes time to learn.

In particular, in my experience -- which is, I must say, almost exclusively with pure mathematics, but in many programs in the US the distinction between pure and applied only emerges later on -- relatively few first year math PhD students are reading papers independently. Unless I very much misremember, I did not start reading "serious" math papers until my second year. For what it is worth, I was a student at Harvard, and I entered with a BAMS from the University of Chicago. I was not poorly prepared compared to my American peers. Also for what it is worth, "one-semester graduate real analysis" is what I took as a third year undergraduate. And then I followed it with another semester. And by the way I was a student of number theory. As I recall I spent the first semester of my first year studying for my quals, passed them at the beginning of the second semester, and spent the second semester learning about elliptic curves, local fields and schemes from textbooks of Silverman, Serre and Hartshorne. The idea of plunging into papers without having learned this material: well, it might have added some drama, but almost certainly it would have added to my total time to degree.

I have very mixed feelings when I hear people on this site say things to early career graduate students like: "don't get too bogged down in any one thing"; "you can read textbooks forever; time to start reading papers"; "only spend as much time to learn something as is needed to apply it to your own work"; and so forth. It is not that such sentiments are not applicable in mathematics: I have said all of these lines myself. It is rather that in mathematics this kind of advice gets given out much later in the day: some of it is great advice for mid- and late-career grad students, and some of it sounds more appropriate for postdocs. On the other hand I have seen a lot of students -- including talented ones -- get snagged because they prioritize "their research" over basic learning. I did my PhD thesis on moduli spaces of abelian surfaces with quaternionic multiplication. I didn't know what any of those words meant as a first year PhD student.

Now I write all this knowing that the OP is in applied math, which depending on what that means could either be identical to the pure math experience, wildly different, or anywhere in between. But he is asking about pure math knowledge and seems to have the intuition that it will not come so quickly or easily. I think the most honest, helpful answer is: it does not come so quickly or easily to pure math students at top places. So if you're expecting it to come quickly and easily to you, then you're setting yourself up for disappointment. A certain amount of patient, textbook-driven linear learning will pay immeasurable dividends down the road. How much? Good question: that's what advisors are for.

Well, after all this I may as well take a crack at the precise question asked. Should you solve exercises in textbooks you read in order to gain background on your research? Sometimes. I think that whenever you're reading a math book and get to some exercises you should at least look over them and get a sense of how close you are to being able to solve them. This is an important clue to how much of the material has sunk in. On the other hand, how much time should you spend solving any one "problem set" when you're reading the text in "research mode"? Not very much unless you see how solving that particular problem is relevant to your work (in which case: lots of time, potentially). If you don't know whether the exercises are relevant to what you're doing, you either haven't read closely enough or are reading too linearly: you don't have to read textbooks in order or one at a time. Grab several off the shelf at once. Play them off against each other. Often what you actually need is something that most texts will hint at, drive somewhere near, leave to you as an exercise....but the right textbook will do it wonderfully. Or maybe no one text will say exactly what you want, but together they will. Being able to "triangulate from multiple sources" is, I would say, an intermediate research skill: I know many PhD students who don't seem to have mastered it (e.g. for complete lack of trying!), but it is one well worth developing if you're trying to dive head-first into the literature.

Good luck.