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Are lay articles good enough to be the main source of information for PhD research?
Doing PhD in new field that does not have enough resources in it. Most of the information I find are articles written in websites such as medium.com.
I really feel awkward citing a website article, as I feel it is not good enough. It is not from university, it has just the author name, not much info about him/her, and the way it is written is for non-academic purpose.
Is it ok to have many of these articles as the source of my information in my PhD? If it is not ok, then what can I do? there is no reliable resources! The field is Artificial Intelligence.
To be more specific: It is not about AI in general, it is about a topic in AI that has not been explored thoroughly, the only place that has done that is Google and they keep the research they have done private and not accessible for public, i have contacted them but they rejected to help with their research
Edit : I know that there are millions of AI researches in the internet. but there isn't anything I was able to find on the area i am studying. google has a product and they are selling as a service and they are not publishing the research they have done on that area, i have contacted google and they did not allow me to look at their research.. there are other researches on other areas may touch that field but none i found on that field specifically.

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is your topic about machine learning? :D

Is it about hospital patients?

W topic guessing

It sounds to me that there's a confusion between two things:

Motivations of the research: imho it's completely fine to use non-academic sources to justify why the research is being done, especially in the case of a new application/domain. This part can even require a thorough analysis of what it would be used for, by whom and what are existing solutions (for instance commercial solutions available). Such work might even qualify as a (probably small) contribution by itself, in the form of some preliminary work to introduce a new application for example.
The actual research contribution, i.e. what is being done and how: it's quite unlikely that a non-academic source would provide all the necessary background (especially theoretical) on which the application is based. Even if it did, its scientific validity could be questioned. So for this part it's difficult to imagine a case where one doesn't rely mostly on regular academic sources, typically in the form of a literature review of existing related works. Note that related works don't have to address the exact same problem: as long as they share some similarities (e.g. similar method for a different task), they are relevant. In this part it's important to provide details about the similarities and differences between the existing work and the contribution.

I find the entire premise of the question quite odd. First of all, to answer your question: I’d say that in most cases I’ve encountered the answer would be no, you can’t use popular science articles as a primary source.
That said, I seriously doubt that they’re all that’s out there. Google works on this problem: they came up with it and no one else ever heard of it or studied it? How did the popular media hear about this amazing idea that has somehow eluded the entire AI research community except Google and your advisor? I feel like you’re either looking at the wrong sources, your advisor is not pointing you in the right direction, or something else is off.

It might also be worth noting is that in AI, and CS more generally, research tends to get presented at conferences in addition to (rather than?) in journals.

In that case, the paper would be available in a conference proceeding and could be cited in a scientific publication.

@DenisdeBernardy That makes no difference. These conference publish peer-reviewed proceedings, which are just as citeable as a journal article. Typically, the peer review is much less rigorous than it would be for a journal, but popsci articles aren't peer reviewed at all. And, in any case, the advisor should be fully aware of the existence of conferences in their own field!

From the way you describe, this sounds really strange especially since there is a lot of real research in AI.
I cannot believe you could only use those articles. However, your supervisor is the right person to ask - most likely, they alone will decide whether or not your dissertation is enough.

It is not about AI in general, it is about a topic in AI that has not been explored thoroughly, the only place that has done that is Google and they keep the research they have done private and not accessible for public, i have contacted them but they rejected to help with their research

@asmgx So, what does your supersupervisor say?

@asmgx And what are the sources of your news articles?

articles does not put references or citation.

@asmgx: sounds extremly fishy and nonaxademic. Did your supervisor say you should study those articles? If yes, youmight want to find out how reputable they are.

Answering for anyone who comes across this question from social science etc. as it is a bit different. We can use popular media sources, but only for certain things.
As someone who uses popular press articles as a "source" for my research, and who advises students who do the same, there is an important distinction to be made and a significant amount of methodological explanation required before you can use much popular media.
The distinction: you can use popular media as a source of information: of facts, or, perhaps, as a source of contemporary public commentary around a subject. You cannot use popular media as a source of analysis. So, for example, you could use popular media articles from the time period, in conjunction with legislative records, to understand the details of and popular sentiment about a change in Australian tax law in 1980. You can't (only) use a post on medium as a sole source of analysis as to why that tax law change was academically significant.
The explanation: you have to indicate that you are fully aware of the drawbacks of using popular media as a source of information for analysis, that you have considered the issues with doing so. You then have to show why it is methodologically necessary to use the media source. I use a lot of local Latin American crime reporting in my research, which I cross reference with government records that I have access to. The local reporting adds context, flavour, and a bit more detail to the government records, sometimes revealing types of information that don't exist in official reports. Media sources also provide names of people that I can follow up with. I note this when I explain my research methods.

Let me provide an example that may be analagous to your current situation.
GPGPU (general purpose GPU) programming first started taking off in its current form when NVIDIA released the GTX 8800 graphics card family and the CUDA programming language back in 2006 through 2008.
This represented a step change from the previous GPGPU techniques in that it was the first true dedicated programming environment that didn't require a connection to a traditional graphics rendering pipeline.
The details of the GPU hardware architecture were not well understood and the only material available on the details were some marketing materials from NVIDIA.
Various research papers started cropping up at the time that attempted to work out the details of the underlying hardware architecture.  Basically, they tried to take proprietary NVIDA R&D, understand the how it was done and explain it to the academic community.  A good example of this is this paper:

Hong, Sunpyo, and Hyesoon Kim. "An analytical model for a GPU architecture with memory-level and thread-level parallelism awareness." In ACM SIGARCH Computer Architecture News, vol. 37, no. 3, pp. 152-163. ACM, 2009.

These early papers tended to reference two major sources of information:

Marketing and technical publications from NVIDIA (in your case, from the Google product / service)
General technical material on GPUs, hardware architectures and specialized programming languages (in your case, AI in general and the math or other techniques your specific AI applications build on)

This is a good example.

Hope you don't mind me adding the full paper reference - I found it a bit odd that one would use an incomplete citation (on a site dedicated to academia) - kinda similar to forgetting to label your coordinate axes :)

@penelope Thanks!

There's nothing wrong with using popular articles as a source of information - for example if I were trying to get a sense of a new field, Wikipedia is one of the first resources I make use of. But using these as primary sources is very iffy. These popular-level articles are written by people who read the research works and then simplified them for laymen. If you're working at PhD level, surely you can read and understand the research works too.
The situation you describe is rather weird. If you're just looking for a reference for "Google has done this", then it'd work as a source. However if you want something more substantial, and if Google is holding some private information which they're not telling others, then the popular-level articles aren't going to help. They won't contain the relevant information either, and you won't be able to duplicate their results using only those. What are you hoping to get out of them then?
In any case your advisor is the best person to ask about this, because he/she will have a better idea about what research question you're hoping to answer, and how to go about answering it. It is plausible that your advisor wants you to reverse engineer Google's product based on the popular-level article, and if that's indeed your goal, then the answer to your question is "yes".

With all due respect, I believe you are mistaken. There is a lot of published research on AI, including the work done at Google. Of course, they don't publish every piece of work they've ever done, but there's a lot out there. For example, if you were interested in something related to AlphaGo, you should look into

Silver, David, et al. "A general reinforcement learning algorithm that masters chess, shogi, and Go through self-play." Science 362.6419 (2018): 1140-1144.

With that said, I see a lot of people, especially those new to the field, finding the papers hard to read, or hard to track down the paper that answers their question. If one wants to learn about how to use a particular implementation of a particular method, I've heard many times now that it's much easier to read blog posts than to read research papers.
If that's what you're doing, that's fine; technical papers aren't always the best place to learn "Hello World". In whatever paper you write, you generally don't cite the website that taught you how to use the package you used, but rather the paper associated with the package you used. For example, if you are using TensorFlow, you should cite

Abadi, Martín, et al. "Tensorflow: A system for large-scale machine learning." 12th {USENIX} Symposium on Operating Systems Design and Implementation ({OSDI} 16). 2016.

rathe than citing

https://www.tensorflow.org/tutorials

even if that's where you learned how to use the code.

I know that there are millions of AI researches in the internet. but there isnt anything I was able to find on the area i am studying. google has a product and they are selling as a service and they are not publishing the research they have done on that area, i have contacted google and they did not allow me to look at their research.. there are other researches on other areas may touch that field but none i found on that field specifically.

@asmgx: Ah, so it sounds like you are interested in specific proprietary AI services provided by Google? If so, that's a pretty interesting "what to do" question.

I can suggest a case in which it might be appropriate, but in general, it would be risky. As you say, the sub field you are exploring is new and little if anything has been published.
Suppose you find a claim in an article that you can base your research on - either proving it or refuting it. The "idea" for the research comes from a reading of the article. Research that refutes a published claim might be stronger than supporting the claim, I think. This is because the person(s) making the claim may have done unpublished research and have some "proof" that it was correct. If you merely confirm it, you are just following, not leading.
But, you also don't say how far along you are in your research. If you are at the beginning, things may change and other publications may speak to the same issue before you finish. So, the question may be moot. But if you are near then end then you do what you can.
Certainly a "green field" topic will find little to cite other than the general literature on the larger domain.

I like this answer. If a proposed research project relies on information from possibly shaky or unreliable sources, then perhaps the project should start by verifying that information in a more rigorous way?


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How much does it cost the publisher to transform the draft of a textbook as given by the authors into a final publication (for web or print)?
I wonder what are the actual costs of translating a manuscript of a textbook as given by the authors into a final publication (for web or print). I.e., ignoring the costs of marketing the textbook, and printing the textbook, and serving content via web.
I am mostly interested in the fields of computer science and maths, English-speaking venues, and the United States, but I am curious about other fields, languages, and countries as well. I am looking for referenced numbers, not guesses.

Given the number of downvotes and close votes from people who seem to think it's impossible, here is an example…

This is not a meaningful question. Manuscripts vary in quality from being near-production-ready to being completely unsalvageable, and in between, one might span a couple of orders of magnitude of cost.

@EnergyNumbers Sure, I'm ok with a distribution, or a dataset containing several samples. I guess we have a different definition of meaningfulness.

I doubt that anyone has tracked this sell enough to compile meaningful statistics. Try approaching publishers yourself, tell them you're doing an industry survey paper, promise them a copy of the results, and ask them if they have this data or would be willing to estimate or gather it for you... Then write that paper; it might even be publishable somewhere if you do it right.

@keshlam Maybe some transparent publisher would have compiled and released some data? (example)

@EnergyNumbers basic copy editing costs about 4 cents a word while technical writting usually costs 1 dollar a word. I would be surprised if there could be an ORDERS of magnitude difference in costs per word.

I fail to see how this is too broad. While the actual cost covers a wide range, there are a only a few things that a publisher potentially does which cost money. I believe the fees associated with those services are well defined.

@StrongBad Copy editing is the least and the last of it. A bad manuscript might need months of developmental editing.

@EnergyNumbers "developmental editing"  would probably be closer to technical writing which is "only" a dollar per word.

@BenCrowell Sure, I'm ok with a distribution, or a dataset containing several samples.

The costs are going to depend on three factors: (1) how long the book is, (2) how well written the book is, and (3) how much layout work the publisher does.
For example, in Math, the publisher might provide a LaTeX template and expect you to hand tweak underfull and overfull lines, float placement, and hypenation. In other fields it is more typical to give the publisher plain text with minimal markup.
The Editorial Freelancers Association publishes recommended editing fees. A typical book might have a round of "line editing" at 4 cents per word, a round of layout at 4 cents per word, and a round of basic copy editing at 2 cents per word.
If the book is poorly written, two rounds of line editing might be needed. If there is automated layout, the layout costs could be saved. There is also the cost of creating an index at 2 cents a word, which depends on who makes the index.

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Why did it become so much more expensive to start a university?
In 1873, Johns Hopkins University was started with an inflation-adjusted $144.5 million. In 1884, Stanford University began with an inflation-adjusted $139 million. Meanwhile, in 2009, KAUST was started with $10 billion. There's a difference of two orders of magnitude.
Why did it become so much more expensive to start a university in modern times?

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Besides all the factors that the other answer already lists, the elephant in the room is that KAUST has explicitly been designed to be a world-class university (rather than organically growing into one, as was the case with your other examples).
In short, it is not so much more expensive nowadays to found just any university - in fact new universities get founded all the time, virtually always spending considerable less money than $10 billion - but founding a university with the expectation that it will compete with the best in the world in a very short time frame is expensive. You need to compensate for all the natural growth in budget and prestige that established universities had over the last one or two centuries.

Are you confident about this answer? The financial records of e.g. the University of Cambridge gives an annual expenditure of 1.760 billion pounds a year, which is also well above the Stanford/JHU founding budgets, and it doesn't even include the cost of construction etc. In fact just the staff costs 787 million pounds/year. (https://www.admin.cam.ac.uk/reporter/2018-19/weekly/6530/section4.shtml#heading2-13)

I am not sure why this is inconsistent with my answer.

In other words, Stanford and Johns Hopkins were modest institutions at the time of their founding, by today's standards.

@xLeitix with a starting budget of $144 million, one would not be able to sustain spending of £1.76 billion, no?

@Allure, I'm not sure how much sense it makes to try to adjust budgets from the feudal 13th century to today, but Cambridge started very small and it doesn't take much budget to sustain a dozen or two lecturers whose only expenses are food, lodgings, parchment, and ink.

@Allure According to Wikipedia, Stanford started with a total teaching staff of 35 and 555 students, while Cambridge had an academic staff of 7913, 12 340 undergraduate and 7610 postgraduate students in 2016.

@Allure What I tried to say in my answer is that traditional top universities had one to multiple centuries to grow into the state that they are in now. If you found a university today your frame of reference is not how these universities started ages ago, but what kind of resources they have today (e.g., in terms of endowment).

"rather than organically growing into one" was simply an effect of the brain drain from Europe after the end of WWII, it has nothing of organic in it.

@JohnB There was also the pre-WWII brain drain of refugees, which greatly helped US universities.

Besides having centuries to grow, the now-leading universities had much less competition for most of that time.  New universities today are competing in an extremely crowded field of established institutions.  The situation isn’t remotely comparable.

I'm accepting this answer because on further searching, it does seem the $10 billion price tag on KAUST is an anomaly. https://www.nzherald.co.nz/bay-of-plenty-times/news/article.cfm?c_id=1503343&objectid=12205925 new campus for University of Waikato $55 million (NZD), https://www.cbc.ca/news/canada/toronto/york-university-campus-markham-1.4153777 new campus for York university $127 million (CAD), both comparable to the JHU/Stanford startup budgets.

KAUST doesn't have a starting budget of $10 billion; it has an endowment of that much. Endowments aren't spent; they are invested so that the return can be spent without touching the principal.

@chepner I.e after inflation they’re probably getting around 500 million a year. A much closer figure.

I would add two other factors to the good answers already available.

Growth of science into multiple fields and disciplines have resulted in increased costs. Back in the day, for example, mathematics was considered one field. But nowadays, there are many diverse subfields within mathematics (e.g., pure maths, statistics, computational math, etc). Creating a university with various departments and faculties results in more human resources cost as well as facilities and equipment costs.
To make scientific and technological advances possible, research has become more relient on expensive lab equipment in the late 20th century and 21st century in comparison with the early 20th century and before that.

"Expensive lab equipment" includes things as commonplace as computers, when you're comparing with 1873. The original mathematics departments at John Hopkins or Stanford needed lots of pens, paper, and blackboards; a new mathematics department today needs computers for all the staff, plus servers/clusters/supercomputers for running simulations/models.

@Stobor: I agree, although I don't consider personal computers for common day-to-day tasks as part of the research equipment. They serve multiple purposes such as communication, documenting, studying, and research simultaneously. However, you are taking about HPC and supercomputers, they are part of equipment dedicated solely to research.

I suspect that you’d probably need to look at the budgets for the institutions in question to get a definitive answer, but I can think of a few potential causes:

Increased administrative and bureaucratic costs. In the days when those universities opened, HR departments weren’t a thing, and there was significantly less regulation on businesses in general.
Increased cost and quality of facilities. Technology marches on - and the cost of building a university building before indoor plumbing was a thing is radically different to building a modern university building with electricity, running water, IT infrastructure, projectors and cameras for the lecture theatres, and all the inspections and certifications being done to make sure that all the work is being done in accordance with code.
Computers, in general. That’s an entire field of costs that didn’t exist back then - not only do they need the physical infrastructure and desktop computers for the staff and students to use, but they also need to pay for licenses for all the software that the students would use for their classes, for the university website, for their online learning system, for their class and room allocation system, for their centralised marking and enrolment system, etc.

Land cost.  You want your university to be located in an accessible location, and that may involve buying out existing land owners, and they will want to cash in.   Another is the huge cost of hiring talents.   Talents don't join a new, un-ranked university unless there is a HUGE incentive.

@Prof.SantaClaus  Land cost generally has not gone up by 100x in ~100 years. If that was the driving factor, it would cost 100 times the amount to start any business, and not be unique to universities. Talent cost also seems like a very minor factor - setting all salaries 50% above the market rate would be a huge incentive to attract talent, and would increase the overall budget by a few dozen percent at best, not anywhere close to 1000%

Computers, in general. — Even with all the licensing costs, computers are significantly cheaper than chemistry or biology labs, athletic facilities, modern dorms, bloated administrations, or Elsevier subscription packages.

Computer costs are negligible. A graduate student with salary, health insurance, a desk to work on, etc, costs ~$50k per year. They need a laptop worth $1k every three years.

@NuclearWang I disagree.  May be you should try renting/buying a place/land in big cities.   Also, you should check out how much top universities pay for top talents; they easily exceed $1 Million USD per year, not including funding for scholarships, labs, etc.  Also, some disciplines require expensive equipment, and huge on-going maintenance cost.  So everything adds up.

@wolf while I agree computer costs aren't a huge factor, there are many more expensive computers that universities use than a stack of laptops for grad students

@AzorAhai -- sure, but you should be able to start a university with a very sizable supercomputing center that costs you $1-2M, serving everyone on campus. That's relatively small potatoes compared to what it costs to just start a chemistry department.

@WolfgangBangerth Fair enough.

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What percent of assistant professors generally receive tenure, and how does this percent vary depending on both school and field?
Are new assistant professors more likely to receive tenure in an expanding field, like biology? And are they less likely (percentage-wise) to receive tenure at elite schools?

The joking description of the Harvard Tenure Model: (1) Make a totally ordered list of every single researcher in the candidate's field.  (2) Call each person on the list, in order, and offer them a job.  (3) If the candidate is the first person on the list to accept, they get tenure!  (Note: Harvard does not actually use this model.)

This is actually quite a difficult question to answer specifically. Here is a brief paper reviewing some of the reasons why good data is unavailable on even very basic questions, together with some references to what is available. In the U.S. case, everyone agrees that, in general, the higher-ranked one's university, the more difficult it is to get tenure. Departments at some elite schools are notorious for their unwillingness or inability to grant tenure to their junior faculty over a very long period—in some cases, decades. (Just last year in my own field, for example, one of the leading departments tenured one of its junior faculty for the first time in more than twenty years. This is an extreme example, but you get the point.)
Beyond the well-known general patterns and the (sometimes widely-reported) particular horror stories, though, many very interesting questions remain difficult to address systematically—including your one about expanding versus stable fields. The question is complicated by the fact that the institution of tenure itself is changing, as is its role within the university. As Wikipedia notes, in the United States "The period since 1972 has seen a steady decline in the percentage of college and university teaching positions in the US that are either tenured or tenure-track. United States Department of Education statistics put the combined tenured/tenure-track rate at 56% for 1975, 46.8% for 1989, and 31.9% for 2005. That is to say, by the year 2005, 68.1% of US college teachers were neither tenured nor eligible for tenure; a full 48% of teachers that year were part-time employees.

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Skimming through a math paper with a group
I am an M.Sc. student in mathematics. I was recently invited by some Ph.D. students and Post-Docs (a group of 5 people, including myself) to join their study group. We are reading a specific text, which should get us ready to read some more advanced work. This work is relevant to the research of some of the other people in the group, but my main goal is to experience this learning methodology with the added advantage of getting to know a few aesthetic results in mathematics.
We met around 6 times, and it is not what I'm used to from courses in the sense that we don't completely understand all the details. Nevertheless, we go on reading.
For example:

We encounter a definition and we can't find out its exact meaning. In this case we usually know of an example of a mathematical object satisfying this definition (because it's mentioned in the text) and we just try to see how the propositions in the text apply to the specific example.

A proof is given with very few details - we manage to fill in some of the gaps, but not all of them, so we just take an example again and simply accept the statement of the theorem so we can use it later.

An excercise is given in the text and we only solve part of it.

We allow ourselves to skip some details because this text is only meant to get us ready for some more advanced, but more specific, material. My question is how we can find out whether or not we are gaining anything, and how we can gain more given the fact that we are all busy and don't want to invest much more time in this specific reading (we have a 3 hours meeting every week).
I have a feeling that I'm "getting used" to some ideas and facts while reading this text (in contrast with "completely understanding"), but I'm not sure if I'm really gaining anything or whether it's just an illusion and I'm not sure how to test my gain of knowledge. The exercises in the text allow us to test our understanding of the details, but not of the general ideas.
EDIT: I will clarify what the question is, in response to aeismail's comment:
As Charles and Nunoxic say, the question of whether shallow-reading is useful is separate from the fact that we are studying in a group. So, the 2 separate questions are:

When reading without understanding all the details, how can I find out whether or not I'm gaining anything?

How can we make the process of studying in a group for 3 hours a week most efficient?

These 2 may have better been asked as 2 separate questions, but I did not  notice that (in my mind they were related because the group study was the first time I encountered shallow-reading).
To summarize the answers I got so far:

It is possible, for some people, to gain knowledge from shallow-reading and one way to test it is to see if you understand why each topic is being developed and why the text is structured the way it is.

When studying in a group, one should test his ability to work out the details himself after the group sessions.

I think the answer I got for (1) is excellent and the answer for (2) is somewhat lacking so far.

@Nunoxic: Each of us goes over the planned reading once before the meeting, and then we read it together again. Sometimes we give an assignment to complete an exercise we started solving together or to find a definition in the literature. Anyway, the work we do out of our 3 hours meeting is kept rather minimal.

user302099: Welcome to Academia.SE. At the moment, I have to vote to close this question, but only because I don't know what you're specifically asking for. Do you want tips on improving the process? Do you want to know what other approaches there are? You need to provide a specific question to be answered.

@aeismail: I thought I was specific in the sentence: "My question is how we...". There I asked for 2 things: 1) a way to test whether or not this is working. 2) a way to gain more in this process given the time constraints. I will try to think how to make it more specific and if you can explain why this sentence does not make a specific question that would help too.

@aeismail: Additionally, Charles answered my question partly by saying "it works for some people" and Nunoxic gave a way to test my understanding by asking for the reason something is being developed. Both of them separate the question of studying in a group from the question of shallow-reading, which is an important observation.

@aeismail: Question changed accordingly.

Okay—thanks for the update. I have to admit that on first pass, I missed it; perhaps because it was buried in an unusual location, and nothing made it stand out. I think we probably should make some sort of statement in the FAQ to ask users to highlight the question (e.g., with italics) if it's not in a "standard" location (first or last paragraph).

There are two positive points of group reading and shallow reading that I feel were not stressed enough by the existing answers: acclimatization and motivation.
By acclimatization I mean gradually learning as to what is interesting and what to pay attention to in a particular field. When you read by yourself (shallow or deep) you only have your own knowledge and intuition to guide you. As a junior student, you might not know what is considered interesting in a given field. If you read by yourself, it is very difficult to spot what is new and what is interesting, especially for some of the less-than-stellar papers that often comprise the bulk of your reading (sure, if you only read the greats they might make things clear, but usually if you can just stick to the greats you are probably reading something old). This was mentioned in @Nunoxic's answer, by attending the group are you learning how to ask questions? How to use the lingo of the field?
By motivation I mean having the extra commitment that helps you to read more. As graduate students we are highly self-motivated, but that doesn't mean we can't benefit from external motivation. By committing to a group, you force yourself to keep up with your reading and work. Some people can replace group meetings by an equal (or even greater) amount of individual work, but I doubt those are the norm. I always schedule a certain number of group meetings and projects to keep myself committed. This makes sure that even on slow weeks where every proof I try fails, and every idea I have is derivative, I still have something to motivate me: the commitment to the group. Further, when I am the junior student in a group, I usually feel the extra pressure to not "be dumb" and tend to invest more time and effort into understanding the material better. The pressure helps me, but it is definitely not for everyone and you should see what works best for you.
Of course, this shouldn't be taken to the extreme. If it is clear that you can accomplish more in those 3 hours (and associated preparation time) by yourself, then you should stop attending.


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How can I know if I am able to pursue a PhD?
I am a 3rd-year computer engineering student at a mid-tier state school with a high GPA (3.97/4.0), top of my class, and 1 semester worth of research. I am also currently participating in a very prestigious REU program, so I do have a decent amount of research experience. I have also taken the GRE and done pretty well (mid 80s) percentile in verb/quant and 99th percentile in AWA. I've also basically narrowed down my research interests to 2 fields, so I have a general idea of what I'd like to specialize in. My goal is to become a Professor in Electrical and Computer Engineering, and I'm starting to contemplate applying to grad schools. I really want a PhD because I know that it is absolutely necessary for my goals.
My only problem is that I am afraid of doing the PhD, because I feel that I won't remember everything (or a good amount) of everything from undergrad. This especially scares me because despite my successes in undergrad, I'm not sure that I could pass the qualifying exams. I guess I'm just afraid of the unknown; do you think that I should just go for it?
Thanks, sorry if my question comes off as rambling; I really want to earn a PhD so I can be a professor or faculty member at some point and knowing that I could fail is very scary.

Don't worry. You are capable.

Talk to your professors. They've been through PhDs themselves, and they know your capabilities much better than anyone else to boot.
Having said that, if you have both a very high GPA and research experience (which you did not dislike), you should be more than qualified to do PhD studies. If you aren't qualified then nobody else in your cohort is qualified, which is not believable. Besides, if you want to become a professor, you'll need to get a PhD - since it's something you must do, you might as well attempt it (or change career goals).

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Choice between A13 Z and E13 for a post-doc position in Germany
I received a post-doc offer in physics from a German University. The position has a fixed three-year term, which might be extended up to three more years. The original position description says that this is the A13 Z position, Akademischer Rat auf Zeit. It corresponds to a Beamter, or civil servant position. Since I am a foreigner, the inviting professor is asking, whether it would be OK for me to switch it to E13 instead (researcher), since my profile for the position in this case is not needed to be checked by the federal government and the documents would be prepared much faster and easier for the inviting University. The salary would then be increased, to match those of A13 (let's assume the same net amount).
What are disadvantages and benefits of E13 compared A13 if one ignores the difference in the salary scale?
Which one is considered better in a long term?
Some more information on the personal situation:

Let's assume I'd like to stay in Germany afterwards.
I'm going to marry before starting the position. My partner has two children from the previous marriage.
I am not a citizen of the EU or the Schengen group.

A E13 position may have a little shorter working hours per week, for eaxample in North Rhine-Westphalia you have to work 39 hrs 50 min/week as "Angestellter" (E13) and 41 hrs/week as Beamter (A13). At least until you are 55 years old, as the working hours for Beamte get gradually reduced as you grow older. But I guess this would not apply to a post-doc position as academic work groups usually do not record the time of their scientist (this means, they often work longer hours without recompensation).
As posted by Roland in his comment above, a Beamter has to get a private health care plan which can be expensive, depending on your age and health status, but as the state pays approximately half of your health care bills, the conditions Beamte get by the private health care companies are much more favourable in comparison to the ones offered to "regular" clients and in the end a Beamter has a higher net salary.
A Beamter has furthermore to pass a health test and perform a vow on the German Grundgesetz (constitution) and the German laws and is not allowed to go on strike. In case of permanent positions, the pensions for Beamte are significantly higher than the pensions for Angestellte. So if you are planning (or hoping) for a permanent position I think a position as Beamter might be more beneficial.
Your family status is also relevant for your salary as Beamter, this means, if you are married with children you will get a higher salary.

Family status is also relevant for the health plan: As Angestellter, the public health plan automatically covers (non-employed) family member. As Beamter on a private health plan each (non-employed) family member will cost extra. As far as I know you also get a higher salary if you are married and have children as Angestellter. (You will have a higher net salary for sure since you'll pay less tax.)

The health care costs are a significant issue to consider, and they are required in Germany.
If you are a Beamter, then you cannot go on the public health plan. To elaborate on drudolf's answer, not only are private health care costs dependent on age, but there is also no protections against pre-existing conditions. You can and will be charged additional costs for coverage if you have a prior health issue. Moreover, unlike the public plans, coverage needs to be extended to each individual member of your family. For a family of four, this could easily be 20% of your net income (or more). While tax changes and Kindergeld allowances can make up some of the shortfall, it probably doesn't cover all of the extra expenses.
So you will want to look at the budgetary issues before making a decision.

It is correct that you need to extend the coverage of a private health plan to the individual members of your family. But if your spouse is working as well and has a public health plan, the children can be covered by that. So it is possible to evade that additional cost, as public health plans in Germany have a fixed cost depending on one's salary.

Depends on your income. Kids have to be insured with the parent that earns the most money, so if your partner makes less money and is on a public plan the kids would still have to go on your private plan.

Depending on the family situation, the income of a spouse and especially their salary (from 2-3 years ago...), the "Beihilfe" rate will also change, and can be extended for your spouse (unless they earn more than approx 20k). Also, with more kids, the Beihilfe will cover a larger share of your health plan, such that you may only need to cover 20% yourself, which would be a lot lower than public health insurance at the same salary (not even talking about coverage).


text:
How can I improve my attention and make fewer mistakes?
Throughout my life, I have always had some issues with what I, my peers and my teachers referred to colloquially as "paying attention". By this I mean a very specific ability to not make mistakes. Some very good examples are:

A mathematically competent adult getting a calculus question wrong because of a simple arithmetic mistake, such as 5+3=15.
A well-prepared student getting a multiple choice question wrong because it was asking "which of the above are not true", but he mistakenly selected the ones that are true.
A skilled roboticist damaging an expensive circuit because he accidentally wired the components incorrectly.
Mixing up two terms which refer to different things, despite understanding very well the concept that either term refers to.
Typos and simple grammar errors.

Note that I do not mean attention in the sense of being able to concentrate on and pay attention to a topic. I am specifically talking about the ability to not make mistakes (where mistakes are simple errors, which you know are wrong but do not notice at the time - not errors you committed because you lacked understanding of a key concept or because you didn't know any better).
While this "attention" obviously influences ability to do well on tests, it also affects my day-to-day work in 2 key ways:

When performing an involved experiment, things such as mixing up samples, accidentally skipping a step of the procedure, forgetting to clearly label the samples and so on may ruin the whole experiment - either because the experiment no longer works when that simple mistake is made, or because the mistake has made the results uninterpretable.
When working with a tool that does not provide much automated error checking, I can end up producing data or programs that are incorrect due to some mistakes I made. It may take me a very long time to detect these bugs - and until I do, all conclusions I draw from my results are unreliable (and I am not aware of this!). Even after I discover the bug, the work done up to that point is still wasted.

So, my question: Is "attention" in this sense (ability to make few mistakes) a skill, or innate? Is there any way for me to improve this skill? Can it be trained, or is it an invariant quality of a person that they can only accept and accommodate?

Note that, for the "making mistakes when doing something complicated" problem, there exist the solutions of

"break it down into simpler chunks which you are less likely to make mistakes with"
"restructure your complicated activity such that mistakes are rendered obvious".

I'm not very interested in these sorts of solutions, because restructuring the task is not always possible, feasible and efficient. Some things simply cannot be made any less complicated than they are.
Also, while I welcome discussions of the physiology of this problem, it is very unlikely that my problem is ADD or a similar disorder. As the saying goes, to err is human - but some humans err more than others, and I am interested in understanding why (and more precisely, what strategies are available to make oneself err less).

Are you talking about absent minded?

Everybody makes mistakes, particularly in "pressure" situations such as tests. I've made the "0 * x = x" type mistake before just because I was too worried about finishing the exam.

@scaaahu Pretty close, but "absent-minded" usually implies a persistent state of unawareness. I am more interested in momentary lapses of, well, attention (for lack of a better word) which result in mistakes (that the mind should normally catch) slipping past.

@aeismail Exactly. Obviously one can try to remove the pressure (or even to add more pressure), but let's say that pressure is not under your control, and it is at a level such that it is causing you to make too many mistakes. Is there anything that can be done, or is it a hopeless situation?

If you don't have time to check your work as you go along or at the end, I can't think of a fail-safe way to avoid errors.

@aeismail That is a good point, but to be clear, I am not trying to get out of checking my work. I am asking if it is possible to improve the efficiency of this checking (checking is also subject to mistakes and missing errors, moreover, it will probably miss the same errors that you missed on the first round - someone else checking your work would be far more effective in this sense), and/or reduce the frequency of error generation in the first place.

I do not believe this question belongs here (in academia.SE). It sound more like a medical issue, or cognitive science.

Note: many successful research mathematicians are especially prone to stupid mistakes, while many others are much more careful (say doing routine calculations while teaching a course), so this issue is not an academic career killer.

The given examples suggest dyslexia; I hasten to add, I'm utterly unqualified

I was unfortunate enough to grow up in an academic upbringing (almost from pre-school up until university) that is a) purely competitive and b) relies solely on multiple-choice exams.
We were drilled for years to try and avoid such small mistakes, since they prove to be extremely costly when millions of people take the same test.
My only advice to you is to make a habit of checking your work, with a clear set of mind. I know it's not always possible (usually due to lack of time) but it's a very important skill to keep in mind that such mistakes do happen from time to time, and having some time at the end of a test/experiment entirely dedicated to checking your work is "money".
To my knowledge there is no fail-safe way to avoid such mistakes. Humans aren't really designed (from an evolutionary point of view) to stay focused for extended periods of time, especially when implicit calculations occur. Which brings me to a "corollary" advice; make a habit of writing out all your thoughts/calculations explicitly. The benefit with that is that it allows you to immediately spot irregularities in your work when you go back and check your work later prior to the point-of-no-return (i.e. you hand in your exam, or turn on the electricity switch or whatever).

I agree with this advice completely.  I was like you to some extent through my early 20's but when I made the commitment to slow down and think things through I noticed I would make far fewer mistakes.  Over time this habit has become so ingrained that I rarely have to think about it any more and now I get through the same work in about the same time with much greater accuracy.

My experience comes from theoretical physics and I do not know how well that can apply to you but I will anyway post my experience.
When dealing with calculations, one should evolve certain intuition for what can be right. For example, if you are calculating temperature of a gas in a problem from thermodynamics and you get a value of -20 kelvin, you must have done something wrong. Most of the time, it will be more difficult to know if one did an error in the calculation but one can still check if a given calculation scales with given parameters in an expected way or not. Such an approach is usually much faster than going through the whole calculation step by step (you just need to look at the result). On the other hand, it requires a good understanding of the problem you are solving (so that you know what you should expect) and some practice. Moreover, it can be used to find incorrect trends only; if you overlook a prefactor of two or three, you won't find it in this way.
This approach also works with any numerical problems. By varying parameters of the calculation, you can check if you get the expected behaviour. The time requirements there might be worse, though; If you have a complicated calculation, running it several times with different parameters can be very time consuming.

I agree with the earlier answer, but I disagree with the questioner's non-acceptance of "restructuring problems".
There are two main classes of checks I employ: plausibility checks mentioned above (which give you a high-level sanity check of what you could hope to expect) and self-imposing structural constraints which limit your ability to make undetected mistakes.
You talk about tools with error checking. In programming, there are many ways of organising code in such a way that will make it difficult to fit together parts which should not go together. It is similar to putting in a special plug that will go only into the correct corresponding socket, and thus will avoid a short-circuit.
In programming, apart from using strongly typed languages, for internal software, I am so paranoid that I litter my code with "assert" statements for any nontrivial assumption I make. This catches many bugs in the making. There are many tricks of that kind. When organising activities, developing a check list and following it, ideally with some kind of physical "cursor", can avoid mistakes. Generally, externalising your activity status can help, such as marking all terms you have operated on in a calculation.
For highly critical processes, I usually create a parallel checking line, such as an independent line of computation or estimate. I'll give a more detailed concrete example of such a parallel check:
I once had to use a formula from literature to estimate a quantity known from literature, but using my own experimental data. I didn't trust it, and did the recomputation from scratch, which took me two weeks of intense work. It paid off, though, as my computation resulted in a factor 2 discrepancy from the original publication. Then I plugged in my experimental data and everything fit beautifully with what was known till then. Had I tried the experimental data first, I probably would have wasted weeks on trying to uncover where the wrong factor 2 would have come from.
Note that I intentionally did the theoretical computation first, without knowing that my experimental data would have given the factor 2 wrong value with the literature formula. This, to avoid temptation to fine tune the factor post hoc. However, in all likelihood, I would probably not have done that, either, and rather would have dropped the whole line of investigation as inconclusive.
This checking procedure was very time-consuming, but the payoff was that it prevented sloppy work and erroneously dropping the hard-won experimental results as useless. I detest debugging after the fact, and generally find it easier to submit to a rigorous discipline to build up my results systematically. I specifically mention this strategy of mine, because the popular "debugging after every substep" (aka "test-driven design") may violate the questioner's constraints about how problems can be structured.


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Should I start my CV by telling about myself?
Currently, in my CV, the first section is the About me section. It goes like this (I'll reserve the format of the text):

Broad knowledge, is why my friends are proud of me.
Never stops asking questions, is what my advisor values in me.

I wonder if writing like this gives makes me look bad. Will the recruiters see me as a confident person, get a better picture of me (which is the impression I want to convey), or will they see me as just arrogant, lacking self-esteem and paranoid?
Next sections are Education, Research Experience and Activities. They are about one page and a half long.
What do you think? Please be frank. Thank you so much.

Thanks to the many people who answered my question, I get that I should save it for the SOP. However, there are some occasions where I'm only asked to send my CV and not a cover letter with it. Should I still keep the "About me" section as a mini SOP in such cases? If it sounds like "platitudes, clichés, and self-compliments" (thanks for being frank, I do need it), how about this idea I just came up with?

I chose science because I want to know everything. I chose physics because I think it is the buttress of other disciplines.

I can make it better later.

Whatever happens with this first section, do have your native english friends proofread your entire resume before you submit it to anyone!

Wow, I have checked the grammar so many times and still make it wrong? Can you tell me where should I improve it? Thank you.

Broad knowledge, is why my friends are proud of me. — Unfortunately, nobody cares about your friends and what makes them proud. Stick to specific, tangible highlights about your skills and interests and why you make a great candidate.

I agree with @StephanBranczyk . I found at least 7 and up to 11 (depending on how strict you are) grammar errors in your post (I'll submit them as an edit). Many employers would be severely put off by such basic errors, so you can probably improve your CV much more than with your idea by just fixing the grammar. Easiest way to do this is to ask a native speaker for help.

Also, generally, I feel like you are trying to put the cart before the horse. "Looking arrogant" isn't something to worry about in a CV (when you get an interview, then you can worry about the best level of confidence). A CV is for presenting the facts of your past life in a clear manner. Besides qualifications, what employers probably look for in CVs is just that they "not be weird". It sounds like what you are trying to do is weird, and you've failed the very challenging task of making it weird in a good way. I'm not an employer, though, so take this with a grain of salt.

@MadJack I disagree, friends can be an excellent resource for understanding your own strengths and weaknesses. Using your friends as a reference in a CV is of course another manner, and I don't know if OP literally intends to mention his friends (which he shouldn't!).

Depends what kind of CV. i did a course on making a 1 pag e CV targeting a particular job. she guided us to write an awesome CV. on the presumption that each CV gets about 2 minutes of perusal, make it super clear format. we started with 6 or 8 work skills that we have, prior to employment list. skills like, data archiving, programming, customer service on phone, trilingual, words per minute on keyboard etc.

What your advisor thinks of you should be presented in a letter of recommendation from your advisor. See Appendix B of this article for an example of a cover letter.

@CountIblis: wow, the example is right to the point. I'm speechless.

1) This is nonstandard, so people are likely to view you as odd, or at the very least unfamiliar with academic norms.
2) On a CV, you should prioritize specific, tangible achievements over things that literally anyone could say about themselves.  You say you have broad knowledge, but will anyone believe you?  It doesn't do anything to differentiate you from people who could also claim to have broad knowledge.  Save that for your letters of reference.

Thank you so much. I have updated my question. Can I know what's your opinion?

@Ooker: "I want to know everything" is the hallmark of a scientific n00b.  Any real scientist knows that advancing the frontier of human knowledge is an uphill, incremental battle.  It may be okay to say this in high school, but if you're applying to graduate programs you're expected to know better.

Yes, I know that I can't know everything. What I want to do does not necessary that I can do that. Is this approach good?

@Ooker: Saying your ambition is to know everything portrays you as someone who hasn't done a lot of actual science and doesn't really know what he's getting into.

Yes, I'm just a graduate student. But if this makes the CV be unprofessional, I'll strip this out. Thank you for your help.

My pleasure.  Good luck with your apps!

sir, I just read a quote from Stephen Hawking and I want to ask you immediately: "My goal is simple. It is a complete understanding of the universe, why it is as it is and why it exists at all". What is your opinion?

@Ooker: It's kind of pretentious to quote famous scientists in your CV, and you're not allowed to talk like that unless you are a famous scientist, in which case you can do whatever you want.

I'm not allowed to talk like that unless I'm a famous scientist. I laugh a lot. +1

Also, will quoting famous scientists in the SOP be a bad idea?

@Ooker: Yeah, generally.

I think I should ask an separate question.

My sense is that broad platitudes, clichés, and self-compliments like the ones you've included are not going to be particularly helpful. I would skip them.
Stick to the basics. There are many websites and templates online that will help give you a sense for what is appropriate and expected. In general, the risk of trying to be creative, especially when you don't have a good sense of your audience or what is expecting, will probably outweigh the potential benefits. If the problem is that your CV is short and weak, there are other questions like this one that might be of some help.
Most importantly, make sure that you have your CV carefully proofread by a native speaker. Both of your two examples sentences are written in poor English. If you put those sentences at the top of your CV, you're going to be sending a message that you probably would rather not.

Thank you so much for being frank. I have updated my question, what's your opinion?

@Ooker: My answer was a general one and my feelings on the matter still stand. I say skip the personal statement. This website is not a free resumé consulting service but a place for asking general questions.

I get that. Also, I do aware if I become a Help Vampire

In a résumé, you want to list facts and what you achieved.
I do not think anybody cares about what your friends think of you.
Those sentences look extremely cheesy because of their structure, in addition to being grammatically wrong. If you write that, you WILL scare whoever reads your CV.
They are also useless as they do not mean anything specific and are not verifiable, they do not contain any HR-drone buzzwords either.
I would skip the About Me section, you can list any meaningful hobbies you have under Activities or whatever that means.
If you want to, you can add a "Profile" section at the top, but just do a brief sum up of your professional profile.
Remember that you can write about yourself and how your characteristics would make you a good fit in the cover letter.

Thanks for your answer. I have updated my question, can you come back and see? Also, I want to ask this question: do I scare you?

If you can't submit a cover letter and are applying for an academic position, include a top section where you briefly describe your achievements and specialties before listing the other stuff, in that sense it's more like a real CV sensu stricto.
You don't scare me but someone who writes "I want to know everything" sounds immature to me, no offsense intended. Everyone specializes in something in his life.
I would stick to facts and achievements.
Go on the personal websites of the professors in your university and look at the short CVs they put there to see what I mean.

This answer will be somewhat U.S. centric.  In the U.S., almost everyone except academics makes something they call a "résumé".  But people applying for academic jobs make something else that they call a "vita" (a curriculum vitae).  There is a significant distinction between the two documents, so if you speak with people in the U.S. you have to be clear which one you mean.   And, if someone asks for a vita, you need to get a sense of what they are looking for.
Quoting briefly from Wikipedia's article "curriculum vitae":

"In the United Kingdom, most Commonwealth countries, and Ireland, a C.V. is short (usually a maximum of two sides of A4 paper), and therefore contains only a summary of the job seeker's employment history, qualifications, education, and some personal information.  ... In the United States a C.V. is used in academic circles and medical careers as a "replacement" for a résumé and is far more comprehensive; the term résumé (a French word which literally means "summary") is used for most recruitment campaigns. "

A U.S. academic vita is essentially just an objective list of the things you have done in your career. For example, here are vitas for Terence Tao (math) and Julia C. Lee (physics). There is no direct "sell", and the vita is not customized much (if at all) for specific applications. It's just a summary of your life.  Sometimes, well-established people make a "summary" vita, which is just a shorter vita that omits less important information.  There is very little "personal opinion", and very little to no commentary. "Just the facts."

I think there is no big different between US and the rest of the world

@ooker - In fact there are significant differences, esp. in what information is considered relevant and how  much tolerance there is of subjective information.

You should not have just one CV, but you should tailor your CV based on the recipient.  The distinction Veblen makes in his answer between resume and vitae is useful to bear in mind (although I do not make this distinction in what follows), and it is also important to bear in mind that  expectations about what should appear in a CV vary between countries and industries.  For example, CVs in Germany tend to be very long (e.g., I have just edited a German CV that is nine dense pages long), exhaustively documenting every post held, with every committee you served on at each post, every professional society attended, every journal for whom you have refereed, etc; and furthermore there is a strong expectation in Germany that the CV contains only objective information.  In the UK, by contrast, CVs are expected to be short, most typically two pages, and it is quite acceptable to list only your most significant places of employment, and to add subjective information, such as what you consider to be your biggest achievement during the period you held a post.
In general, testimonials may be valuable in some applications, but they should be attributed, it should be clear why the testimonial is credible, and they are probably better in your cover letter than a CV, and if you do put them in your CV, I recommend that you have a testimonial section in your CV.  They are more acceptable in the US than in Europe.
You ask about occasions where I'm only asked to send my CV and not a cover letter with it - this is a place where putting more and more subjective information into a CV may be useful.  It is common for recruiters to want just your CV: be aware that the standard of ethics in the recruiting business is not high and you should not be too dependent on their services.
If in doubt, contact the human resources department of the institution to whom you apply before sending anything.  Doing so demonstrates initiative, often will yield useful tips on an unofficial basis, might give you insight into what and how many applications there are for the post, and may help you avoid what the intitution regards as mistakes in a CV.
It is possible to provide supplementary information about your career if you have a page on a website, and provide the URL to this page at the top of your CV.  It's common to link to Linked In pages, although bespoke pages offer more flexibility for you to tailor your presentation, include more subjective information, and probably will have higher information density and attractiveness than these networking websites can offer.  I do not recommend putting exhaustive information about your career online: this material can be abused.

I wish I could give you more than one upvote

To me, it seems you are trying to include in your CV the content that belongs to your cover letter.
As previous answers highlighted, a CV is mainly to present actual past achievements. This should be a document that looks as objective, removed of feelings and subjective opinions as possible.
That's why the cover letter is a natural complement to the CV: this is where you present your achievements and yourself in a more human aspect: you describe not only your achievements, but also why and how you did them, how do you work in a team, etc. However, you still have to be, or at least sound like, as factual and professional as possible: the interviewer is not your pal, he/she doesn't want to know what your friends think of you, but how you will handle your work and how you will fit in the professional setting.
This is not to say that you cannot put a bit of subjective info in your CV, for example some people put at the head of the first page (just below the name and contact details) a short description of their academic education and their short-term and long-term goals (eg, "I have a PhD from the Amazing University, and I intend to work in the field of subquantic fields for panoptic pathologies." -- this is total gibberish, but you see the point).
So the bottom line is that if you want to give some insight about you, you should provide a cover letter, do not add this info inside your CV.

Isn't cover letter the place to show more about your research, not yourself?

Actually both, but more about you and your prospects than just detailing all your researchs, that's the place of your CV (where you can include the abstracts of your most important works as appendices if you want to detail your work).

When I read a CV, I'm looking for why I should hire you. In particular, I'm looking for two things - how useful you're going to be in the first 90 days (how relevant is your experience right now!) and how easy you will learn things for the next 3 years (how broad is your experience, implying you can learn things as this field changes). I'm in computer programming, but I've found this holds for most fields.
I don't care about what your friends say about you. I care about what you have done. So, skills, experience, then education/other (in that order).
Remember - this is a sales pitch. You are marketing and selling yourself. Anyone who tells you a CV is anything else is wrong.

Since this website is Academia.SE, this question is presumably about an academic CV for an academic position (otherwise it would be off-topic here). Academic CVs have a very different format from standard CVs.

@ff524: yeah, but they are CVs after all. I think Rob Kinyon has given me some useful tips

@ff524 - I did miss that this is Academia, but the point about a sales pitch is still valid. What's valuable, though, will differ. 90 day viability is less important, I'd imagine. :)

Actually, academic CVs are typically not as sales-pitch-y as non-academic CVs. They are usually a very formulaic listing of all the academic things the candidate has done, with no editorializing or embellishment (see this random example of one of our users). The "sell" is reserved for other parts of the application.

@ff524: good example. I just afraid that I can't write that long.

You are probably on the wrong stack exchange site. Maybe Workplace is the right place for you.

In particular, academic CVs almost never list "skills", and always list publications and similar academic accomplishments (which you omit to mention). @ff524 is right that there is no explicit sell.


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Comparative quality of articles in questionable journals
This question on citing from publications on Beall's list got me thinking...
The list itself details predatory publishers, who follow bad practices or bad business models. However, is there any evidence that the papers themselves that are contained within those journals are any "worse" than articles in non-predatory, low impact factor journals? I'm not comparing to Science or Nature here, just any other run-of-the-mill journal. By worse, I mean:

Poor research practice
Lack of citation of previous relevant research
Higher incidence of fraud
Non-academic writing
...?

Does anyone know of a study that looked at this?

One of Beall's criteria is "publishes plagiarized papers" so the list does self-select for that.

@ff524 although not all of the publishers/journals listed by Beall have a documented history of plagiarism.

@Jigg not at all. I'm just pointing out a self-selection bias that might make it less meaningful to compare the incidence of fraud in Beall's list journals vs other journals

@ff524 - Interesting. I wonder how he identifies that.

@eykanal spot checks of a couple of issues, usually. Occasionally a reader brings a specific plagiarized article to his attention.

What strikes me, is the seemingly consensual opinion that citing articles published in these pseudo-journals is perfectly ok.

Maybe what I'm about to write was obvious to all.  But just in case:
As I understand it, a "predatory journal" is a journal that will accept anything that is submitted to it so as to financially profit from the authors (and the buyers of the journal, perhaps).  Moreover, they are not forthcoming about this practice because that would drastically lower their submissions (not to mention sales!).  I would guess that most predatory journals would not want to accept papers of the sort created by Nate Eldredge's wonderful mathgen package: although it did happen at least once, I'll bet that incident was embarrassing (or rather, recognized as working against the game they are trying to play) for the Advances in Pure Mathematics.  If that journal published a full issue of gibberish papers, then I think it would seriously jeopardize their profit line and possibly cause them to fold (and yes, get replaced by the next journal, but evidently people like Beall are paying attention not just to the journals themselves but the publishing companies behind them and even the people behind the publishing companies).
Sometimes predatory journals will still publish your paper if you tell them that at the end that you can't or won't pay.  I found this strange at first, but I think I understand it better now: these journals want some papers that are actually for real in order in order to acquire a penumbra of plausible legitimacy for all of their papers.  At the higher end you get journals most of whose papers are written by real researchers who need their work published somewhere and for various reasons they have chosen not to go through the time and effort of a selective journal.  (I don't mean to imply that this practice is not still shady: of course pretending there is contentful, critical peer review when in fact there isn't is highly, highly academically inappropriate.)
What's my point?  I don't think there is going to be any uniform sense in which papers submitted to predatory journals are worse than papers published in "real" journals.  Demonstrably, some of these papers are real papers.  However, if you agree that part of the definition of a predatory journal is that they accept virtually 100% of all submitted papers that are not too clearly gibberish (as well as some that are!), then it would be an amazingly strong indictment of the peer review process not to believe that the papers which have gone through a selection process and are among the X% of accepted papers for some number X bounded away from 100 are going to be, on average, better in every way than papers published by predatory journals.
Is there any evidence of this?  I sure think so.  Any kind of statistical study is either going to concentrate on a very limited range of journals which need not be of direct interest to any given reader or going to take a massive amount of work.  I would rather suggest: select a predatory journal in your field and a legitimate, though run-of-the-mill journal in your field.  Page through, say, the articles published by each one in 2010 (or some reasonable subset thereof).  First evaluate the articles yourself: can you see the difference?  Then look at official reviews of the article (in mathematics there are two internationally recognized services that write reviews of every single math article published -- except that certain journals they drop as not being worth their attention; I believe that similar things exist in many other academic fields).  Then track citation statistics of the articles.  Is there a difference?  Is the difference subtle enough to warrant statistical analysis, or does it just stare you right in the face?  I have done a little bit of this practice myself.  I am getting inspired to try it more systematically.

'If that journal published a full issue of gibberish papers, then I think it would seriously jeopardize their profit line' That would be the case if they had any sort of readership and if the bulk of the authors actually cared about anything else than an additional line on their CV. Most of the time, authors just want a cosy position in a government agency and have no scientific interest whatsoever. The journal will just go on harvesting the money of despair from the next academic drone, not caring about the occasional honest (and naive) author.

The problem is that whoever is hiring these people have themselves no concept of what a decent scientific article is. All of this is a pretense of academia, and frankly should not affect the actual academic community that much, because legitimate researchers and scholars know which are the good journals in their fields.

@Jigg: I know what the good journals are in my field, yes.  But I don't know exactly where the border is between journals which are predatory and journals which are merely very undistinguished.  Given that some predatory journals occasionally quite solid papers by perfectly good researchers (who have frequently published in mainstream journals), I suspect I am not alone and that this mixture of the illegitimate and the legitimate is an essential part of the phenomenon.

Your observation that this is would be a damning indictment of the peer-review process is spot on. I'll restate my question: is the peer-review process functional for low-impact journals? I would hope yes, but I'm not sure, and it's probably tough to answer either way.

I agree with the 'mixture of illegitimate ant legitimate' and would be very interested in the result of the systematic analysis that you consider doing.

@Jigg: I was struck by your comment "That would be the case if they had any sort of readership and if the bulk of the authors actually cared about anything else than an additional line on their CV. Most of the time, authors just want a cosy position in a government agency and have no scientific interest whatsoever."  Just now I checked all 30 papers published by Advances in Pure Mathematics in 2014: based on Nate Eldredge's experiment, I think we can agree to call this journal predatory.  The results were very interesting....

Of these 30 papers, for 28 of them the authors listed an academic affiliation.  Of these 28, 26 were from Africa or Asia and 2 were from Europe.  The 2 unacademically affiliated papers were both from Americans who had earned PhDs in mathematics at American institutions many years before.

@eykanal: I wonder how we confidently identify journals that are low-impact but not predatory?  I know of at least one journal in my subfield -- the JP Journal of Algebra and Number Theory -- for which I am not really sure which side of the line it falls on.

Can you formulate an opinion based on what you saw? I can't judge the content of these articles because it's not my field. As for identifying predatory from low-impact-non-predatory, I think that there is probably a form of continuum, but I would look at the article processing charge.

@Jigg: Yes, probably, but let me get back to you on this.

@Jigg: It turns out that I am having a hard time figuring out how to suitably respond to this, both because (i) such a detailed subject-specific study is not an answer to this or any question on this site and (ii) I feel like I either have to make vague statements that anyone could reasonably question or "call out" various authors for papers which are (I believe) sincerely submitted and not completely trivial but do not meet my own standards of publishability.  I wonder if you have any suggestions.

I understand your reserve. But do you know subscription-based journals in the same field where the demographics are similar to the one you mentioned above and have a similarly low percentage of papers 'sincerely submitted and not completely trivial but [that don't] meet [your] own standards of publishability'? Anyway, I guess some countries have different academic/political systems than the one I'm used to. I imagine some of these people are doing in good faith what the local system is pushing them to do.


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What are the common productivity measures of a scientist, like h-index?
I am aware of h-index. I was wondering what other types of scores are both widely and rarely used to measure the impact of a scientist?

related question: http://academia.stackexchange.com/q/13/66

exact duplicate?

not really a dup. It's a larger topic, and it can include the "einstein index" in the answer. I remember a very interesting paper or blog post on the comparison between h-index and the einstein index.

The h-index is common (and the g-index, which corrects for self-citation), as is the Journal Impact Factor. Johan Bollen has a good review of the various metrics.
However, it's important to point out that all those measures are just different ways of counting citations. They don't account for things like code you've written or talks you've given and they can't address systematic bias in citation practices such as coercive citation or citation mutation. Also, any citation-counting metric will penalize younger researchers simply due to the time it takes to publish one paper and for other papers to get published citing yours. In order to keep academics from having to publish a paper just to describe some code they've written or a dataset they've accumulated, aggregators have been built to pull in these various metrics and consolidate them. Total Impact is a good example of such a system. The general field of study looking at incorporating these broader metrics is called #altmetrics, and you can find a collection of research on the topic here.

There's the g-index and the h-b-index. Another thing is (in conjunction with the number of publications) the number of coauthors, i.e. has somebody only worked with one group (perhaps at the same university) or have they collaborated with lots of people from different institutions.

Beyond the h-index, I don't think there's any definitive parameters used in practice. However, some other common factors used to evaluate research faculty:

Publication count
Quantity of funding
Number of invited talks & invited journal articles
Lab size

Note that these apply to the fields I'm familiar with, neuroscience and engineering. I suspect that these answers will vary according to field.

The number of patents is also sometimes useful.

To add to other answers:
How often one publishes in the most prestigious general journals (e.g. Science and Nature) and most prestigious journals in their field (e.g. Physical Review Letters).

I think that nowadays publication in the most prestigious journals is not as good as it used to be, this because of people trying to do it just because of popularity.

Take a look at this open article in Scientific Reports for a measure that attempts to discard productivity as a factor in evaluating the output of research.

I believe the answer to your question depends very strongly on the field. In mine, mathematics, the most used quick proxy for quality of research is the prestige of journals one's publishes in (which is not measured by impact factor, although there is a correlation).
In some humanities fields, books are the most prominent research outputs.
For a PhD student in biology (especially molecular and cellular, at least in some labs in France), time spent in lab in the evenings and week-ends seems to overweight everything else.


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Will I be penalized if i give someone who hasn't taken a test my test so he could study for his?
I took this Mathematics class and this student asked me if I could ask the teacher to send my test so I could send to him so he can study for the test. It's not that I don't want to be a good person but thinking about doing it is eating me and  I feel if I do it so many things can go wrong for and ruin my future. What should I do?

You’re under no obligation to provide your friend with a copy of the test, particularly if it makes you feel uncomfortable. Just politely decline, and if pressed further, say that you don’t think it’s appropriate to ask the instructor to share the materials that way.
As for the possibility of a penalty, I would not share “active” materials like quizzes or exams that other classmates still have to take, because that could be viewed as an academic code violation. Sharing something that everyone has completed and received grades on may or may not be penalized, based on an instructor’s or program’s explicit rules.

I agree - the actual test is not “normal” revision material available to all...

@SolarMike: That depends a lot on the respective rules. In my place, it is usually considered due diligence for students to revise with previous actual tests (which are never reused in a relevant way, though).

@O.R.Mapper then if that is "normal" the student can ask the teacher themselves directly - taking it through a third person is what is odd...

@SolarMike: Indeed; either, the teacher has nothing to do with the entire process (with the exams being passed down among students, starting with a student who took the respective exam themselves), or any student can ask the teacher directly.


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Referring to author order on paper when arXiv and published copy are different
A paper that I need to refer to reasonably often has in its arXiv version the authors listed alphabetically by surname (as is the custom in mathematics). The published version lists the authors in a different order, having moved the last author to second place. The last author in the published version is  recently told me he doesn't understand why people keep insisting on using the published author order (or to put it bluntly: why they keep listing him last).
What would be the correct way to refer to the joint work, given that the arXiv version is no less prominent than the published version? (Other than in the bibliography, where I would stick to the published order) I'm not sure whether it is more accurate to talk about the work/results of ABCD or of ADBC.

I consider the published version to be more prominent than the arXiv version, because it is clear who reviewed the published version, but unclear whether anyone reviewed the arXiv version.

I would use the order corresponding to which version you cite. Thus, use the arXiv order if the citation is to the arXiv appearance and use the published order if the citation is to the published version.

@user2768 the two versions are identical up to journal branding. And I don't know what you mean by "who reviewed the published version" : refereeing is anonymous.

@Dave I would cite both version simultaneously in the sense of giving both the journal reference and the arXiv  number. The arXiv version is the same, and free to read.

I would actually cite both versions, with cross-references between the two.  "[1] Alpher, Bethe, Gamow, and Deltoid. Twinkle twinkle little star. Preprint, October 2009.  Arxiv:0980.1234 [astro-ph.CO]. Preliminary version of [2]." followed by "[2] Alpher, Gamow, Bethe, and Deltoid. Twinkle twinkle little star. J. Shiny Objects 14(3):123–194, 2010. Archival version of [1]." Ink is cheap.

@DavidRoberts the published version remains more prominent, because it is clear that it has been peer-reviewed. (Even though the arXiv version is identical, it is unknown whether it has been peer-reviewed. To discover that the reader needs to know about the peer-reviewed version and know that both versions contain the same material.) By "who reviewed the published version" I was referring to anonymous reviewers of the journal/conference/...

@JeffE since the OP has stated the two versions are identical, I'd suggest merging the two citations: [2] Alpher, Gamow, Bethe, and Deltoid. Twinkle twinkle little star. J. Shiny Objects 14(3):123–194, 2010. Also available as arxiv:0980.1234. (Ink might well be cheap, but the reader's time is not. The single citation hopefully suggests the versions are identical, whereas multiple citations might indicate distinct content.)

@user2768 But the two versions are not identical; they have different author orders! And it’s impossible to tell which of the author orders is “correct”, so I won’t (and shouldn’t) try. Thank Alpher et al. for wasting the readers time (or the reader for actually reading the bibliography(?!)), not me.

@JeffE the documents aren't completely identical. The orders are different, the formatting is different, and no doubt the content is different too. (Any suggestion that you're wasting people's time was unintended! Your comments/answers are of high-quality.) The author ordering is entirely unimportant for me. Albeit, the ordering used in the main body should correspond to the ordering in the bibliography. This is where the problem arises.

@User2768 the content is identical, up to the journal branding and the author order.

@DavidRoberts, yes, you've said that, but are you sure? Is it possible that a colleague or an editor made a change? Have you verified that? For these reasons, your readers cannot be sure that the two versions are identical and no one has the time to check.

(That said, I'm usually more inclined to trust the technical report version, which hasn't been touched by an editor, because that version is how the authors wanted me to read it, rather than how the editor thinks I should read it.)

Either it's an error in the journal, or I'll be suspicious of the soundness of the paper. Why would two identical papers have different author order unless the authors, who clearly don't speak to each other, send without consulting the others have changed the order of authors on their own mind? (That's why I always try to stick with alphabetic ordering. It shows pettiness otherwise).

I'm not suspicious of the soundness of the paper, @Dilworth, since I understand the results myself, have generalised them in my own work, and know at least three of the authors personally. I don't know why this happened.

Unless it's a mistake, then something is seriously wrong here: either the contribution is distributed evenly between authors or not. Having identical papers with different author orders shows that one of these publications is falsely representing the contribution of authors.

@Dilworth in mathematics the usual practice is to list alphabetically, whatever the various contributions. There is no magic position (first author, last author etc). That is why the situation is odd.

@DavidRoberts, yes. That's precisely what I said: something is deeply odd here.

As Aaron Montgomery's answer states, if you use the full author list in the text, it should match the author list in the bibliography. However, with four authors, you're usually in a position where you can just say

A et al.

in the text rather than

A, B, C, and D

or

A, D, B, C

I find this trick particularly useful when writing A et al. [1,2], where [1] A, B, C, and D ..., and [2] A, D, B, and C ...

This is really unfair to B, C, and D.

Writing "A et al" in a field that (usually!) uses alphabetical order of authors is not a good practice.

Are there a lot of papers in such fields that have lots of authors?

Three- and four-author papers are more common now in mathematics than they used to be.

@PeteL.Clark: At some point, writing out a long list of authors for completeness's sake doesn't seem like a good practice, either. I would try to refer to that paper obliquely.

In this paper alpha.math.uga.edu/~pete/Main_Theorem.pdf I refer to a result of "Alon-Kleitman-Lipton-Meshulam-Rabin-Spencer."  It is rare but not unheard of for math papers to have more than six authors.  But I have never seen a paper in pure mathematics with so many authors that it would add any significant length to one's paper to list all the names in full.

I agree with @PeteL.Clark here, though I've had publishers change such references to "Alon, et al." in the copy-editing (even with only three authors).

I would defer to the order in the version that shows up in your bibliography, presuming that one of those made it in. If not, or if you're somehow citing both, I personally would use the peer-reviewed ordering, but I doubt anyone would quibble either way.

I doubt anyone would quibble either way one of the authors is, as I noted in my question.... And I would stick the arXiv reference with the published version in my bibliography as a matter of principle, since it is a freely available copy: there's no reason to cite both separately.

I mean, if you're worried about personally offending one of the authors, I suppose you have your answer.

This is probably an error on the part of the journal.  This happened to us once on a four author paper, because the journal got confused because they typeset 4-author papers in a 2-by-2 grid and then messed up the bibliographic information when they read it off the grid.  We’ve tried to get it fixed, but it’s essentially impossible.  Go with the version that the authors have control over.

Didn't think of that. I could ask A, the senior author (coincidence in this case that they are alphabetically first) if that happened.

I have spoken with D, who was placed in second position in the author listing for the published version without their knowledge. They've said they don't mind me referring to the paper placing them last, as in the arXiv version. I'm not going to hack BibTeX to fiddle with author order in the citation keys, but if I use the authors in a sentence I will use "A, B, C and D".


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What is a customary startup package for a USA Engineering TT position at an R1?
My colleague and I, both postdocs, are going to TT positions at separate R1 public universities. For various reasons, our advisers have little idea what present startup packages look like. I am in Industrial, he is in MechE.
Here are some guesses from our last brainstorming session:

Equipment (thinking 100k or so)
Cash for travel, supplies, etc (Thinking 50k or so)
Grad student support (thinking 1-2 grad students for 3 years)
Postdoc support (might be substituted for a grad student)
Summer salary (for 2-3 years)

Thoughts? Additional things?

are going to TT positions -- Does this mean that you are still at the interview stage or that you have a job offer in hand / have already accepted an offer?

I would guess this varies a lot, even within the same field.  Perhaps even within the same department.

Related: https://academia.stackexchange.com/questions/85919/startup-package-for-assistant-professor-in-usa-should-i-ask-for-a-an-extra-phd?rq=1

Nothing in your proposed startup packages sounds too unreasonable. The only thing that might be a problem is the number of years of support. You’ll want to know how much it costs to support a grad student, between tuition and stipend. The larger the cost, the fewer the years of support you’ll be able to ask for.
Also, I would expect that the department will not support a post doc, but would instead prefer you to use their funding to support graduate students.


text:
How should I respond to a reviewer comment that I didn't make changes when I did?
I received an email from the editor, including a quote from the reviewer saying "I regret to inform you that the authors failed to address the points I raised in my previous review of this manuscript, in this case, any further comments on this manuscript is pointless."
I sent them an email to ask about the point that we failed to address because I made the changes in the manuscript that the reviewer ask for it. The reviewer said that the authors failed to update the reference list. I add 3 more references to support the old one because he said in his review paper that if the authors don't want to omit old references at least can use them together with more recent ones.
This is the reviewer's comments on my original manuscript:

The references list needs to be updated. There are old references (1980s – 1990s) that can be replaced with more recent ones. Please see below a number of suggested recent papers that can replace old references. If the authors are not willing to omit old references at least can use them together with more recent ones.

And this is his comment after I updated my manuscript:

Unfortunately, the authors failed to update the reference list, and failed to respond to these comments. There are no changes on the manuscript. Authors should address any comments given by reviewers, in a point-to-point response; even if they do not want to consider the comments or suggestions from reviewers they must address their reasons for not considering these comments and suggestions. Given that there are no changes on the manuscript, and there is no point-to-point response from the authors, this review is pointless. Thank you for given me the opportunity to review this manuscript, I leave the final decision to you, since there is no response from the authors.

Please advise me if there is anything that I should be doing? The other reviewer recommended that my manuscript be accepted "as is."

Did you double check that you uploaded the correct (i.e. revised) version of the manuscript, and indicated any changes you made during revision?

"There are no changes on the manuscript." It sounds to me as if the editor might have accidentally sent the original version, and not the revised version, to the referee.

What did you respond in your point-to-point reply to this comment (adding recent references), and what did you do?

Might be technical issue here. You and editor should double check whether updated version has been sent to the reviewer.

Yes I uploaded the correct manuscript and highlight it with different color. Thank you all I will check with the editor.

Did you attach a document with the list of changes? A response to reviewers?