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Does academia have a lazy work culture?
I'm a rising sophomore at a top US university, and I've become really fascinated with the world of academia over the past year -- so much so that I'm considering doing a PhD after I graduate and entering it myself. But there's something about academia that bothers me.
I'm doing a summer internship at a research center at a university where I'm in the company of several PhD students and post docs as well. I've noticed that the work culture here is a bit lazy. I understand that academia isn't the most "organized" area (unlike the corporate world), and that one great thing about academia is the flexibility you get to do your work however you want. For instance, I've spoken to professors who say they do most of their work at night -- which, obviously, is impossible in a regular job. But I've observed this getting translated into laziness. People will only come in to the center for 3-4 hours a day, and sometimes not even every day in the week. I also see people often passively sitting on their computers and not really actively doing their work.
I completely understand that academics are less "robotic" than people working corporate jobs in that they don't follow the same routine every single day, but it just seems to me that a lot of people lack the drive, intensity, and seriousness that I see in my romanticized version of the world of academia. Thoughts?

Specifying the field would be helpful. For instance, experimental biology has a lot of long hours of work, which looks like work. Meanwhile theoretical physics (my field) has a lot of work which doesn’t look like work, such as long discussions at the blackboard. Moreover, for a theoretical field one can work from anywhere, and the people I know usually do their serious work outside the office.

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This seems opinion-based, too broad, and unclear what is being asked ("thoughts?"). OP even seems to have answered their own question ("do most of their work at night"). Have voted to close.

Just how do you get from "spending 3-4 hours at an institution and doing the rest at night" to "lazy"? The "butts in seats" metric is not the only one in the world, possibly not even the best one.

obligatory comic reference https://heeris.id.au/2013/this-is-why-you-shouldnt-interrupt-a-programmer/

Are you really convinced that people working corporate jobs don't sit around doing nothing (work-related)? I'm not saying all of them do, but doing nothing is not something particular to academia (nor is it necessarily a bad thing).

Different areas of work look differently. A mechanic, a tailor or a miner perform visible physical operations and deliver an objective and measurable result by hour. Compared with them, office work may seem lazy: people sit at their desks, they are not sweating, can have toilet and drink breaks whenever they want, etc. Also, the result of their work seems less tangible: we do not see goods or materials produced, only papers, and looking from outside, we often can not understand how good the  result is without taking their manager's word for it.
Academic teaching and administration work is very much like office work in a company. Teaching-focused colleges and universities often seem very similar to corporate organisations (with one important difference that they have  less support  structures and security for academics).
Academic research work seem even less organised and the results seem even less tangible. People either appear sitting at their computers idly (while they are in fact thinking on the problem), or stay at the whiteboard scribbling unreadable equations (still thinking on their problems), or stay at home (thinking about their problems). If you look around, you will see the result of their thinking process (e.g. a computer or smartphone in front of you, as well as many many others). But the results do not jump out of their heads in the same visible way how an ore appears from the mine.
Corporate culture portraits an idealised worker as an energetic, serious man in suit. There are many, many problems with this idealised picture, for example, the fact that it is relatively easy to make such an appearance without any real skill, knowledge and desire to produce a meaningful result. Academia, partly, shares this problem: there is an idealised image of academic (a person excellent in everything, highly introvertial but excellent in communicating complex ideas to different audiences, etc etc), which has little to do with the real academic culture. Many academics visibly change their behaviour when they have to present their results for promotion or appraisal. However, in their natural habitat, they still focus on solving their problems in the way which is most effective for them, do not act to impress you or match your expectations about how this process has to look.

You could also highlight the issue of waiting in both office and academic work. If your desk job is to check and rubberstamp a never ending stream of paperwork in a government office, then you might not have much downtime. But if you're waiting on experiment results or information/feedback from elsewhere, then it is easy to get stuck in a state with nothing really useful to do. For some jobs, there is only so much that can be done in a given period of time, and when it gets done can be fairly flexible.

I'm certainly sweating at my desk this week!  (Germany)

@TheLuckless Good point. Lifesavers spend their time idly looking in the sea. Policemen spend their days idly walking the streets. Photographers spend hours idly waiting for the perfect moment. Researchers spend years chasing something that no-one ever seen before.

I once saw a poster with a bunch of sharp pencils and one dull pencil. The caption read, “It’s easy to look sharp if you don’t work.” Ultimately, it depends a lot on the university. Top research universities have a “publish or perish” mentality. Many colleges require faculty to give up a lot of their time to serve on or oversee committees of all kinds, not to mention teaching, grading, performing research, overseeing student research, etc. Some universities care only about profit, and everything takes a back seat to sports programs and enrollment figures, so humanities faculty feel demoralized

Do not fall into the trap of assuming that "Value of work done" is proportional to "Hours spent at a desk".
Some HR departments do think this way, but it's rarely true.

+1 I work far more efficiently in coffee shops than in my university office.

+1 I work far more efficiently taking frequent breaks than working non-stop.

Well, being available even if idle can provide value. An hour you spend away from your desk is potentially an hour you're not available in for colleagues to bounce an idea off you. Of course you weren't talking about never being in the office, and colleagues can just take a note or send an email, but physical presence still helps collaboration.

@Trusly As one professor once said to me, "networking is one letter away from not working".

Would you like to differentiate between "Hours spent at a desk" and "Hours spent working"? Someone might generate a certain "value of work" (whatever measurement you'd like to apply for that one...) in 8 hours, and someone else might achieve the same in 2 hours. Does that mean that the latter can just slack off for the rest of the day? (Just playing devil's advocate here, to point out how hard an objective and fair comparison actually is...)

@Marco13 - In industries like real estate where agents are paid by commission, the latter agent can either go slack off or go sell another house – it's their choice. But in industries where work output is much more diverse and isn't so easily measured (like an office or school), we often default to desk time simply because that's far easier to measure than units of true productivity.

Here's an experiment you might try: Next time you see one of those "lazy" instructors staring at the computer screen, ask them how many graduate students they are advising. Then ask if you can read the latest drafts of all the theses and dissertations for each one of those students. Then ask if you can read all the latest drafts of the papers that this professor hopes to see submitted for publication in the next year. And then ask to read all of the papers that were submitted for publication in the past 18 months.
My guess is that you'll be going home with a pretty big sheaf of paper.
Next, you have to read each one of these, not just as a cursory read, and not even to the point of understanding each paper or dissertation. You need to get to a level of familiarity where you could even spot a mistake, a flaw, or an error, because once this research is ultimately presented at a conference, there's a good chance there will be fifty experts in the room trying to do just that.
Now, imagine doing all this while you are teaching one or two classes, grading 30 papers every time there is a homework assignment – hopefully fast enough so that everyone feels like they are getting the timely feedback they deserve.
Better yet, ask if you can be a grader for one of the assignments, so you can get a feel for what it's like to analyze 30 attempts at solving the same set of problems, not only giving credit for each correct answer, but also figuring out where each student took a wrong turn to arrive at an incorrect answer, and giving them the feedback each one will need to learn from their mistake.
Maybe you could offer to be a guest lecturer for one week, too, so that you can see what it's like to learn a subject well enough to stand in front of a classroom and deliver an informative, thorough, 50-minute lecture in an engaging way in front of a couple dozen students, many of whom would rather be doing something else.
I'm guessing that, by the time this experiment is over, you might start to realize there is a whole lot less "laziness" happening on campus than you may have initially speculated.

Your mistake is to assume that people who are only in the department for a few hours a day are only doing a few hours' work per day. They're probably working at home, too, or in cafes.

One reason so many academicians can get more done at home than on campus? Fewer interruptions. At any one time, you'll be advising a handful of graduate students while teaching a few dozen undergraduate students, and any these might pop in unannounced for that next "quick question".

Honestly, most academics I know get work done at home or elsewhere. Writing up one's research isn't something one can do easily in the office. I don't know any lazy academics.

Actually, I do some of my best thinking when I'm out hiking or cross-country skiing.  IMHO, it's all about increased blood flow to the brain, which you don't get sitting on your butt in front of a computer :-)  (Even when I worked at a corporate research lab, I'd take an hour or two in the afternoon for a walk or bike ride.)

Absolutely.  I absolutely cannot do anything but the most basic of lesson planning for lower level courses when at the office because I'm interrupted every five minutes by something

On that note does Academia/any very free research environment have a notion of full time part time and overtime?   surely a researcher may wish to work more or fewer hours and think more or less

@HaoSun There's usually no overtime in positions where pay is quoted per year rather than per hour. I've never heard of overtime in academia.

@DavidRicherby: At least in my country, almost every job comes with working hours per week (which in turn are capped at roughly forty). This applies also to academics, which can thus do overtime. However, actually registering overtime would require clocking academic work, which nobody does. Still, I would certainly consider somebody working in a lab for sixty hours per week doing (unhealthy) overtime

@Wrzlprmft "Overtime" doesn't mean working beyond your scheduled hours: it means being paid for it.

As someone who's done both academic and more routine white-collar work (programming) I can say that academics work a lot, but indeed at odd times, in fact basically always, you are always thinking or writing or reading. But because of the flexibility, it's a lot less tiring than working fewer but more restrictedly fixed hours in a particular office with particular people you have to interact with daily, like in industry. Academia isn't only the life of the mind, but to the extent that it is mind work it can be very flexible but also constantly hanging over your head. Some people take advantage of the lack of supervision and don't get much done, others work too much and hurt themselves, others thrive. Worse, it's hard to even tell if you are thriving because you may produce work no one pays attention to for years, and it may be poor work or it may be that years later all sudden your field takes it up.

+1 My experience is mixed. For most parts as you say. But being a programmer was much, much less work than being  a lecturer.  Academia has much worse crunch times In my experience. It is offset by a quite  a lot  of freedom though (however its  a  bit of a lie, your free to do things  in many ways but  they have  to get done). Its typical that you are your own worst enemy in academia as there is a lot  you can do to your work burden. So eventually you learn that its  not  a sprint but  a  really long  marathon so you stop taking every burden on yourself.

@joojaa Yeah, the first couple years of lecturing (asst prof) are the worst when you are writing the new lectures & getting on top of which emails you have to attend to and which you don't. I was talking about overall--don't worry, it does get better.

I've worked as a software developer in both private industry and academia. I could tell you all sorts of anecdotes of lazy folks in industry and hardworking academics. I briefly worked at one firm where several employees ran their own  businesses on the side during our regular work hours. The PIs I've worked for  worked just as hard as the entrepreneurs at the start-ups I've worked at, which is very hard indeed.
I worked in software development at Microsoft in the 90s. At the same time, my spouse was working on their Ph.D. Comparing notes, we were both working about equally hard in terms of hours put in, stress, and fatigue. My work had more time pressure, but my spouse had more responsibility for determining the direction of their research. In some ways the biggest difference was that I was served free soda and espresso every day, and ate catered dinners many nights, while my spouse was having to pay for and prepare her own sandwiches. And of course I was paid 4 times as much as they were.

When I worked at an office once although I learned how to look busy, in reality I was only doing maybe a few hours of work a day and in the meantime I was studying on the side and working through maths problems.

I really want to play the scene from Office space "Yeah, I just stare at my desk, but it looks like I'm working. I do that for probably another hour after lunch too, I'd say in a given week I probably only do about fifteen minutes of real, actual, work."

I think all this stems from the misguided idea that people actually can work thinking heavy jobs 8 hours straight and be reasonable productive this whole time. - Almost nobody I know is actually productive 40 hours a week. A typical day is mostly 2 hours really high productivity interspersed with 6 hours low productivity busy-work, because your mind doesn't work like a conveyor belt. - And then there is some research suggesting about 60% mental capacity in the workplace is usually dedicated to social-structure / office politics.

The question is difficult in several ways. Although you're not starting with the presupposition that people tend to be lazy in academia, you describe your observations in a way that seems to support this claim. That's okay (and that's probably why you're asking the question in the first place). But consider where you are asking this. I mean, let's be honest: You didn't expect responses along the lines of

"Sure, we're all just slackers! Grab one of these cocktails with the tiny umbrellas in them, and join us! Research is far better than real work!"

Therefore, the arguments in the answers so far followed the patterns that one could expect as answers (here) to such a question:

You don't "see" the work, and/or the results are not "tangible" - it's a different kind of "work"
The teaching and preparation of lectures takes a lot of time
The schedules are odd because you can do some of the "work" at any time and any place

In general: People will tend to justify what they are doing. And as a last resort, one can go down one or the other rabbit hole and start nitpicking about what constitutes "lazy", or what "work" actually means.
Fortunately, there have been some responses from people who worked in academia and in the industry. In contrast to people who went the straight "high school - college - PhD - post-doc - tenure" road, they could, at least principally, do the comparison that is at the core of the question.
I personally don't have the direct comparison, because I've mainly been working in "applied research". So the following may not really be an insightful answer, but rather a truism:

There are workaholics who are extremely conscientious and industrious and work for 80 hours per week straight, without taking a vacation, until they achieve their personal goal.
There are lazy slackers with the life goal of sitting in front of a PC with the monitor being arranged in a way that nobody else can see it, in an organization that is large enough so that nobody notices that they are essentially doing nothing.

And you find both sorts of people in academia and in the industry. In fact, this has been examined quite extensively: Price's law states that the square root of the number of people in an organization is doing half of the work. His work originally referred to academia and the publication count, but has also been applied to companies.
So you'd have a hard time arguing whether academia has a "lazy work culture", or more precisely: whether it has a work culture that is lazier than that in the industry. One reason for that is (not an argument for any side of the debate, but just) another observation: It's really hard to quantify academic work. When filling up shelves, standing at an assembly line, or chopping wood, for that matter, you can trivially measure and compare the amount of work that has been done. The more "abstract" the work becomes, the trickier it is to quantify it: Even in the industry, at a certain level of the organizational hierarchy, people are pushing numbers forth and back, trying to quantify the revenue that can be attributed to a manager, and at some point it's certainly impossible to break this down to the individual employee. In academia, there are very few conceivable "key performance indicators" at all. (A distressingly common one is "publication count", but we know where that one leads...). There are few people in the world who could dare to "quantify" what a certain researcher has achieved, let alone make a profound statement about how much time would have been "appropriate" for that achievement.
(So, subjectively, I wouldn't say that academia has a "lazy work culture" per se. But I'd tend to say: For someone who is lazy, academia makes it far easier to get away with it - particularly when the person has tenure. Strongly related: What happens to unproductive professors? )

But then, getting tenure is very hard if you're lazy, in most fields. (Though I think I agree with your final paragraph.)

@sgf That's probably true, although it certainly depends on the field and country etc. I'd even go so far to say that at least some people recognize the potential for being lazy, and do a shallow PhD while establishing the right contacts, with the explicit goal of receiving tenure and then essentially retire, but these are (hopefully) rare, and can in a similar form be found in the industry.

Lazyness is not  the only reason why the prices law applies. It  has also a lot  to do how the organisation works. Sometimes you are rendered ineficient because of external factors. This can havbe a devastating effect on your productivity and morale. Even without post  rationalisation, being lazy can be beneficial even productive with the right environment. And working  your ass of can still lead to no effect because your wofk is wasted.

@joojaa Sure. And after all, laziness in considered one of the three virtues of a great programmer. Beyond that, as a former colleague of mine once said: There are four types of people: 1. Smart+Industrious, 2. Smart+Lazy, 3. Stupid+Industrious and 4. Stupid+Lazy. And the worst ones are not Stupid+Lazy, but Stupid+Industrious ones ...

You don't even have to go more abstract in work to make it hard to quantify. As soon as you introduce quality of work as a second metric it starts to get hard. If two people are filling up shelves and one does a sloppy 20 shelves in an hour, the other a neatly organized 10 in the same time, the second seems lazy, until one of the sloppy filled shelves topples over and crashes unto one of your customers.

@Falco Agreed, although what I said about "quantifying" academic work shows that it's even hard to define "quantity" and "quality" here. Applying some of these questionable metrics one could ask what is better: One paper with 400 citations, or 4 papers where each has 100 citations? In both cases (industry and academics), one could argue that mediocre work takes disproportionally less time than good work, and noticing the difference can be difficult. In research, the difference can only be seen by people who deeply understand the subject, and there are generally few of these.

In short, no. However, I would say that it is often an inefficient and poorly organized work environment where people often end up overworking slightly to compensate for the inefficiency. Academia is pretty high up there in terms of being a demanding sphere with a lot of work, but there are worse industries - surgery, finance companies, certain startups can be a lot worse.
Let me touch on some misconceptions in your question:

Just because you see people there for 3-4 hours a day, doesn't mean they are only working that much. There were times when I would come in to lab at 4 in the afternoon, and it probably looked to other people like I worked only 2 hours as I left at 6 to eat dinner (breakfast for me). However I would end up coming back later and working into the early hours of the morning. (I absolutely do not recommend doing this!) Sometimes you just want to work in peace with few distractions, and so end up working weird times like very early morning, very late evening or weekends. Sometimes you elect to do your big chunk of work on the Saturday instead of Friday, because it doesn't matter when you do it but traffic and parking are a lot better on Saturday.
Academics sometimes "work" from home, but they often actually work from home. Reading papers, emails, writing papers or applications, grading are all things that can be done anywhere. I don't recommend this - eroding the psychological division between living space and work space has negative consequences for most people, but many do it anyway. Just because they're not at work doesn't mean they're not working.
Research, like much creative work, is not a linear process where you can make consistent, incremental gains. It's not like clocking in every day and assembling x widgets, and you get x/y of your quota done. Sometimes you can make great progress by goofing off. Even though breaks seem like a complete distraction from work, your brain still processes things "in the background", and when your break ends you magically "get" much better ideas (in reality, you don't get the ideas, the same idea you've always had just moves from your subconscious to your conscious mind). Rest generally improves the quality of creative/intellectual work as well.
There is a HUGE variation in how a PI will run their lab. There are PIs who genuinely don't know or care when you show up. There are those that mark the minute you came in and time your lunch breaks like a foreman. There are PIs that will chastise you for working on weekends or after hours, while others demand it (that's an infamous letter and a pretty extreme example, but read that and tell me about "lazy academia"). There are PIs that have strict work-life separation, and then others who get mad if you took more than a couple of hours to answer their email at 3 am on Sunday. While there's a general trend, it is fairly irrelevant because what matters is the particular situation in the group you end up in. Yet another excellent reason to carefully consider who to choose as your graduate advisor.

The work culture of academia pervades all levels, but the PhD is a pretty strong early peak. What happens is that you get talented young people, who are very passionate about their work, lack perspective and maturity, have little or no actual work experience, and feel omnipotent because they have just been accepted into the PhD program - the biggest accomplishment of their life (and in their minds, of the world). These people are given enormous freedom in deciding how to structure their time (as a result, many don't). Add the inherent randomness due to working in completely unknown territory, and it creates all sorts of bizarre work styles. Many fail to see the point of doing anything besides their research, so they work till they drop, and then they do drop, then they become horrendously inefficient and just go through the motions as they recover from the burnout, then there's a break in the research or some other serendipity happens which excites them and the cycle repeats.
The "up" part of this cycle feels incredibly productive, but overall it's usually much less efficient than slow and steady work. Almost every person I've known who treated their research like a 9-5 job seemed to do better as a result. There's a saying that a PhD is a marathon, not a sprint. But young folks are always eager to sprint. Of course, in some sense trying to force a regimen on creative work is a futile effort: You either have ideas or don't. You can do some things to make the best use of the ideas you do get (keeping an idea journal, thinking things through, reading relevant papers, talking to colleagues, rotating ideas when some are stuck). But inspiration isn't really obligated to provide you with a good idea no matter how hard you squint at a problem. Sometimes, you just don't see it no matter what you do. And while there are some common ways to boost creativity, ultimately everyone has their own personal "triggers" that work only for them. That said, many academics are very far from that point of diminishing returns from being more organized. Especially for students, it's more a matter of the student having very little notion of real organization or the need for this. Due to the non-profit nature of academia, feedback on efficiency is very subtle and it takes a long time for many to learn it. In the closely allied field of industrial R&D, the feedback is much more direct - the company has a bottom line which imposes some requirement on the researchers to exercise and demonstrate efficiency. Industrial researchers often seem like some of the laziest, least organized workers in the company, but compared to academic counterparts they are much more organized.
In my opinion (based on my own experience) academia is very inefficient. People work a lot, but because the work is not structured well, a lot of their effort is wasted. They accomplish far less (which is still a lot!) than they could have. Part of the reason is lack of fiscal incentives, part is lack of experience and formal training in being organized, part of it is just cultural inertia. What this means for you is that as a prospective PhD student and academic, you should make an effort to be disciplined and organized as much as possible. You will learn the value of these traits whether you like it or not - but you have the option of learning it the easy way rather than the hard way.

Sorry to spoil your statistics (if it does), but some of the really bad PhD students I've met were of the very organized, orderly, 8 - 4 or 9 - 5 type (the best lab book doesn't really help if you cannot get simple stoichiometric calculations correct) - to be fair, I've also known a very good and 9 - 5, organized, orderly student. The bad students probably wouldn't have gotten so far without being so organized. I think this is a bit like what I once heard about school maths: calculations and rewriting calculations will be correct without understanding if only the formal rules of manipulating..

... the symbols are obeyed. But there's a limit how much "senseless" rules a human can keep in mind at the same time. This was proposed to explain the observation that quite often 11/12th graders are found to "suddenly" get bad marks in maths - and looking into the matter it turns out that more basic problems are underlying such as: did not understand fractions. Also here one may say that being orderly and industrious, they did get further than if they had not been (11th grade instead of 6th grade). Same with bad PhD students who'd never have been ending up as PhD students otherwise.

Then again, unorganized but otherwise good researchers may be more efficient if they'd in addition be organized.

As a beginning PhD student, I always have been keeping in mind that I'm running a marathon, because if I'm having a work style I cannot keep up with during my PhD, how on earth am I going to do so for the rest of my career? Or, to choose the words of the letter you link to: if working in all evenings and weekends is expected, I indeed need to correct my work-place immediately.

1/2: Before reading your parenthetical clarification, I thought your link might be to this PHD comic, which I think is worth mentioning since it speaks to widespread views of academic work culture, at least in engineering.  When I was a PhD student in 2007, that sort of view motivated me to target 70 hours of productive work per week, which I found to be the most I could sustain for long periods.

2/2: I partially disagree with your last paragraph about inefficiency, based on my own experience.  While there can be room for the sort of wasted effort you describe at the PhD and postdoctoral levels, I find that those who manage to make it onto and through the tenure track (and especially those who have families) are forced to become hyper-organized and brutally efficient in order to survive.  This supports a small ecosystem of academic productivity coaching/training firms including The Professor Is In, Cathy Mazak, Katy Peplin, to mention just a few I've personally encountered.

@cbeleites Appreciate the comment - as they say, the plural of anecdote is not data so I don't think you spoiled anything. I definitely agree that I generalized a lot, but in my experience (experimental STEM discipline) being organized seemed to help in an overwhelming fraction of cases. Note that being organized is not just doing a 9 to 5 - it's also about taking notes, planning ahead, sticking to the plan, managing your time within the 9 to 5 and so on.

The optimal level of organization and discipline probably differs for each person, but I doubt it's ever zero. Whereas I think many students (and scientists) naturally tend towards almost zero - therefore I think it might be a good idea to resist this tendency and try to be more organized. Of course, there is probably a point where you are over-organized and lose productivity - I doubt military-level discipline would work with research (although then again historically militaries have been able to make some phenomenal research progress when they needed to).

@Discretelizard The letter is a very extreme case and 90% (99%?) of PIs are not like that (even Dr. Carreira now claims the letter was a joke). Not 100% tho - I have personally known (and avoided) people who have similar attitudes. I have also known students who thrive in such an environment. But working weekends and nights is not necessary for success in science. My point was that there's a wide spectrum of academics from extremely lazy to the horrifyingly non-lazy.

@DavidSchaich Agreed re: tenure track, that has been my impression as well. Although FWIW, after getting tenure there is theoretically an opportunity to take it easy - which few people take. However, not to second guess you, but in general I don't think PhD students work 60-70 hour weeks. I believe the average is actually something like 38 hours, but everyone thinks they should be working 70+ hours, many fail to sustain that, and experience a lot of unnecessary stress which then reduces their productivity.

Also for any young academics reading this - The Professor Is In is also a very good book about structuring your academic career, as is Getting What You Came For by Robert Peters.

@Trusly Well, I guess my main point was that that particular environment the letter illustrates is not a place where I'd be able to succeed, regardless of whether it is common or not. I agree with your point and I think my own work-ethic matches with my current environment (While my advisor once told me he has no concept of "free time", I don't think he implied I'm expected not to either...) and I think that is also an important factor to look at when deciding where to work (or do PhD "work") in academia.

@Discretelizard Fair enough. FYI, just because your advisor has a certain work style doesn't mean you should - unlike him, you are not a (tenured?) professor and don't necessarily have the same goals. If (and only if?) your goal IS to obtain tenure, then your advisor's lifestyle is a valuable case study, but you should at the very least also consider the lifestyles of other professors in your department as valid alternatives.

@Trusly I'm not in US and I don't think there really is a concept of 'tenure' over here. My advisor neither seems to be among the busiest nor the least busy of the permanent staff in our research group. But yes, I in fact cannot even evaluate whether my advisor is particularly busy wrt. his 'paygrade' or not, because I have no idea of the full scope of his activities, nor of what standard he is being held to. That is, no idea other than that it is likely very different from my own. I mean, I could definitely ask, but I don't think it would be very helpful for the reasons you just stated.

I'd like to add a few points that I've not seen in the other answers so far

I'm doing a summer internship at a research center at a university

This may have a lot to do with the observed laziness.

Summer is when people go on vacations, which may mean that others who need the vacationers cannot (or do not want to: they may even have promised to wait) go on with certain projects until the other is back.
BTW, this is also true in industry (e.g. closing of some production lines).
For those who have family, summer is also the time when kindergarden and school are closed for vacations: parents may have to come late/leave early/take days off - basically looking after their kids in shifts with the partner.
The same if not more in industry.
Summer is right after exam season. When I was working as university researcher, end of the year exams meant that many of us had to do overtime in order to get the corrections of the written exams done, and to take care of the oral exams. Also the labwork practicum protocol corrections had to be finished and marks given.
After that, people may take off the overtime they worked before.
Research internships are part of the teaching. They usually have a net cost of time for the supervisor of the intern.
Therefore, internships are usually offered at "lazy" times: when few people are around, so noone needs the instruments and there's an office space for the intern. Also, when there is sufficient free time to take care of the intern.
You wouldn't (shouldn't) want to be intern as a 2nd year student during times when the group is working really hard.
(Contrary to this, summer can also be the time to get busy with crazy side projects because the others involved with the main project or are anyways away. Or the others with whom the instruments are shared.)

I understand that academia isn't the most "organized" area

@Trusty has brought up some interesting points how being more organized yourself can help tremendously in research.
That may be the case, but IMHO the case isn't that clear:

I'd say that much of the work I've been doing as researcher that lends itself well to strict organization and structure could actually have been done by a technician or administrative staff. Which would be cheaper macroeconomically but for specialties of academia.
I'm not sure how such organizational structure correlates/interacts with the creativity needed in research. To formulate it pointedly: is scheduling out-of-the-box thinking from 8 till 9 in the morning a good idea?

do most of their work at night -- which, obviously, is impossible in a regular job.

Academic research allows for this flexibility, in contrast to research at governmental institutions or in industry. Thus, people who like that flexibility will tend to accumulate in academia, and people who are not comfortable with others following such flexible schedules will probably tend to leave the academic environment.

Yes, deciding lazyness vs. efficient work is not easy for an (almost) outsider:

Some of the most perfectly industrious (actual and visibly) lab work I've been doing, namely, aligning and calibrating instruments when starting measurement series at the same time was necessary and in a higher sense highly inefficient: Without the "academic abuse" these instruments were subject to (read: other researchers working hard), instead of a full realignment and calibration of half a day's work 15 min of measurements to show that it is still aligned and well calibrated would have been sufficient.

 I also see people often passively sitting on their computers and not really actively doing their work.

Yes they may just be lazy. An academic researcher browsing news or totally unrelated youtube videos can be lazy just like an industrial worker taking lots of smoking breaks. Just that it's typically a bit more difficult to decide at the first glance whether the academic is lazy or, say, looking up examples for a lecture (other answers have more examples). Like it is with industrial worker who is lazy by going for each tool extra instead of bringing a cart with all or most tools at once. Or adminstrative staff that sends back a form as soon as they find one mistake, and once that is corrected, send it back with the next mistake and so on instead of highlighting all mistakes or possibly even explaining why the form needs to be filled in differently and how.
I certainly admit to having lazy days.
However, I've also found that many of the "nothing really productive done at the end of the day" days were quite filled with tons of "tiny" tasks that each took quite a bit longer than I'd like them to take. (Administrative bla, phone calls, answered emails, sort some papers, ...) - that may not be the laziness you refer to, though.
One more point that makes seeing whether a fellow academic is lazy when "not really actively doing their work": part of the academic work is learning. In contrast to the undergrad version of learning which uses a textbook that you can study front to back, lots of the learning as a professional takes place by coming across
interesting things that are more or less closely related to your field and then, instead of ignoring them thinking about them. And by coming across questions where answering challenges and then clarifies your mental model. (That's what I'm doing right now, in a meta-way of my actual work)
There may be an inherent tradeoff: part of the personality that is required to be a good researcher is intense curiosity. However, this curiosity will usually not stop short of what is considered outside your field, and it may make researchers prone to "waste" time reading through the internet (or books/papers/encyclopedias). I personally think that this is all in all good for science. The apparent waste of accumulating "useless" knowledge is just a price we have to pay in order to increase the chance to  have knowledge that turns out be useful when it is needed. This includes   accumulating lots of loosely or unrelated (actually: not yet related) knowledge. At some point there may be something that will trigger "there may be a connection" - and this is what I need that previously "useless" knowledge for.
I may say that after accumulating such knowledge for 10 years, I started to feel efficient in my profession in the sense that for many new problems I come across in my field I can produce an idea where to look for suitable approaches quite fast. Now, after 15 years of professional experience, I'm learning as fast as ever.
Also, it's often not easy to see what level on concentration different tasks require/how tiring they are and in consequence, what recovery is adequate afterwards.
Also applies to industry.

the drive, intensity, and seriousness that I see in my romanticized version of the world of academia.

Working at the utmost limit of your (intellectual or whatever) capabilities means that you'll need time to recover from that exertion. So we're again back to lazy scientists...
The intensity of work you can keep up for 8 almost consecutive hours every day will be just middling compared to what is possible for shorter times with appropriate breaks in between.

You asked this about academia, but since it compares academia & industry, let me start by answering your question from an industry perspective as an analyst & data engineer as the basic issue seems to be not understanding the differences between what different fields consider "work":
TLDR;
In industry, government, or academic work this all comes down to the old saying "perception is reality". If someone has an idea of what "hard work" looks like and you don't fit it that person is going to assume you're not working hard and are lazy. No matter how hard your actually working or if you find academic work to be the most challenging work you've ever done (after five years in industry and six in government).
Work that doesn't look like work
Dmitry's answer covers most of this, so I'll just add the industry example:
At my first industry job I might be staring at the screen waiting on it to finish compiling or building. This was common, and I couldn't leave, because I needed to see if there was an error, but I also couldn't really do much until it finished. As an analyst, I now find that is more waiting on my data analytic programs to finish or actually reading the results to see what I can figure out but essentially - all of it is work that doesn't look like work.
Not working a normal 8-5
Further, to address these statements:

For instance, I've spoken to professors who say they do most of their work at night -- which, obviously, is impossible in a regular job. But I've observed this getting translated into laziness. People will only come in to the center for 3-4 hours a day, and sometimes not even every day in the week. I also see people often passively sitting on their computers and not really actively doing their work.

That was pretty much my regular schedule as a data engineer (or even when I was a developer just not as often). I'd have weeks where 70% of my job was either done from home or really, really early in the morning (think starting work at 2 to 4 am). This was because to work on the systems we needed without slowing everyone else down and ensuring it just worked when people came into work at 8 am - that was the only choice. Then from about 8-10 am, I would just be sitting there watching network traffic, real-time analytics, bug reports, and other trackers we had and if everything was working I'd go home and go to sleep. If it didn't, time to fix stuff.
FYI, while waiting on those reports (to stay awake) we (IS department) were often accused of just standing around the coffee pot and gossiping for two hours and then leaving. As people didn't understand the gossip was all work related and us trying to stay awake at the end of a long day.
In academia, some will always assume that you only have to do two lectures a week means you're only working 10 hours a week even if it takes you 4-6 hours to prepare for the lectures and you then spend another 40 hours on research for your latest paper, grant proposal, theory, data analysis, etc. or work a second job because you're just starting out in the field. Partially if you perform all of these tasks at home. Such as when you're only remotely collaborating with peers and have only set a single "stand-up", in person, meeting a week.

Some years ago, my mathematician friend and I were talking about a world-famous mathematician we both knew, X, who had moved away from our institution a few years before to take up a prestigious position elsewhere. This happened around the time that X had published a series of groundbreaking papers developing a new and incredibly deep mathematical theory. Later the man would go on to receive many important awards.
My friend told me that his office door used to be a few doors down from X’s office during the time when X was developing his theory. Whenever he walked past X’s office, he said, he would see him there sitting at his computer playing online chess.
When the man got any real work done remains a mystery.

Maybe he was doing his "real work" while he was playing online chess.

@PatriciaShanahan  is that a thing?  like there seems to be this movie Trope that once a researcher is good enough their subconcious works while they do something else or they even take up a new hobby as part of their research
(also relevant to strategy games and art)

@HaoSun I got at least one patentable idea while playing solitaire. After loading in a lot of information, backing off and relaxing can let things mix and something new appear.

I often get ideas while playing games or doing some other non-work task. I think it's a bit like a fidget activity such as spinning a pen, it helps maintain a baseline of mental activity so I can tolerate inevitable lulls in my own thinking.

I believe there is some merit to your observations, and I can lend some validation as to their sobriety from personal experience in academia. A bottom-line lesson is that you bring the drive, intensity, and seriousness with you, that are helpful towards your own process of discovery.
Notably, it requires greater self-discipline to work effectively in a less-structured environment than it does to work in a more highly structured one. Consequently, it is natural to find that some slip under the radar of the less-rigorous environment and probably prefer it because they can get by with ease for a time. On the other hand, freedom from the constant pressure of production demands is essential to making ground-breaking progress and toward promoting creativity and mental elasticity. If true principles are discovered and documented during this season of relaxed constraints, the next round of production may be all the more fruitful due to the increased knowledge. I personally believe that all useful work consists of cycles wherein we spend some time in rigorous or intense activity, followed by time that is more relaxed, and that both phases contribute towards our ultimate productivity.
Consider the example of tree rings in nature. During Summer, abundant light and moisture are used to promote fast growth and increase the size and porosity of the tree trunk, facilitating nutrient flow between the roots and branches. During winter, growth is much slower and the accretion is narrower, harder, and usually darker. Trees would not be as strong without the Winter season and the harder, denser wood they build during those times, but they would not be as large or as vigorous or as healthy without the growth that Summer brings.
So research and production are symbiotic. There is a significant precedent in the Biblical commandment to labor six days, and rest every seventh. There is a great deal more we can accomplish by recognizing the cyclical nature of life and by leveraging rest and relaxed times in addition to productivity-driven times, than we can by giving exclusive focus to "getting things done" or to the appearance thereof. A key is to develop and exercise the discipline to use each block of time for its ideal purpose. Much of academic work involves taking in new material, working with it and exercising its functions to gain experience, which experience is then searched mentally or visually for connections, patterns and themes, inviting the inspiration that leads to new discoveries.
So in short, expect some bursts of intense activity as you labor through a mathematical problem on the board or hack out a prototype or have an engaging discussion, and also expect times of apparent lull as you immerse yourself deep in thought, searching for the connections you would never find if you were moving too quickly to allow them to come into focus. Move decisively and with energy once you know what to do (but don't wait until you know everything--there are great and important lessons to be learned by moving in a direction you feel is "good" but without sure proof in advance), and also take time often to be still and ponder your next move. Don't forget to eat and sleep, but don't let rest and recreation take over--you must be very alive, active, engaged and serious to bring the best fruit to bear from your research. Enjoy much seriousness, enjoy much laughter. The best discoveries come from the marriage of imagination with hard work.

Not to dismiss your concerns but I think this is a local phenomenon more than something due to acedemia specifically. I've been in industry for several years and I've seen people who are even lazier than you describe above and others who are some of the most hardworking people I've met.
You should maybe look around at other teams and see if they have a different work ethic that suits you.


text:
Two co-first author publications vs. one second author + one first author publication
Hypothetically, which of these authorship scenarios would look better to the eyes of a potential employer in the academic world of biology/bioengineering from the perspective of author A:
Work 1: author B*, author A*, author C - moderate potential for impact
Work 2: author A*, author B*, author C - moderate to high potential for impact
*these authors contributed equally
OR
Work 1: author B, author A, author C - moderate potential for impact
Work 2: author A, author B, author C - moderate to high potential for impact
My colleague and I have a theorist/experimentalist relationship with a work that has since fractured into two separate works. The second work is more theory focused while the first is more experiment focused. We believe the second work has a more broad ranged application and has potential to be heavily cited.
Pragmatically, author A is close to finishing his PhD and, besides these two works, he has one first author paper.

Sorry to interject, but fields for which this might be an important issue just seem weird to me. Not your fault, of course. But maybe an AI could parse out all of the nuances and come up with an algorithm.

I 100% agree. I'm annoyed for even having asking this question, but these nuances appear to be relevant in my field of study.

Surely it would depend on what the employer was looking for...

First, I want to make it clear that I am not in your field, and do not know what relevant people's attitudes to co-first authorship are. In addition, answers and comments to What does first authorship really mean? suggest that they may actually be different between biology and biomedical engineering, so that might be something to pay attention to as well.
The main point I'd like to make is that the nature of the papers can (and should!) matter - I would at least that to happen in my own field. Say if the more experiment-focused paper has minimal theory/modeling, and the theory-focused paper only uses previously published experimental data... Well, if the contributions look incommensurate (and remember that the journal might require author contributions to be clearly stated), people are going to see right through that co-first authorship - and that can reflect poorly on both authors. Even if the journal does not require a description of individual contributions, A would likely be asked about their individual contribution in a postdoc interview situation, for example.
Hence I would always suggest picking the natural/ethical author order over a strategic one. It's also generally better to get a paper out this week than having it delayed a month over an authorship order debate or prolonged strategic analysis... Co-first authorship should be considered if there are clear arguments for it on the level of an individual paper.
Now, overall I actually expect the two scenarios to have fairly similar outcomes (again with the caveat that I'm not from your field) - especially since I suspect C to be the advisor, who'd presumably write a fair recommendation letter either way. If pushed, I would say that the second scenario could hold a slight strategic advantage for author A, since A could appear to have a higher degree of intellectual leadership in the higher-impact paper. If it is more theory-focused anyway that may well be the case.

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text:
Improving my application package regarding Maths undergraduate grades [for Master in Economics Program]
I am looking for some recommendations about how I could enhance my application package for a Master (MA/MSc) in Economics, considering that I have low grades in mathematics courses, despite that I took 4 courses in this realm.
I really like mathematics and I believe that I am good on it. For example, after I finished my undergraduate career in Economics, I applied some of the knowledge acquired from previous courses through econometric modelling.
For that reason, taking into consideration that I have plans for studying abroad, I would like to know if there are some courses, international/standarized exams or any other strategies (considering the other sides of the application) in order to improve my mathematics grades register and convince the committee for graduate admissions. For example, I am considering to take the GRE as soon as possible.
Thank you very much!
Greetings from Peru.

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Does your previous university’s reputation matter when applying for a PhD?
I have been applying to PhD programs for the past 2+ years and keep getting rejected. I have pretty good degrees that I worked hard for from good universities (not the top unis).
For the past year I’ve been doing everything I could think of to improve my CV; working for free as a research assistant at a research institute, publishing, attending seminars and conferences, etc.
I always thought that all applicants were treated equally and were judged only by their grades, personal statement and CV. However, I just got my 15th rejection letter, and the university was “kind” enough to tell me that I was rejected because I didn’t meet their entry requirements, specifically, that the universities where I did my Bsc and MSc don’t have a good enough reputation for my application to be considered.
I have been told by academics in the past that potential PhD candidates aren’t judged using this criterion. So my question is, are Phd applications one of those things where people are told that everyone has an equal opportunity while the reality is wildly different? Because I would like to know if I’m wasting my time applying and putting myself through all this stress unnecessarily.

I work at a perfectly reputable university - probably slightly above average among all universities in the US.  Most straight A students from my department would fail out of a top 50 graduate program, though there are exceptions - and we do say in our recommendation letters who those exceptions are.

To be honest, your experience surprises me unless you are only applying to the top few universities or your previous university has some problematic reputation such as a predatory for-profit institution or one that values some form of orthodoxy over true education.

@Alexander Woo I have seen my letters of recommendation they’re pretty good, so I don’t think my ability or potential ability is the issue.

@Buffy my experience surprises me too; that’s why I’m thinking there’s something I’m missing, because I don’t think it should be this hard... and I have been applying to all types of universities from top unis to mid level ranking unis to what you may call bottom of the barrel institutions and still nothing. Both my undergraduate and master’s universities are mid level and have a pretty good reputation but aren’t elite by any means... so I’m left scratching my head.

Perhaps you were just given an excuse rather than the real reason. Someone who wanted to reject you but didn't want to think very hard about why.

This probably depends a lot on country/region. For example, my impression is that the ranking of the applicant's undergraduate institution is more important for European and Australian programs than for programs in the US.

I always thought that all applicants were treated equally and were judged only by their grades, personal statement and CV.

Applicants from different universities are not treated equally (at least not by my department's selection committee).
Your grades are looked at as a baseline (to filter out obvious rejections or single out interesting cases), and then a discussion goes on about the rest of it (CV, statements, references and research experience). You are missing two key parts (which you refer to in your comments but not in the question body): reference letters, and publication record. You say that you have read your reference letters: have you read all of them? It could be that you are experiencing selection bias - the referees who are comfortable with you reading their letters are ones who generally like you. In addition, nowadays top schools (in computer science at least) may reject your application if you haven't had at least one decent publication.

I have been told by academics in the past that potential PhD candidates aren’t judged using this criterion.

This must have been a misunderstanding.
The institution the conferred your degree absolutely matters. There is a huge difference between how a top 5% student from a top university and one who hails from a less renowned university is perceived.
This cuts both ways - good universities may produce inadequate graduates, and less reputable ones can produce excellent students. The institution is just a signal of your likelihood to succeed in your PhD.

Sure, it matters.  After all, the other schools did a selection process.
That said, I do think it is very normal for grad schools to reach out to people from various backgrounds.  Provided the applicants show top test scores and grades, it's not that hard to get into grad schools.  I used to even see a preference for liberal arts school graduates (at an R1 grad program) because the kids hadn't seen as much of the downside of the R1 life, yet.
It does sound strange to be getting rejected by 15 schools.  I would suspect low grades and scores--you did not describe them.
Also you don't tell us the field, which makes it hard to interpret.  Knowing the country helpful also.  Even among schools, there will be different practices.  But do you think all fields/countries are same and we can give all encompassing answers?
I think if you didn't get into any first go round, I wouldn't go applying over in subsequent seasons.  Move on to real jobs.  Don't spend your time fluttering around trying to rack up more bullets for grad school. But put your efforts into a normal career.

-1. Answers should not require clarification from the asker (that's for comments), and I do not think you have enough information to conclude that OP should give up on grad school altogether -- that is a highly personal choice that depends on OP's career goals.

You leave out your academic discipline, which may guide towards better answers. Also, the 'gap' between your current and prospective schools. However:
I think you may be overlooking another factor: the authors of your letters of recommendation.
If your grades/scores are sufficiently high, then this is clearly not what is failing you. Now, school reputation is a factor (mostly only tacitly, but there may be exceptions), but your letter of recommendation is possibly even more so.
The standing of the author of your letters matters a great deal - so you want a bigwig, if you can. Then, academics have several ways of signalling to their peers if the candidate really has their blessing or not (although, to the untrained eye, all of these letters look pretty glowing). After 15 rejections, should you be looking to another writer? Also, you could consider applying to non-US institutions (again, subject-dependent); the world outside the US offers wonderful institutions, many certainly less hung-up about the prestige of the sending institution. Good luck!


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What should I do to prepare to apply to a math PhD program?
A little background information first. I am about a year out of my undergraduate program where I double majored in Computer Science and Mathematics. My main focus was computer science and the math major was mostly for fun. Since I wasn't considering grad school during undergrad I never partook in any REU programs as I was planning on working in the computer science field long term. However after about a year working as a software engineer I miss studying Mathematics and am not loving my work as much as I thought I would. So now I am looking into applying for a PhD program not just because I am not loving my job but because of my love of Math. My love of Math is what led me to study Computer Science in the first place. The earliest would be starting in Fall 2020 but I think Fall 2021 might be more reasonable given the timeline.
This is where the bulk of my question comes in. Since I double majored, I didn't get to take as many math courses and so I have holes in my education such as Differential Equations and Analysis. I do have textbooks on these subjects that I have begun studying with but how can I show programs I apply to that I have the knowledge in these areas? Will not taking these classes affect my chances to get accepted? I should mention that I did take courses in Stats, Abstract Algebra, Number Theory, Combinatorics and Linear Algebra. My overall GPA was a 3.5 and I did well in most of my classes except for Abstract Algebra and Number Theory where I struggled more in, but I do have a reason for that as I was taking three Upper Level Computer Science classes at the same time as Abstract Algebra and then that led to struggling in Number Theory due to lack of understanding of some of the basics. Are there any other tips that you could give me to help improve my attractiveness to a program?

I have concerns about your mathematical maturity.  Out of the math courses you listed, abstract algebra and number theory are the ones you struggled in, which happen to also be the more "serious" (most likely upper-level) pure math courses.  You say you love math, but are you sure you will love math research?  Have you thought about which field of math you wish to focus on?  Something to consider might be getting a PhD in theoretical CS.

You might consider editing to add the USA country tag, if appropriate.

Possibly useful: All the Mathematics You Missed: But Need to Know for Graduate School by Thomas A. Garrity and Lori Pedersen (2001).

@zoidberg How would I find out if I would like Math research? I've read about research through books like "Birth of a Theorem" and the first time I really considered this degree was through reading that book. As to what I would like to focus on I'm not sure yet. Logic piqued my interest through some study of Russel but then I also find elliptical curves interesting and the work of Hardy.

(US-specific) The REUs don't matter much for admission. The problem with not having analysis at all on your transcript is that most programs use it as a litmus test for whether you are able to write proofs and handle graduate coursework. The fact that your weaker courses were number theory and abstract algebra is also going to raise red flags in that regard.
There might be programs that would be willing to take you as an MS so that you could remediate, but probably the best course of action is to just register for a year as a post-bac or nonmatric somewhere that offers upper-div math courses.

I was afraid that those two classes would be a detriment. It wasn't that I didn't understand the material I just didn't have the time to commit to master the material for exams due to time consuming assignments for my CS classes. Thank you for the advice I will look into taking a couple classes at a local college.

I'll assume this is the US. It might apply elsewhere, but I have no experience. In the US, it is possible to apply for a PhD with "only" a BS/BA degree. Those degrees vary widely and some smaller schools don't have enough faculty to cover the very wide mathematics territory very deeply. Graduate admissions people understand that.
On the other hand, most such doctoral programs include at least the possibility of additional coursework before prelim/qualifying exams and research. Some schools require it. My first graduate level course was in Measure Theory (new to me) and I did little but coursework for three years. Another early course was in Topology, and was much deeper than anything I saw as an undergrad.
In addition, a doctoral dissertation requires a very deep dive into a very narrow part of mathematics, and, while breadth is useful, it isn't normally necessary to write a dissertation.
The conclusion of all of that is that you are probably already qualified for admission, other things being equal, though you will find a lot of competition from well prepared applicants.
My advice would be to apply ASAP to one or more programs and write up your background and experiences in the most positive way. You need to give evidence of your likelihood of success and your letters of recommendation need to support that.
But for the direct question - what to do -, you can find a way to improve your math knowledge and skill, either working toward breadth (analysis) or depth. But the way to do that most effectively is with a guide of some kind. If you are near a university you may be able to take individual courses and so obtain the guidance of a faculty member. You might be able to do it for no credit or grade. But the advantage of doing it formally is that you get both guidance and feedback. The feedback is essential, not just for looking at your work, but for suggesting what you should look at next.
Reading existing texts will not have the same effect, though reading along with a lot of problem solving will be better. But, again, feedback on your solutions to those problems can be extremely valuable. If you can only solve things awkwardly you need to find ways to "up your game". Practice and feedback.


text:
Mistake in uploaded file type after revision
I have revised my manuscript in Elsevier's journal and uploaded it along with the point-by-point reviewer comments responding. I found I have made a mistake in uploading the file.
There is the list of file types need to submit in the author page as follows:
1. Manuscript (revised manuscript)
2. Respond to reviewer
3. Revised manuscript with Changes marker
For the file type number 3, I uploaded the wrong file, which lists the changed in manuscript in detail instead of the full manuscript with changes marked.
I wonder Do I need to write an email to the editor to explain about that? Anyone has experience in this problem please give me the advice.
One more question: how long should we wait for the status change from "with journal" to "with editor" or "under review" for the revised manuscript?

You can email the editor.  However, the admin person processing your paper may notice the mistake and send it back to you.

Mistakes can happen.
You should email the editor or they might notice it and ask you to upload the correct one.
"One more question: how long should we wait for the status change from "with journal" to "with editor" or "under review" for the revised manuscript? "
It depends on the journal, you should check the journal website for more information or ask directly the editor.


text:
duplicate published data figure
I read two papers just published online (paper no.1 accepted about 1 month before paper no.2) in the same journal by the same authors.
Two papers have the same topic, using the same numerical method, same at least one simulation object. I found in paper no.2 some figures that very similar to paper no.1. The example of the figure in these papers shows in the picture below. Fig C is exactly the same in the two journals (just change the view angle a bit) while Fig A, B, C, and D are different. However, there is no statement that the data in Fig C has been published in paper no.1 and no citation. Additionally, there are also some similar figure data in the two papers but just change the axis scale.
So can it consider as duplicate data?

Do they at least reference paper 1 in paper 2? If these are simulated data, there is not much point in indicating they are the same if it's already indicated that they have been generated the same way, in my opinion. Though also the authors might have been in a tricky position if they've submitted both papers at about the same time. Maybe more importantly - why do you care, specifically?

yes, they mentioned paper 1 in the introduction. But in the discussion result, no citation or statement about the data has been published in paper1. Because of the same numerical condition with the same method, So I think the data must be the same

Last time, I published two papers in two different journals, I used the same method, same object but discussed different topics. Paper 2 was submitted several months after paper 1 is online. But editor from the paper 2 sent back the manuscript to me and said paper 2 has many parts similar to paper 1. it is somewhat similar above situation. And I had to remodify the paper, cite the data in paper 1 in the figure of paper 2

Duplicate data is mostly a problem when the data are experimental/real-world data and where repeating an analysis with the same data makes the overall literature seem to support a conclusion more strongly than it would if it were presented only once.
Let's say you have an experiment showing that green jelly beans cause acne. You publish it once, but people keep some healthy skepticism. Now suddenly 2 more papers appear that say green jelly beans cause acne... oh my! This is becoming quite the interesting field of study! Well, if these are 3 independent data sets, it appears to be a fairly strong conclusion supported by replication. If they're actually the same data set analyzed 3 times, now the authors of the second two papers have committed academic misconduct if they haven't made it clear that this is the same data. If you were conducting a meta analysis you would want to be careful not to include more than one of the studies.
The second issue is with copyright of figures. Typically the journal publishing a paper has copyright of figures published in that journal. Copying a figure from one paper and presenting it in another may violate that copyright. However, you can't copyright data itself, and there are only so many ways to plot some types of data, so the extent to which this sort of copyright is valid is quite narrow.

In the situation you describe, you have simulated data. The jelly bean issue isn't really relevant for simulated data. The papers are also in the same journal, so it's not going to argue with itself that the figures are too similar to a copyrighted figure that they own the rights to (to cover all the bases they could ask themselves for permission, but why?).
If the simulated data are created by some complex methodology, it is important to cite a previous paper using the same methodology to properly credit those authors, but sometimes this isn't really necessary. For example, if I generate simulated data by adding noise to a sine wave, it's probably sufficient to describe this. Sure, if another paper in a very similar area used exactly the same parameters, it's good to cite it to be thorough, but a sine wave plus noise isn't really much of an intellectual contribution and if it's skipped I don't think any major crime is committed. Maybe less so if it's the same authors not self-citing.
The only issue I can possibly see here is that the authors have perhaps padded their publications a bit by splitting one paper into two and publishing them separately. Reviewers can certainly comment on this, and can argue that the similarity of the second paper to the first makes it less suitable for publication, but this has very little to do with one set of simulated data that are the same/similar in the two, it has more to do with the rest of the publication.
I'm not sure why you're worried about this case except for some perceived unfairness in how you were treated versus them, but I don't see any benefit to you in pursuing this any further.

Thank you Bryan.


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What is the current status of submitted manuscript?
I submitted a manuscript to ASME journal. Now the different status is showing as in the figure below: in the general screen, the status is associate editor assigned. However, in the detail screen, the status is under review.
I wonder that the manuscript now has been sent to the reviewer and is under review, or still with the associate editor?

I know the journal workflow. I wonder here a different status appeared. Then, what is the manuscript status now: with AE or under review

It looks like the AE is looking for reviewers or even still doing the preliminary review himself, to decide to which reviewer forward your paper. A long way to go ...
You can always wrote the journal (not the associate editor, just their contact/customer care) the exact same question and bring here their answer.

The associate-editor is the person who is handling your manuscript. He is not the person doing the reviews. The associate editor send some e-mails to some researchers to invite people to review your papers. These reviewers will submit their reviews and then the associate editor will make a decision on your manuscript based on these reviews.  The decision could be something like : accept, reject or need to be revised.
So there is no conflicts between these two status. An associate editor was assigned to handle your paper. Then, "under review" means that the associate editor has already invited some persons to review your paper and that at least one of them has already accepted.  Now, it can take some time before all the reviews are submitted... sometimes weeks or months. Then eventually you will get the result.

So it means the manuscript has been assigned to at least one reviewer. That is what I want to clear here. Thank you Phil!

Yes, for some journals, the paper will have the status "with the editor" and then as soon as at least one reviewer accept the invitation to review, the status will turn to "under review".  Then, maybe later, the status will turn to "review completed" and then after that the associate-editor will take a decision on your paper.  The names of these status may vary from one journal to another but that is usually the process. You are welcome ;-)


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Plagiarism of former supervisors copying from my master thesis
I graduated a couple of years ago performing a master thesis with two supervisors. They both were happy about it and wanted to write a paper from my thesis, including me as author, but after my graduation I didn't hear from them again. It is worth to say that my supervisors had the pdf file of my thesis and all the figures and plots in vector graphics.
To my surprise and deception, I found out that my two former supervisors have published a journal paper based on my master thesis, which is not cited. Not only they have reported all of my plots, but they have also copied the captions (with almost no modifications), equations, tables, and entire sentences (some of them just copy-pasted, other ones with very minor modifications). Moreover, the simulations section reports 2 simulations that I carried out during my thesis, and both the parameters, the plots, and the analysis of the simulations is basically copied from my thesis. After all this content taken from my thesis, I only see that the authors have just acknowledged me in the article for the simulations only, and not even for all the plots and all the sentences they used.
Needless to say, this situation makes me very angry and frustrated. I would like to know, given this situation, whether:

I can accuse my former supervisors of plagiarism, contacting the editor of the journal and proving that a very large portion of the paper is taken from my thesis, which is not cited. Although my thesis is not available online, the authors could have included it in the list of references, and I can prove that they have a copy of it;
I can ask to be included as author of the paper, since most of the work published is based on my master thesis, and not only the "simulations", as the authors wrote in the acknowledgements.

Are you still in academia? Or doesn't it matter to you if everything "burns to the ground"? If you have nothing to lose in academia, you can roll in the big guns and say precisely that not only were your studies, but also your text used, which is pretty clear plagiarism and you expect amendment of the author list. Otherwise, you might consider being more political.

Agree with the above comment. I suspect you are not in academia and they behaved so incorrectly because thinking you don't care.  If you are in academia their behaviour is totally awful but it also more tricky to give you a suggestion.

That's a great piece of advice @CaptainEmacs. I am still in academia, though I do not know for how long. So I would opt for a more political option, but I still want to know which options I have

@Joey They already published - this makes it difficult to find a solution that preserves their face and secures your rights at the same time. How much substance is published, and how much more of the work is still unpublished where you could ask (well, in principle "demand") to be co-authoring?

@CaptainEmacs the article is 30 pages long and many subsections exist basically because I wrote something about that topic in my thesis. There is no other content "left" in my thesis, since all the publishable results were included in that article.

@Joey Phew, that's not good. If you intend to mark your territory, you could write to them and ask how it came you were omitted (by mistake? - although you know it's probably not) from the paper and whether they could send in a correction sheet to the journal. Again, it really depends how important the matter is to you vs. whether you stay in academia vs. when you intend to leave. It is incredibly upsetting, but if you wish not to burn all bridges, the idea would be to try to leave them a way open to save face and reinstate your rights as co- (well, actually first) author.

@CaptainEmacs that's true, but they already put my name in the acknowledgements, which means that they did not add me in the authors list on purpose and not by mistake...but with your comment I now understand that I have to be very careful and political with my choice. Even more considering that my current supervisor has some papers with one of my former supervisors

I can accuse my former supervisors of plagiarism, contacting the editor of the journal and proving that a very large portion of the paper is taken from my thesis, which is not cited. Although my thesis is not available online, the authors could have included it in the list of references, and I can prove that they have a copy of it;

Yes, you can do that.

I can ask to be included as author of the paper, since most of the work published is based on my master thesis, and not only the "simulations", as the authors wrote in the acknowledgements.

Yes, you can also do that.  Based on the information in the question, you should be an author on the paper.  I suggest you contact your supervisors and ask them to fix the author list first.  If that is unsuccessful, you should follow your university's grievance procedure.  Contacting the editor should be the last resort.

I understand your situation as I had gone through the exact same thing. Am sorry that it happened. Anyway based on my experience I would suggest you need to assess the extent of copying based on that you need to first try contacting the authors(if you want to maintain the relation request for the addition of your name give them time and wait for the reply). Otherwise, proceed with second step, get the contact info of the journal get in touch with the editor(if you are not able to directly get there don't worry try the section contact us to )obtain their email and mail that you need to contact the editor as the article with DOI is plagiarised/having significant overlap with your thesis.
Once you get hold of journal head/editor you may explain the case with proof (thesis) this step may take quite a lot of time. Then wait for their reply if your claim is genuine the editors may offer to add your name as author or retract. The entire process may take months, say 6-10 months or can be fast if its in press. Remember you need to be patient and follow up.
Goodluck

Accusing a colleague/former colleague of misconduct will likely cause you big problems. Hiring managers will always try to contact them and they will sense trouble in you. Unfortunately, if they cite you in the graphs it is arguably enough.
Outside of academia, the problem is worse, people will always take credit for your work. I would recommend to wait until you are a bigger fish, get more experience and then you will be able to do something about it. We all go through this.

If they supervised your work, they do have some right on the result. Check the exact guidelines, any licenses you gave to your school or funding entity. Before doing anything rash, do ask somebody knowledgeable with all details. Could be a trusted colleague or your lawyer.


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What is the best/most important form of publication in applied linguistics/language teaching?
I'm wondering what it is commonly considered to be of high value/importance amine the types of publications in applied linguistics/language teaching ? Is it journal article, conference paper, book chapter, books...?
What would be the best choice for Phd students seeking a position in Academia ( post-doctoral/assistant professor)

Actually, to be more explicit, this varies drastically by field.

Linguist here.
I would rank publications in the following manner:

books (reasonable to make plans while a grad student, but might be too ambitious for most PhD students to actually pursue while they're also working on their dissertations)
peer-reviewed journal articles, which I think I'd rank almost alongside books if you're publishing in top-tier journals.
book chapters
conference proceedings
book reviews

If you're only just starting out in your PhD program and haven't tried publishing anything yet, I don't think it's a bad idea to start with conference proceedings (if they come up) or a book review (journals or even through Linguist List), just to get your feet wet. However, as you advance in your PhD program, I would urge you to go up the ladder, and focus on publishing your work as journal articles.
I would also keep in mind that in any given category of publications, there's a lot of variation along the 'prestige' spectrum. For example, a chapter in an edited volume that's being published by university presses like Georgetown or Cambridge would probably be valued more than an article published in a virtually unknown journal.

At last, a linguist.

The most important publication for you as a PHD student is the publication that will award you your title. Normally that is your doctoral thesis although it can also be paper or two. That depends on your university.
After you get your PHD title then the most valued publications are papers (in peer reviewed journals) because researchers/academics are measured by the number of papers and even required to publish certain amount a year (creating of course a wide net of vicious incentives to publish as much as possible regardless of importance or quality, thats why there are so many predatory journals pout there and a whole business of ghost writing... yeah, I expect the downvotes from this.)
Then the industry (although it depends which) value books (but a book chapter would be a good start and then a book once you have more works to your name) and media content a bit more (Tech for example would value your github stuff and working prototypes/projects more than they care about a paper done during your studies).
So,the answer to what would be best for a PHD student regarding types of publications is to first foucs in whatever publication is useful to finish your PHD according to your school, and secondary about the type of publication that would help you afterwards according to your personal plans to go into the industry or go into academia/research.
NOTE: There's a middle but gray ground regarding research outside of academia and in that case articles might be of consideration for your case.

Journals aren't the preferred venue in all fields. Hence my comment to the OP.

I disagree with even the first paragraph of the answer.  Your most important publications as a PhD student are the ones that help you get a job after your PhD.  Just getting the degree is easy in comparison!

Not to pile on, but I agree with Buffy. Journals are the preferred venues for most of STEM, but parts of CS prefer conferences, and much of the humanities prefers books. Industry is similarly multi-faceted -- though I've never heard of any industry that prefers books, would be interested to learn which industry has that feature. Your advice in the fourth paragraph seems sound, though I imagine OP has deduced that much on their own. Hopefully OP will provide more information.

@cag51, hmmm. Book publishers prefer books. ;-)  Sorry - a bit orthogonal, I guess.

@JeffE , First thing is always to get the degree, and for many universities, publishing is requirement for such. Once that is secured, the student can focus on else. Worrying about getting a job afterward its like worrying about what you are going to spend the lottery money before you even buy the lotery ticket.

@deags No.  Always aim past the immediate target.  If you think finishing the PhD is a matter of luck ("a lottery ticket"), either you are woefully underprepared, or your advisor isn't doing their job, or both.

@JeffE You clearly misunderstood. Getting the title of Doctor is not a matter of luck as you think. It requires a lot of work,
strenuous amounts of homeworks and projects, and passing through a hell of bureocracy and tramits and permits. For many universities you don't even get to ask a professor to be your advisor until after you finished your PHD, which is when you can start the process of titulation to accredit the title. Please revise the international experience beyond your own opinions.

@JeffE Luck is an random occurrence. A PHD is the ultimate level of studies in a career and it involves, research, homework and bureocracy. Please revise any dictionary or as a particular question if your confusion remains.

@deags I've had a PhD for more than two decades; I've graduated several PhD students, some of whom have graduated grand-students.  I've been on dozens of PhD committees, in several different countries. I know exactly what it takes.  I stand by my previous comment.

Maybe I'm misunderstanding something in this exchange, but it looks a lot to me like @JeffE is saying "Getting a PhD is not about luck", and deags is saying, "No, you're wrong, getting a PhD is not about luck."

@Mark Meckes seems about right. Although I cant see where did JeffE got luck involved as something like that is never mentioned.

@deags: You referred to buying a lottery ticket.

@ Mark Meckes The whole phrase is 'First thing is always to get the degree, and for many universities, publishing is requirement for such. Once that is secured, the student can focus on else. Worrying about getting a job afterward its like worrying about what you are going to spend the lottery money before you even buy the lottery ticket'


text:
Finishing a Phd in two years and few months
I am a phd candidate in education. My doctoral program takes 3 years. However, I have worked very hard and got several publications that sole-authored. My supervisor thinks that I can  finish my phd in 2 years and a few months, but I am not sure about this move. Most of eminent scholars that I look up to took their time and finsihed their phds within the normal timeframe, so I am thinking that it is not wise to take the risk and finish earlier than the usual time.
I would like to have your take on this. Would the fact that I finish my phd in shorter time negatively affect my chances in getting a tenure-track academic position?

I agree with the answer below.  I've had students who finished 'early' with strong publications. Their career has not been impacted.   However, for the layman, a quick PhD degree translates to an 'easy' or low quality PhD.

@Prof.SantaClaus, "answer below" is ambiguous.

It likely doesn't matter much. The major question is whether finishing in two years will adversely affect the quality of your dissertation. If the quality of your publications is high and your dissertation makes a strong contribution to your field of research, it's unlikely that a search committee will care that you finished early. Depending on the type of institution you are applying to, they'll have specific criteria that they're looking for with regard to your ability to produce high-quality research, conduct high-quality teaching, etc.
If you believe that taking a third year to finish your dissertation will help you produce better work, then you should take the third year.

The other thing to consider is how it will affect you financially. If you pay for your PhD yourself, then you will obviously save money by finishing early, and might get some refund on tuition fees, or avoid having to pay "continuation fees" when you submit at the end of the third year, but it takes time to get you graduated.
Conversely if you are on a scholoarship or studentship, you might forfeit the final payments by finishing early. (although you'll be able to get a better paying job sooner).


text:
Is researchgate still useful?
It seems that researchgate is gaining some popularity in recent years. However, there is some criticism on their habit of sending requests and unsolicited spam emails?. What is your experience of using researchgate? Does it help promote your research and get some readership?

My impression is that Google Scholar is much more popular and accepted. Though both Goggle Scholar and Research Gate have evidently flawed data. I think that Orcid serves a completely different function though.

Was it ever useful?

@WolfgangBangerth Well, it actually is. At least in my experience many people seems more comfortable in asking copies of papers through RG rather than email.

Can you edit your question and elaborate on what it is your looking for?

Depends on your purpose.
If your aim is to track the publications of a given academic then I would recommend these in the following order of preference. Some of these may surprise you:

Google Scholar;

Google Scholar seems to capture more publication outputs any other source. This is partly due to the scope they have for including different publication types, such as  reports and discussion papers that many other platforms exclude. They also have greater capacity to show citations to those publications. This will often lead to a higher H Index on Google Scholar than on other platforms;

Microsoft Academic (Microsoft's weird equivalent to Google Scholar);

Microsoft Academic is the almost unheard-of equivalent to Google Scholar. It has a different look and feel but does more or less the same thing, but less well. It does not seem to capture as many publications as Google Scholar and seems to require more intervention on the part of the academic to keep their record up to date, and is therefore less reliable;

Twitter;

Whaaat? Twitter? Yes. Twitter. Many younger academics send a tweet whenever a new publication of theirs becomes available. It's as close to a real-time notification of new publications as you can get with those that do this consistently. Not very good for reviewing previous publications but great if you are following the latest from a particular academic;

Academia.edu;

Academia.edu is hanging in there as a platform despite being behind a paywall for many of their features. Many academics still maintain a record of their publications on this platform because it offers reasonably good analytics. But they have to keep it up to date themselves, which can often mean an inconsistent record of publications and often a significant time lag in publications being added;

ResearchGate;

As with Academia.edu above, only their analytics aren't as good, so there is less incentive for academics to keep this up to date.

Linked In;

Many academics use Linked In for their professional networks. They typically want people in their network to see what they are up to so they often keep a selective record of their publications there as well;

Their own departmental web page;

Updating their own department's web page is normally the last thing on the list for most academics. It's often a pain for them to update because they typically don't have access to this record themselves and are therefore reliant on the lazy-ass staff at their own institution to (reluctantly) update it for them - or worse - rely on the deeply flawed system their institution uses to track and report their research outputs. These often deliberately exclude publications which do not count for 'points' in whatever research incentive scheme they use. Don't get me started!
Finally, there are a host of platforms claiming to offer a definitive list of publications attributed to each author (including Orcid, Publons, etc). Orcid really exists as a means of attributing a unique identifier to each author so that publications might more reliably be attributed to the correct author. These have a role to play but they are not really designed as a means for making an author's publication catalogue accessible (and these platforms are simply awful to use, so many academics don't bother with them at all once they have their author ID number).
The main differences between these pertain to how much information is included and how they are updated.
Platforms like Google Scholar are more reliable as they do not rely on the academics themselves to keep their records up to date. Academia.edu and ResearchGate can still be useful, particularly where academics make the full text of their publications available through those platforms. Twitter and the others are useful for keeping up with the latest and getting a sense of what they think is important.
Try them out and see :-)


text:
Funding from Advisor
This semester, my advisor supports me financially from his NSF funding. So I was wondering if I can write this NSF funding in my resume in honors section?

It’s not an “honor” to be funded by a normal NSF grant, or any other grant. It’s how you got funded, and is not something you can typically claim as an “award,” because it doesn’t represent you specifically. The only exception to this would be if you were somehow involved in the preparation of the grant.

license: Creative Commons - Attribution Share-Alike - https://creativecommons.org/licenses/by-sa/3.0/


text:
Recommended for admission by the department but still haven't received official decision
I was recommended for admission into the Math PhD program at a large state university in the US two weeks ago and the department informed me that they are forwarding my application to be reviewed by the graduate school. The graduate school said they will review my application and will get back to me in two weeks for official decision. Two weeks have passed and I still haven't received any notification from them, so I sent a polite email asking about my status couple days ago. But at this point, I still haven't got any update.
What should I do now? Thank you.

Polite phone call to the graduate school.  Emails could very well be received initially by students, and given that many schools are on spring break right now, that could delay them (or just student workers losing an e-mail wouldn't be unheard of).
If the phone call isn't able to resolve any doubts, speak with the department you applied to and they can put some pressure on the graduate school.

I agree.  Be polite is key!

all_licenses: Creative Commons - Attribution Share-Alike - https://creativecommons.org/licenses/by-sa/3.0/