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Why do past PhD exams appear more difficult than current ones?
I noticed while doing practice math PhD exams that the newer exams tend to be a bit easier than the older exams. The online archive goes back about ten years or so, but I was able to dig up some old exams from the mid-80s. I was absolutely shocked. I would get wrecked if they gave me one of these. I don't even think I could finish one if they let me take it home.
I looked around at some other PhD exam records at other universities, and it seems to be an across the board thing, not just my department.
Some people I've asked about this give the explanation that PhD programs are bigger now than they used to be-- in other words, in the past, only geniuses got PhDs, and since then cretins like me have gradually wormed our way into academia and lowered standards for everybody. This would make sense, but I'm not sure if this is just something people say, or something that is actually true. People have a tendency to put the past on a pedestal, and I'm skeptical.
Another explanation I could think of would be drift in material content. Maybe they were studying different stuff back then at the same difficulty, or using different terminology to study the same thing we do now. Maybe it just seems harder to me because I'm not used to how they talk about it. A lot of PhD level material is, after all, reasonably modern.
I also wonder if exam practices used to be different-- open book, take-home, more hand waving tolerated in grading, offered at the end of the 5th year. Something?
All this is speculation, though, which I find unsatisfying. Has this actually been studied with healthy rigor and skepticism? What is the history?

I can't speak to a rigorous study of the history, but I do offer another possibility. Many fields have seen substantial advances in the past few decades. As a result, it's likely that PhDs have become much more specialized. Thus, you don't cover as much breadth of material in pursuing your degree and therefore those old exams contain a much larger spectrum of material than you are used to seeing.

It's very hard to evaluate the effective "difficulty" of an exam by looking at the questions without knowing the grading standards, and these are rarely made public.  (Sometimes they are not even formalized, but are the subjective opinion of that year's graders.) You speak in the first paragraph of not being able to "finish" the exam, but it may be entirely possible to pass the exam without "finishing".

I would speculate that the most likely reason is the instructors, and also course content/emphasis, has changed.  I'd be skeptical about asserting a change in difficulty.  I often find reading older treatments of material harder than more modern ones, because the latter are closer to the way I think about things.

When I started programming, it was basic C on a text editor without any sort of syntax highlight. The newer kids get a full-fledged IDE from the start, with more modern stuff like Java and C#. My course was all about understanding how code works and what it really does, understanding memory models, coding patterns, etc. The newer grads can barely write a "Hello World" program. Yes, I'm really salty about that.

(In mathematics:) I'd be willing to believe that pre-college math curricula, and lower-division college (in the U.S.) curricula have become easier to get through, for reasons mentioned in other answers and comments. But I think this becomes less universally so at upper-division level (last two years of undergrad in the U.S.) and even less so with regard to the sort of "prelims" that math grad students typically do/take in the first year or two of their graduate work. This reflects my observations over the last 45 years in math in the U.S.
So then how to account for the phenomenon apparently observed by the questioner? Again in my own direct experience, decades ago there were impulses to ask "interesting/challenging" questions on prelims, that even the other exam-writers might not be able to do. Some contest-like spirit, resembling the old Tripos in the UK? At the same time, again somewhat contest-like, the questions were at a lower mathematical level than nowadays. This, combined with the impulse to ask challenging questions, led to many Baroque, Rube-Goldberg-like questions whose statement alone might be difficult to parse, and whose relation with any known mathematics was unclear. E.g., very complicated questions about iterated operations in point-set topology, with delicate separation assumptions? Difficult questions about proving that a bunch of relations in a group implies another one?
After a decade or so of that kind of thing, it was apparent to me that such exams did not encourage forward-looking study on the part of the students, which was a bad thing. Often, as in prep for contests, some amusing tricks were learned, but basic, standard, useful more-advanced ideas were neglected entirely because they'd never show up on those exams. Thus, around 1989, we deliberately changed the nature of those exams to address less-tricky, higher-level mathematics that would actually be used by people in doing their PhD work. Another attitudinal change has been within the last 10 years, when we have moved completely away from surprise/tricky questions at any level.
At least at my own University, it's not at all the case that basic graduate education is being diminished in favor of supposedly jumping into research immediately. As in some comments above, it's not feasible to really start doing modern mathematics research while not knowing anything... But, yes, we do try to encourage a more active version of engagement than merely "fulfilling requirements" (even while those "requirements" are aimed to be useful).
So, in the end, I'd argue (as in other comments) that the exams are not truly easier, but just "modernized", so that some acclimitization to modern mathematics makes them seem easier in our context.
(And, yes, I recognize that in fact some grad programs in math have "thinned" their prelim requirements, apparently motivated by "getting students into research faster", but it is not clear to me that this can truly accomplish the avowed goals... though I am equally confident that programs would be disinclined to candidly discuss such a thing. The ever-increasing commodification of "research" does provide considerable pressure to degrade things...)

I think that you've discovered a fairly good example of credentialism and educational inflation. It's pretty well established at this point that over time there's a trend towards more jobs demanding higher degrees, jointly with more higher degrees being awarded. It makes sense that, for this to occur, standards are being relaxed over time. Note that this is a pretty solid evidential counterpoint to the de rigueur defense that an older generation always complains about a younger, or that "people have a tendency to put the past on a pedestal".
At a different level, we could demonstrate the same thing at the community college where I work. A senior faculty member has kept final exams for a variety of mathematics and computer science courses for a number of decades, and if they were lined up side-by-side there would be very clear evidence that current students would have nearly no chance at passing prior exams. In some cases what was once a one-semester course is now a two-semester sequence to cover the same material. And in the decade that I've been there, there's been a fairly public process with making general-education exams easier in an attempt to get a majority of students to pass them (maybe 4 iterations of downshifting the university-wide basic math exams by administration).
You might consider whether this discovery itself makes for a worthwhile academic paper. Personally, I'd love to see that documented and published.

"standards are being relaxed over time" are you sure this applies to mathematics?

@GennaroTedesco The second paragraph of this answer pretty much answers your question "are you sure this applies to mathematics?". Furthermore, I myself witness similar phenomenon in my location - Taiwan which was well recognized by its quality math education, but not anymore.

I further clarified that these observations are especially about mathematics (and computer science) education.

I downvoted this answer because I do not believe it applies to PhD qualifying exams in mathematics (the topic of the question).

I've seen evidence of that in basic chemistry exams (inorganic and organic) where the same pool of questions has been used over several decades and a corresponding change in the requirements for passing. (However, even for undergrad subjects one may argue that school curricula may have been covering fewer subjects more deeply, and that this has consequences for undergrad courses.)

The fact that more advanced degrees are awarded can be consistent with standards going up. More people are receiving more education after all.

This very much depends on the area at hand ("mathematics" is a quite general thing that comprehends many different lines). It is however generally not true that newer exams and exercises are easier: it is instead the converse, as the study, the knowledge and the level of understanding go deeper as science evolves.
Notice however that finishing (or not finishing) a test/exam is by no means indication of the level of difficulty of the topic. As an example you could be asked to manually calculate the determinant of a 1000x1000 matrix in one hour: you will never finish that on time but it is monkey job with no difficulty or understanding required; as such, do not grant deepness of knowledge according to how messy or long or cumbersome the exam tasks may be.
Moreover, the argument of "difficulty" is usually very subjective. There are no easy or hard topics, there are just topics you are not familiar with because you did not study them before. One thing that is however true is that the flavour of research has changed as the time went by and different efforts and emphasis have been put on different topics; as such, you may find yourself to have a more natural understanding and practice on some topics and aspects rather than some others.
Are those old-style-exams that you are mentioning really more difficult and intense or is it any of the above that may come into play?

I've spent 8 years in academia. When I started, the maths were so hard just 4 students, out of 30, passed the Basic Calculus class. The exam I took back then was around five pages full of puzzling stuff. The newer, 2016 exam is around a page-and-a-half, with multiple choices, and no need to show real calculations. I felt almost cheated - I almost killed myself studying back then for an 8, and now those "fresh bodies" barely study at all and get a 9.5. Also, the grade you needed for an approval on that college dropped from a 7 to a 5. If this is not "getting easier", I don't know what it is.

I have never taken a "multiple choices" maths exam in my life, never seen anything of that sort. I've always taken maths exams with theorems to prove or sensible calculations to make. I guess the teaching of mathematics varies from one country to another, at this point.

Never did I during my college years. Still, it seems it's the norm nowadays in several colleges on my country.  There seems to be a trend to mass-produce diplomas, unfortunately, even in the high-profile colleges.

@T.Sar A (retirement-age) colleague of mine tells the exact same story. In fact, all my colleagues at various levels of age and seniority tell the exact same story. Apparently, university courses where incredibly difficult 40 years ago and got linearly easier since then. Or, alternatively, we humans have a tendency to vividly remember outliers and don't retain an accurate view of our standard coursework 10+ years later ...

@xLeitix Going from "show your proof" to "mark the correct answer" couldn't be explained out by me misremembering things, however.

I don't really agree with this, I have looked at qualifying exams from the 60s and their difficulty was less, or at least their assumed background was less. For example, many only tested on an understanding of advanced calculus instead of measure theory. Todays exams are far more indepth.

Speaking as a physics grad you can clearly observe this trend in our quals as well. For example UIUC has an archive with exams going back to 1995:https://physics.illinois.edu/academics/graduates/qual-archive. You can see a clear trend of the difficulty going down. Princeton's are still hard though but they seem to take the difficulty of their qual as a point of pride.

And I remember the Dean of the engineering department, when he made his leaving speech some 20 years ago he produced a final exam from 30 years before and said if we gave this now the students would fail. Also worth remembering that the exam was designed for log tables and slide rules as calculators were not in existence at the time for that exam. Now they use functions on calculators with no understanding of the maths & theory being used...

with no understanding of the maths & theory being used — [citation needed]  Using a calculator doesn't mean that you don't understand logarithms, and using a slide rule or log tables doesn't mean that you do.

I agree with this trend from physics, though my specific program has increased in prestige over time so it was less noticeable.
I don't think it's that people now are less innately talented or genius. The number of people getting physics phds has gone up, but access has also significantly increased. It reminds me of the quote by Gould: "I am, somehow, less interested in the weight and convolutions of Einstein’s brain than in the near certainty that people of equal talent have lived and died in cotton fields and sweatshops."
The thing is, education hasn't really kept pace with the increase in access. The people who went to grad school 40 years ago generally came from a class that gave then the best education money could buy. I struggled through undergrad upper division classes with 100+ students, and professors who had no idea who I was.
I think education got worse, but I'm not convinced the talent has decreased (though there are reasons to believe it may have, such things are very hard to measure).

I believe the larger trend is that PhD programs are putting much more focus on research over coursework. Not to say that research was ever not an important component of a good PhD programs, but the importance has greatly increased over recent years in many fields.
Students are expected to start writing papers earlier and to write more papers before obtaining their PhD, which necessitates spending less time on coursework. At the same time, as research becomes more and more specialized, it becomes harder to design good courses that will be relevant to the students' future work.

I'm not sure about such a trend for pure math--exams in the US are usually in the 1st or 2nd year, before one starts on research.  Though somewhat along these lines, I could imagine that some PhD programs in the US have been started demanding more teaching duties from their students, but I don't have any actual knowledge of this.

I did not down-vote this answer (I have not up-voted it yet, neither). But, I am furious about something here. Don't you need to have foundational knowledge before you do research?

@scaaahu Of course you do, but I'm talking about emphasis. I never said programs are removing coursework, but I think there's definitely a trend of deemphasizing it a little, especially the more advanced topics, in favor of learning by reading the literature and actually doing research.

@Kimball I'm in statistics, not math, but many programs I know have students started research during the summer after their first year (or even during their first year) and continuing it through second year. This goes hand-in-hand with many programs making qualifying exams easier or having fewer of them. Though it's entirely possible that my experience does not match the trends in pure math.

@RogerFan Students starting research sooner than they should is also the reason behind the skyrocketing of the number of bad papers out there.

Although I do hear people say "learn X by reading papers", in much of mathematics that would simply be impossible without considerable background, usually obtained by fairly systematic study of advanced textbooks or notes, whether in an official course or not. High-end published papers assume a very substantial body of knowledge, and it's essentially impossible to bluff one's way through such things, since there is also no general tendency to give useful backward pointers to textbooks.

@paulgarrett I'm not making a value statement on whether this is good or not, just that it's a trend I've observed in several fields. This may or may not be also true in mathematics, as that is not a field I'm very familiar with, but I thought the trend might carry over.

Roger Fan, I agree, things vary wildly from field to field... but/and there is a current fad of people suggesting that it is possible to "do research" without knowing much, since one can back-fill. In math, there are "REU"'s that purport to have (ill-informed!) undergrads "do research" in 8 weeks in the summer... This leads some of them to think that there's nothing more they need to learn, and why should a PhD take 5 or 6 years? Completely inaccurate expectations... So I tend to "push back" at least in reference to mathematics (having seen decades and decades of this trend...)


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How to manage your advisor's jealousy over your work?
Say you made a smart move in solving an important question that your advisor did not think of and all of a suddenly your advisor becomes jealous because you have made your advisor look bad. What are the best way to manage situation like this?

Can you elaborate a bit more on HOW you made him look bad? Did you correct him in public? Falsified his previous research? Made a dumb comment?

Is this question real or hypothetical? How do you know your advisor is jealous? What is she doing differently? It's probably better to try to change what she does; it's hard to do much about how she feels.

The nature of being a research adviser is that your students must exceed your expertise, especially on the topic of the student's thesis. If your adviser cannot handle this, perhaps you need a new one. If your adviser becomes openly hostile - get out of there. Don't walk. Run.

it's still not clear to me whether this jealousy is something you think is happening, or is something you have some actual evidence for. I'm asking because students often assume advisors think/feel a certain way when they actually don't.

I'd distinguish between three scenarios:

If you have accomplished something genuinely magnificent (e.g., you just proved the Riemann hypothesis), then it may be natural for your advisor to feel a little envious, particularly if it was something your advisor had hoped to do someday.  Hopefully they'll soon switch to feeling proud of their amazing student, and in any case your career success is assured by your great accomplishment.
In less extreme circumstances, this could be a real problem.  If your advisor feels threatened by your success, then you may need a new advisor, since you certainly don't want an advisor who goes around explaining how you aren't as great as you seem.  Before you reach that point, it's worth discussing these issues.  For example, you could say "I've felt some tension recently, and you seemed upset with me at the X Symposium.  Am I doing something that's making you unhappy?"  This may be an awkward conversation, but it's worth a try.  It's possible that you are somehow making the problem worse (for example, by publicly saying things about your advisor that could be interpreted as disparaging, even if you didn't mean them that way), or that your advisor will feel a little sheepish that you noticed this behavior and will try to change.  If talking about it doesn't work, then I don't know what to suggest.  You either find a new advisor or put up with it as best you can.
It's also possible that it's all in your head.  I become suspicious whenever I hear someone attribute other people's behavior to jealousy, since it's an awfully convenient excuse.  Until you have really clear evidence, you should keep an open mind regarding other explanations.

I have seen my advisor getting very jealous of my accomplishments sometimes.Bottom line is people dont like surprises. If you blow somebody away and the larger community with your work, your adviser will feel intimidated and will feel threatened and cut you off in short term. But eventually an good advisor will realize that you are a catch and will guide you and help you in your career .  A bad advisor will use you to get her things get done and will later treat you like she never needed your services in first place.

your adviser will feel intimidated and will feel threatened and cut you off in short term — Yikes.  Even in the short term, cutting off successful students out of jealously is completely inappropriate.  (Unless by "short term" you mean something on the order of hours, and then it's not so much "cutting off" as "needing alone time".)

@JeffE I am speaking from my personal experiences. Initially my advisor was very friendly[more like a co worker than a boss] , but the moment she realized what i had accomplished and how the industry was blown away by my work and offered me internships,she kind of started acting more i say formal[like a manager]. We filed for patents and wrote to CHI(holy grail of HCI Conferences) which was unprecedented for MS students from an small univ. in midwest. The moment i realized this , the more i hated and resented her and and i think she realized this and  our relationship went downhill from there.

@JeffE  Not much of a life lesson but it made me realize that people above you like you  as long as you don't fly above them . The moment you surpass them ,the relationship cannot last anymore.Not all success in life is for good .

it made me realize people above you like you as long as you don't fly above them. The moment you surpass them, the relationship cannot last anymore. — As painful as your experience has been, please don't extrapolate from a sample of size n=1.  (As an HCI researcher, you should know that already!)  I can't claim in good conscience that the childish behavior you describe is uncommon, but it is certainly not universal.

@james234 - Relationships between students and advisors can sour; sometimes this is the advisor's fault, and sometimes the student's, but there are probably many cases where there is plenty of blame on both sides. In your case, this remark seems telling: "The moment i realized this, the more i hated and resented her..." Yikes! No wonder that relationship didn't end well.

Say you made a smart move in solving an important question that your advisor did not think of and all of a suddenly your advisor becomes jealous because you have made your advisor look bad. What are the best way to manage situation like this?

Generally speaking, whenever somebody tells me that their advisor is jealous of their work, I get rather suspicious. Usually, students that make smart moves and solve important problems do not in any way reflect badly on advisors! Quite the contrary, hence there usually is absolutely no reason to be anything than happy for the student's success. That she (I am taking from other comments that your advisor is female?) did not think of the solution herself matters little - in practice, most concrete solutions to research problems come from students and not the advisors. Again, this would not reflect badly on the advisor in any way.

I am speaking from my personal experiences. Initially my advisor was very friendly[more like a co worker than a boss], but the moment she realized what i had accomplished and how the industry was blown away by my work and offered me internships,she kind of started acting more I say formal[like a manager]. We filed for patents and wrote to CHI (holy grail of HCI Conferences) which was unprecedented for MS students from an small university in the Midwest. The moment I realized this, the more I hated and resented her and and I think she realized this and our relationship went downhill from there.

This is a statement of yours from one of the comments. First of all, congratulations on the CHI paper as well as on the patent applications. However, that being said, the entire paragraph reads like you maybe got carried away a bit by your own success (how the industry was blown away by my work, holy grail of HCI, unprecedented, etc.). Reflect for yourself - is there a chance that your advisor is not so much jealous, but simply annoyed by your high-handed behavior as of late? Are you rubbing your success into her face? Have you maybe even made sure that she understands that this was your success, and not in any way hers as advisor?
Also, the last statement (the more I hated and resented her and and I think she realized this and our relationship went downhill from there.) kind of worries me. These are pretty strong words. Surely, more than a little bit of distant behavior and perceived jealousy has happened for you to resent and hate your advisor?
EDIT:
As it turns out, I am not capable of reading, as the second quote is not from the OP but from @james234. Anyway, I'll leave the answer here, as it seems to reflect the gist of such advisor/advisee problems quite well (even if it does not necessarily help the OP).

That last comment ("the more i [sic] hated and resented her") didn't come from the O.P., but from a commenter to another answer (james234). That said, I wish I could upvote your answer here twice. Questions like this one don't seem to tell the entire story; this isn't the first time I've seen a "What should I do now that my advisor doesn't like my brilliant idea" question, and I tend to be skeptical when the language of the question portrays the advisor to be petty and narrow-minded, the student to be a brilliant prodigy, and no room for middle ground or misperceptions. Something smells fishy.

@J.R. there are lot of details i had omitted ,which would have made my position more clear. Like paying my lab mate(an PHD) more than me and from my research funds ,even though he was nowhere related to project. Omitting my name from PPTs given to my research sponsor although it was all my work and not doing the same with the other guy. I understand the advisor in future will work more closely with PHD than MS student ,that doesn't mean you count your chips and bet everything on that guy alone. Nobody wants to work their ass out for their advisor and give up on them. Its very painful mentally.

@J.R. in retrospect i truly wish i was much wiser and had handled the situation better .Ours is a very small lab of just 2 people but we do a lot of work between us. I am the da facto programmer in lab , so i do my research as well as all other programming stuff ,including building prototype for PHD guy.I was looked upon my advisor for guidance and thought she will take me under her wings and she did seem to but after my project got recognition , i felt i was left to wind. My advisor got multiple consequent projects

@J.R. I was promised that she will speak with my sponsor for internship. And i thought it would be an honor for your advisor to vouch for you in front of other managers. But she advised me to speak with him myself and i did do that but i was disappointed with my adviser.When we were celebrating success of our project with our corporate sponsors,she never mentioned me but at the end the manager i worked with introduced me to group as the person who developed the interface and the product.I mean isn't it the job of adviser to do that ,to promote your own student?Small things but show what i mean

@james - Just to be clear, I wasn't necessarily asking for all the details here in the comments, where we only have 600 characters to explain a situation. I was more talking about a trend I've seen here, where students will sometimes report feeling slighted, wronged, or marginalized, yet their words strike me as somewhat pretentious, defensive, or haughty. When I see that, I really wonder if the whole story is being told – and suspect that it probably isn't.

@J.R. well , there are two sides to every story .I have finished my thesis in HCI and wrapping things up. In Summer ,i asked my advisor if i can work on  PHD in HCI ,but she replied that i was good in CS , so i should pursue an PHD in CS and not in HCI .This is telling in PC way to get out of lab. A good adviser would have pointed out your deficiencies and asked you to work on it instead of blanket rejection. I will definitely ask her on my last day in lab as to where she honestly think i went wrong and what i should have done. But advisors are people too ,so they are not all virtuous.

If your supervisor is already a professor, this is highly unlikely as the difference in the competence is way too big. If such thing really happened by pure chance, just ignore and concentrate on work instead. He is a professor. He is competent. He should manage.
Such friction may only happen when, for instance, the professor assigns near finishing PhD student, young post doc or the like, to help the starting PhD student.
Such "low level supervisor" may provide a lot of useful assistance, so you need to think twice before attempting to run away from it. But if you really do not want him, and are also sure you can get without him, go to the professor and ask to remove that supervision. This usually works no problem.

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Are ethnic "minorities" given preference in PhD admissions in the US?
I have a question about college education, or more specifically, admittance into college education in the US.
Since as far as I remember, I've always heard that colleges or universities in the US have a sort of special preference for admitting people that are considered "minorities". I would like to know if this is true, and if so, what it entails.
For example, I myself was born elsewhere but moved to the US at an early age, and eventually became a citizen. I don't know where this places me as far as "minority" programs go, if they exist. I imagine there'd be a sort of hierarchy such as scholarships > minority with scholarship > minority, but I really have no clue.
This interests me because I am studying in a university outside the US, and I'm considering applying for a PhD program in the US. I'm aware that schools function differently, but if someone knows of this topic for a specific school it'd help.

You are the perfect applicant: minorities get a small advantage in admissions, and U.S. citizens get a small advantage in admissions.  The only flaw is that you're currently studying outside the U.S., and we tend to look on this unfavorably unless you're at a particularly famous university now.

@vadim123 Great! So where can I find out what universities have enough prestige to cancel out the negative factor of not being from the US?

Minorities are defined in the US by race, not by citizenship or national origin, except for "Hispanic", which in principle means loosely "has family roots in Latin America" (not Spain) but in practice means "self-identifies as Hispanic".  Confused?  Welcome to America.

@JeffE Spaniards are considered Hispanic, they aren't, however, considered Latino.

There is a slight preference in the US for what are known as "underrepresented minorities"—that is, people who belong to groups who are not adequately represented in college enrollment relative to their proportion in the general population. That currently includes groups such as Hispanics, African-Americans, and Native Americans, but not groups such as Asian-Americans. So long as someone is a citizen, it does not really matter if one was naturalized or was a "born" citizen.
This does not mean that quotas are used, but it can be used as a "plus" quality in terms of admissions and hiring decisions.

So the last sentence in the first paragraph implies that I'm no longer an underrepresented minority? (Beforehand I was "hispanic") Also when you say "preference" does this mean officialy (as in, specific programs) or extraofficially (as in, a slight "leaning towards")?

@GPerez: I think you've misunderstood that sentence.  Becoming a citizen doesn't change your race or ethnicity.  Becoming a citizen does affect a lot of issues surrounding college enrollment, but unless you want to become president there's no difference between being naturalized or born a citizen.

@NoahSnyder I got a blood transfusion and replaced all of my gametes (jest). Jokes aside though, what I meant is that I was living in the US with a hispanic passport and a green card, whereas after becoming a citizen the green card was revoked and I subsequently was living there with US passport.

@GPerez: Such policies are official, but typically not formulaic (in part because of Supreme Court decisions).

I think you're misunderstanding how the word "Hispanic" is used in the US.  "Hispanic" refers to "a person of Mexican, Puerto Rican, Cuban, South or Central American, or other Spanish culture or origin."  My sister-in-law is Hispanic, but her family has lived in the US for 150 years.

@NoahSnyder Viewpoints aside, now I'm a bit confused. First you said that becoming a citizen doesn't change your race, implying that race is something inherited biologically, but next you give a cultural definition? If the definition is cultural I certainly wouldn't be considered hispanic, seeing as the life I've known has been entirely in the US, and the culture I'm most familiar with is that of the US. So which is it? By "it" I mean an official definition used by schools, casting aside, as I've said, viewpoints (because a certain philosophy may question the well-definedness of "race").

@gperez Hispanic is not a race; it is a ethnicity. There can be black/white/indigenous/mestizo hispanic people. You can self-identify as "hispanic" in your forms, or not. It is up to you (assuming you have hispanic ancestry, which you just said you do).

@Gperez There is no official definition.  Aside from a few special cases like Native American tribes, who have official member lists, there is no formal definition.  Race is a bit biological and a bit cultural and a bit something else.  Mostly you're Hipsanic if you say you're Hispanic, and African American if you say you're African American, though if you don't have an appearance or a name that fits, you might find people have trouble accepting it.  For purposes of admissions, it's mostly on the honor system.

@GPerez: The last sentence in the first paragraph means if you were Hispanic before becoming naturalized, you remain so afterwards. The same would apply to Native Americans and African Americans.

Are asian-american disadvantage because of race? I know this is true in undergraduate, but was shocked to hear it's the same at graduate school. Looks like discrimination against asians is much more rampant in the usa than I thought.

@A_Happy_Student You are misreading my comments. Asian-Americans are not underrepresented in graduate schools relative to the overall population. Most schools outside the upper echelons are too worried about finding enough qualified students to discriminate for any reason.

I wasn't misreading your comments. I was asking for confirmation to something I've been told. Of course asians are not underrepresented, which is why those top universities discriminate against us. I had thought, though, that it was just the admissions committee that was racist, and not the professors that deal with grad admissions. Looks like I was wrong.

Graduate admissions are an entirely different process from  undergraduate. Being accepted is a function of not only your academic record but also the specific research needs of the department. You can be “leapfrogged” by someone with more relevant experience but a weaker transcript. And also don’t forget the international pool. So I wouldn’t rush to the idea that you’re being discriminated against just because you’re Asian-American or anything else.

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Deciding to not apply to a college that I have met with a faculty member, advice on what to do
I met with a faculty member for a history MA program but have decided not to apply there. Simply put, there are better programs that I would be a better fit for and also it requires an expensive verification of my transcript which other universities don't require. However, I met with the graduate director and they were very helpful earlier this year. Do I need to do anything/is this a valid reason for not applying?

Interviews are a two way street. While the graduate director was very helpful, that help indicated to you that the program was not for you. That is still quite helpful, but you do not have to apply.

"Thank you for meeting," blah blah blah, "Unfortunately I have decided not to apply to XYZ University because I don't think it will be a good fit for me. Thank you again for your time! Sincerely, ohivegotswag"

Maybe explain this to them, so that they can improve their process and if they don't want to than you can apply to those other opportunities. This gives them a chance to change and it gives you an out without feeling bad.

You do not need to apply to a program just because someone is helpful any more than you need to enter into a marriage agreement with anyone who has smiled at you.

You don't? Anyone knows a good divorce lawyer?

It would be polite for you to send them an email thanking them for their help and letting them know that you will not be applying.  There is nothing else you need to do.  You may but do not need to explain your reasons.

I think application fees are a perfectly good reason not to apply to a school. They can get outright predatory. If you have reason to believe that the fee is larger than typical, and is within the school or the program's control, it could even make sense to write to them and politely tell them that you're not applying for this reason. Maybe that will help nudge them towards reducing their fees someday.

license: Creative Commons - Attribution Share-Alike - https://creativecommons.org/licenses/by-sa/4.0/


text:
Why do Americans care so much about recommendation letters?
In Europe, we judge students based on their work and abilities. How are their grades? Do they have relevant work experience (TA/RA, maybe part-time industry work, etc)? What projects have they done? What courses have they taken? And of course the odd recommendation letter is always a nice bonus.
We expect students to write up a summary of all these things (it's called a resumé) upon which they are to be judged, and further detailed inquiry can then be made during a possible interview process.
However, as I understand it, it seems to be quite different in the USA. Reference letters is all that matters. Be a mediocre student, but have a good friendship with Professor Abstract Algebra? You're as good as made. Be a fantastic student, but be a bit shy or having done most of your work independently of the professors? Tough luck.
I am particularly bemused by so many of the questions on this very site where professors come to talk about awkward situations where they are being forced to write a recommendation letter for some student that they don't even know. Who the heck is Robert James? I lecture to hundreds of students, for Christ's sake!
Or when you in turn get students here asking for questions about how to approach a professor they've spoken very little to all year and ask them to write a recommendation letter.
And yes, I get it. One day, one time, you'll get a fantastic reference letter from a professor who actually knows and has worked with a particular student, and that reference letter will give you a better understanding of the capabilities and experiences of this student. I get that. But that's only part of the whole process here in Europe: That's the bonus I mentioned in my first paragraph, but we don't make it our everything. We realize that some people might get luckier with recommendation letters than others.
So why do Americans put so much weight on  recommendation letters?

Having myself criticized several times here the practice of recommendation letters (in particular, I don't want that my chances of being hired depend on someone else's capacity for writing recommendation letters and I find the practice of requiring the students to waive their right to see the recommendation letter utterly unethical), I like this question, but, yes, you can probably remove the sarcasm for a better result.

I like your optimism that in Europe your CV is all that counts. It's not like nepotism was ever an issue here, right? Right?

But let's also be honest here: the real reason we Europeans hate the US tradition of recommendation letters is that it forces us to write recommendation letters for our students who want to go to the US :-) Every time I receive an email asking for a recommendation letter I start @#£$§!!!

The premise is wrong. Grades and resume certainly matter. Recommendation letters from someone who can speak with some authority about your strengths (and weaknesses) also matter, just as they do when not being hired straight out of school. There is an assumption that people will not write unjustified recommendations, since doing will damage their own reputation; as a result, if an American has nothing significant to say about "Robert James", we probably won't be asked to write a recommendation and in fact would probably decline if asked.  You can and should do likewise. Rant resolved.

Comments are not for extended discussion; this conversation has been moved to chat.

I don't wish to restart any conversation (which should go to the chat room https://chat.stackexchange.com/rooms/81049/discussion-on-question-by-jezusiswatfhing-why-do-americans-care-so-much-about-re ) but I note that the OP, having breezed in here with a rant at the level of "pub chat", has not been seen since asking the original question (which is his or her first and only activity on this site). It's not clear to me that it is worth people expending so much more care and effort on the rebuttals than the OP did on the original question.

@YemonChoi Part of the reason we have this is for future people who have the same question, so even if the OP did/does completely forget about it, it's still useful for others.  Also it's on the Hot Network Questions right now, so it's interesting to people like me :)

Somehow this topic reminds me the Z-list in Harvard. Although the matter is different here.

because every measurement has uncertainty, I guess?

I think Bryan's answer gives a nice perspective on the issue. A perfect system does not exist, and different continents have developed different (imperfect) ways of dealing with the fundamental recruiting problem that it is hard to judge whether a specific student (or employee) will perform or not.
What I want to add is that, if you peek behind the covers, the European and American systems don't actually differ all that much. You assert that in Europe "your CV is all that counts". That is, unfortunately, quite naive. The CV of your average student is simply not expressive enough to be "all that counts" - good grades are at best a weak indicator of research potential, and (despite your counterexample from France), also in many places in Europe many students have very good grades, to the extent of being low-value as a discriminator in hiring. Grades also do little to measure the soft factors such as motivation or being a good team player, which ultimately matter more than whether a student had an A or a B for some largely unrelated undergrad course.
How professors in Europe largely have dealt with this uncertainty is by personally asking the professors that the student worked with before what their impression of the student was - so you still have your "recommendations", but not through written letters but through informal email or telephone exchanges. This was possible because traditionally, students in (at least central) Europe were not particularly mobile - most prospective PhD students did their undergrad in the same university, a close-by university, or a different university where the professors are already in close contact. Applicants from other places were often rejected outright. Now times are (slowly) changing and more and more PhD students come from abroad - and, lo and behold, suddenly formal recommendation letters are becoming important as well.
Another aspect that I am missing in your question that at least central and southern Europe has historically had a problem with rampant nepotism in academia. So I find it particularly curious that you draw Europe as a haven of objective hiring strategies.

Note that what you're describing could be construed as a backchannel reference and are generally somewhere between 'frowned upon' and 'class-action lawsuit worthy' in the US which might explain why the explicit LoR is used instead.

I think the traditional model in many European countries was more like "it's CV and research plan that count". When the PhD applicant already has a Master's degree, they should be able to produce a reasonable research plan. External reviewers were frequently used to fight nepotism. These days recommendation letters are often used as a faster alternative to external reviewers.

Do you have any actual data to support your assertions like these?:

it matters less who you are and what you can actually do, but more how many professors you are able to suck up to. Reference letters is all that matters

Recommendation letters are valued because it is difficult to objectively assess the other criteria you mentioned:

Grades vary greatly by institution, and in many cases have become inflated to the point of meaning very little. Because so many students get "A" grades, a GPA only points out the occasions when someone does not receive an "A" which may be because they are a terrible student, because there was a course they chose not to prioritize, or because they had a professor who disagrees with grade inflation and attempted to give objective grades with reasonable variance at the top. Reading a GPA doesn't tell someone anything about which of these possibilities is true.
Test scores are only very vague predictors of future success.
Research projects are hard to evaluate. You could base it on publications, but for someone with a short career, like an undergraduate being evaluated for graduate school, minor setbacks that are normal in research can have a huge impact on publication productivity. You could base it on how many projects someone says they worked on in their personal statement or on their resume, but how do you know what their actual impact was? Maybe they are taking credit for everything that happened in a lab where they washed the dishes.

Reference letters are also flawed. There is often an expectation that references be incredibly glowing and praise-worthy, so a more honest letter might come across as critical when it is really just meant to be honest. Any admissions committee worth their salt knows about all these flaws, and therefore uses the combination of all the information they have to make decisions. Inconsistencies are just as important, and can let a committee identify possible weaknesses to address in an interview.

+1 for item "B," but I'd go further still: test grades and one's aptitude for research are nearly orthogonal. I've met and worked with several students with mediocre grades who are awesome at research because the skill sets are so different.

While I agree that test scores are not always a perfect indication of aptitude, that doesn't mean that recommendation letters are any better (as they are inherently subjective). You're trading the inaccuracies of objective values for the inaccuracies of subjective values. A recommendation letter, especially when relied upon to the degree that they are, are effectively no more than a verbal curriculum score instead of a test score. If professors wrote feedback next to test scores (similar to elementary school report cards), that would effectively supplant the recommendation letter.

@Flater I think I make it pretty clear in my answer that both are problematic, and I at least somewhat agree with aeismail's stronger stance. Test scores might be an objective measure, but they are an objective measure of how well you did on a test. They are not an objective measure (except at low thresholds) for readiness for research. Also I'd point out since it's not clear in your comment whether you are on the same page, but when we refer to test scores we mean standardized tests like the GRE used for admissions in the USA, not coursework exams.

In addition, GRE scores have been found to be bias. In which different demographics perform better.  So even these are imperfect.  I think the goal of LORs (as are all the items in an application), is let's get a set of imperfect predictors to do our best at evaluating a student.

How are their grades?... What courses have they taken?

Good questions! These are relevant everywhere. Of course, one institution's A is another institution's B-. Ask any professor, in any country, whether undergraduate grades are a reliable indicator of graduate performance. Graduate school admission is not a reward for getting good grades.

Do they have relevant work experience (TA/RA, maybe part-time industry work, etc)? What projects have they done?

Also good questions, but you can't take the applicant's word on them. Okay, this applicant said he wrote an operating system from scratch as an independent study project. But if you haven't heard from the professor who oversaw it, how can you know whether that's as impressive as it sounds, or whether they wrote a buggy real-mode kernel and a buggy CLI and squeaked by with a "pass"? Or that applicant said she spent a summer helping revolutionize the efficiency of desalination plants, paving the way to turn the Sahara green. Awesome, but only her supervisor can tell you whether she was actually involved in the process and effective as a researcher, or whether she just made posters all summer because she wasn't competent enough to do anything else.
Academia, at its very core, is collaborative. You stand on the shoulders of giants, and do your best to help the next generation see a little further. Part of this is helping the right people advance in their field, both because they're promising in their own right, and because they can potentiate the contributions of others. A formal letter saying "Lisa has a real knack for experimental design, and you should ignore her organic chem grades because she was working through some stuff that semester" is a lot like an email saying "You should consider switching to acetone as a solvent, toluene never worked for us." It's one researcher collaborating with another.
As for the difference between the US and elsewhere: I've definitely noticed in some countries that grades are extremely important and evidence of relevant extracurricular work (such as on a CV or in a letter of reference) is much less so. I suspect that's correlated with how historically standardized university examinations have been in the country. I guarantee you, though, that in many/most European countries, references are just as important as they are in the US.

The original question is, indeed, snarky. Take, for example, these claims:

Reference letters is all that matters. Be a mediocre student, but have a good friendship with Professor Abstract Algebra? You're as good as made.

Nope. Sure, you may have a great relationship with Prof A.A. But astute readers of reference letters can read between the lines of the recommendation letters--that's plural for a reason. One good letter and two tepid letters are not going to elevate a mediocre student to admission to a top graduate program.
Furthermore, the assumption that the letter is the only evidence of a student's ability is odd. Most programs will examine, among other things, grades (including the rigor of the courses that were taken), the GRE examination scores, and other evidence of motivation and potential. Few phenomena in the social world are monocausal, least of all graduate admissions.

Be a fantastic student, but be a bit shy or having done most of your work independently of the professors? Tough luck.

Some programs--at least, in the United States--seek to train potential scholars who will work in the lab or in the field, or with data, and in the classroom. Ultra shy students whose teaching potential seems limited may not get a strong letter. But my experience is that letters matter at the margin: two students with near identical records on paper are  hard  to differentiate without the reference letters. So, as a tie-breaker, letters can be very helpful indeed. And we do counsel students who want to go to grad school to work to make a good impression on their faculty, so that their referees can write useful letters for the application dossier.

We expect students to write up a summary of all these things (it's called a resumé) upon which they are to be judged, and further detailed inquiry can then be made during a possible interview process.

I thought the Europeans called what we  call a non-academic resumé a CV. Anyway, we ask for similar materials as part of our application packets.

One day, one time, you'll get a fantastic reference letter from a professor who actually knows and has worked with a particular student, and that reference letter will give you a better understanding of the capabilities and experiences of this student. I get that. But that's only part of the whole process here in Europe the United States.

Same thing here. We can tell the difference between a heartfelt and useful letter and a perfunctory one. And most of us won't even write these letters if the student is utterly unknown to us aside from a face in a lecture hall. I urge the OP to see the pile of paper we read when we serve on graduate admission committees. It's a bit taller than a stack of reference letters.

As suggested by the OP, I've been on several hiring committees for postdocs and selection committees for graduate students at a US university and recommendation letters are always carefully considered (although they might be considered in Europe too). Recommendation letters matter because we are hiring people, not robots. When I am hiring a graduate student or postdoc, the recommendation letters carry a lot of weight for me because I'm going to be working with this person almost every day for a few years.
Grades, previous research experiences and publications tell little about how the person is to work with and can be misleading about what their strengths and weaknesses are. In my experience, there is not much correlation between grades and research productivity. Even if a person is first author on a paper, it's not clear how much of the work they did or how much was done by the advisor.
Recommendation letters tell you what a person's strengths are and (often implicitly) what their weaknesses are. Perhaps Candidate A is first author on a paper in a prestigious journal and Candidate B is first author on a paper in a less prestigious journal. With that information, you might consider the first candidate to be better. However, if the recommendation letter for Candidate B says something like "Candidate B came up with the idea for the paper independently, performed the experiments using method X, and wrote most of the paper themselves. I only offered a bit of counsel on the research plan and the organization the paper," then this would provide strong evidence of Candidate B's research skills.
On the other hand, let's say a person has worked in three labs previously. By itself, it may look like they have a lot of research experience. However, let's say they do not obtain letters of recommendation from any of their former supervisors and instead I get letters of recommendation from professors who barely knew them. Without some kind of explanation, I will assume that they have poor personal relationships with their former supervisors. Maybe this person is ambitious and productive, but is difficult to work with? It would make me think twice about hiring them.
I often see comments like, "Candidate C's spoken English may appear weak, but their written English has improved significantly over the last year and they have become excellent at organizing and writing scientific manuscripts" or "Candidate D is expert at experimental method Y, but needs to work on their scientific writing." This is invaluable information that can't be gleaned from a CV. If I hire them, I already have some idea what I need to work on with them.

Recommendation letters are indeed a double-edged sword, they're meant to cover a void that isn't shown in GPA or a regular CV. For example, a friend of mine who teaches in the chemistry department of my university has a very bright student, she is in a research group and they just won an award to do some research in Standford next year. Now, she wants to be a researcher, and this opportunity is great and all, but she has a GPA of 2.0 because she got pregnant, abandoned and had a lot of financial difficulties. There are many who face big difficulties that tarnish their grades, and legitimate recommendation letters are a way to express those kind of situations.
You have to notice that most of the time recommendation letters are sent directly to the university of the applicant with their template, this way they're usually more honest. Some abilities and aptitudes are better explained by teachers and coworkers, such as teamwork, leadership, confidentiality, soft skills in general.
I live in a very corrupt country, so I understand your concern, but most of the nepotism actually takes place either in person or by other means of communication. Letters of recommendations can be a part of nepotism it or a way to "legitimize" it but they're in any way the core of the problem.

It's spelled Stanford

Ignoring the tone of the question, addressing a couple points:

How are their grades?

This is extremely hard to normalize, and assumes that grades, which test being good in class, translate well to research potential. They don't, and I can think of several examples of students who were middling at best in classes, but excellent researchers. Additionally, letters may help put those grades into context in a way where the letter grade might not.

Do they have relevant work experience (TA/RA, maybe part-time industry
  work, etc)? What projects have they done?

It's interesting that you assume these things are not associated with the same soft skills (getting along with a professor) that you assume drive recommendation letters. I would suggest this is not the case.
There's also some issues with bias in research experience - in the U.S., that's often students who don't have to hold things like summer jobs to pay for tuition who can afford to buff their CV instead. A letter lets a professor talk about someone's intellectual curiosity, keen insight or engagement in class, etc.

Reference letters is all that matters.

This is just patently false. We have GPA requirements. We have GRE requirements. I read people's cover letters critically.

Be a mediocre student, but have a good friendship with Professor
  Abstract Algebra? You're as good as made. Be a fantastic student, but
  be a bit shy or having done most of your work independently of the
  professors? Tough luck.

Only if Professor AA can speak to your abilities as a researcher, and you have the evidence to back it up.
If you've done independent work that's interesting and stands up on its own? Talk about that, and I'll take a look at it. You know how I know? Because I've hired people who have done exactly that.

And yes, I get it. One day, one time, you'll get a fantastic reference
  letter from a professor who actually knows and has worked with a
  particular student, and that reference letter will give you a better
  understanding of the capabilities and experiences of this student. I
  get that. But that's only part of the whole process here in Europe:
  That's the bonus I mentioned in my first paragraph, but we don't make
  it our everything. We realize that some people might get luckier with
  recommendation letters than others.

Context is important. I've had letters that explain circumstances that, looking at a CV, are odd or worrisome. I've had letters talk about someone's potential, how much of their research project is truly theirs, etc. I've had them speak to the shortcomings of a student, so I can evaluate how much that matters to me, or if that's a potential for growth in my lab. It lets them talk about passions that are hard to quantify (outreach, teaching, etc.).
It's part of a holistic process. I also weight grades, and research experience, and career opportunities. I'm keenly aware of the bias issues that sometimes arise in letter writing, and actively look for them to make sure I'm not weighing them heavily.

Many reasons have already been mentioned.
One reason might be that there other (demographic) criteria for the inclusion of students. To put it blantly, letters of recommendation give you some leeway for covert racism.
For example, much of the "well-roundedness" that was expected of candidates (personality beyond their grades) was originally a means to discriminate against Jews in academia, since they didn't attend church activities which were so important back then. Nowadays, it is used to discriminate against Asians.
I have had Asian students explicitly asking me to get their well-roundedness across in their letters. I have met admissions officers telling me that they limit their intake from Chinese students by a quota because otherwise they had too many Chinese.

"otherwise they had too many Americans." Did you mean they would have too many Chinese students?

@Ambicion, can you give more substance to your remark that you've had "admissions officers" (actual faculty in graduate departments?) tell you that they have a quota system? This is not exactly legal in the U.S. these days. But understanding that the role of a beyond-undergrad academic includes more than just a narrow interpretation of "the subject" is important. Sure, it can be used prejudicially, but that doesn't invalidate it immediately... Mentoring? Outreach? Cooperation on committees? Can you clarify?

@scaaahu: thank you for pointing out the mistake, it's been edited.

The second paragraph is either misguided or misstated (probably the latter). LORs can be used to get past racist admissions officers and their quotas; they do not give "leeway" for covert racism. Recommendation letters are usually written by authors that are positively inclined towards the applicant; almost no one would agree to write a LOR for a student only to stab the student in the back in said LOR.

@paulgarrett: I'm sure you're familiar with https://en.wikipedia.org/wiki/Students_for_Fair_Admissions_v._President_and_Fellows_of_Harvard_College . The validity of the criticism will of course greatly depend on whom you ask, but I find it quite convincing. The opposite claim rests on some secret extracurricular sauce, known only to admissions officers, that unexpectedly many Asian applicants lack in comparison to e.g. Americans. I'd find it a bit more convincing if the recipe for that sauce would at least be public...

@darijgrinberg, oh, yes, well, some "special" places feel empowered to operate outside the rules everyone else plays by. "Common law only applies to commoners, not the nobility...". Harvard's history, from finishing school for children of old money, to supposed meritocracy, is stunning... in a bad way. On another hand, for grad admissions in math in the U.S., at my R1 but "not elite" place, in my experience, "the numbers" do not tell a complete story, by any means, as extensive-if-anecdotal observation has shown locally here in MN. But, yes, certainly, some people are biased, and some systems.

I think the reliance on letters of recommendation for admission to graduate programs in the U.S. educational system (which is not at all homogeneous, and is not really organized in any way), is substantially due to the general breadth-but-shallowness of all (to my knowledge) undergrad degree program requirements, plus the wildly varying resources of all the various colleges and universities, plus the wildly varying opportunities (due to both the college/university and students' socio-economic situations).
The typical (maybe not most-elite) U.S. grad programs in math allow people 5 or 6 years, explicitly acknowledging that many students will need to learn a good bit more... since in most cases they simply did not have time/opportunity to do more math coursework as undergrads.
Yes, often, getting an M.S. in math in the U.S. compensates for this, if one can do the M.S. at a reasonable place. Oop, but most M.S. admissions (currently, in the U.S.) do not include funding. So, if money matters to a person (and, to some, it simply doesn't! a colleague of mine chronically expressed bafflement at faculty concerns about salary and benefit... which was eventually explained by discovery that he was an heir to a billionaire), a paid-for M.S. is probably infeasible.
So, one would/should want to be admitted from B.S. to PhD (and maybe, in effect, get an M.S. along the way), because most admissions to PhD programs pay tuition and a nearly-livable stipend.
Simultaneously, applicants from nearly every other country in the world have been operating under a different system, so that their B.S.'s are U.S. Masters', and their Masters' are a fraction of a PhD.
So, perhaps, by some formal rationale, essentially every U.S. student fails in comparison to non-U.S. students.
Perhaps so, in_the_short_term. But the short term is not the criterion of most interest.
Yes, it would be reasonable to speculate that a head start gives a permanent advantage. But, very-interestingly, this seems not to be the case (in my observation). Sure, in some cases, but, by far, not reliably so.
So, how do we compare apples and oranges? I think that rhetorical question is a correct explanation/analogue of the issue of comparing students from different educational systems. (Which is a legitimate version of the original question. If, as in some comments, it's about "asian-americans" versus "anglo-americans", then I have nothing to say!?!)
So, how to gauge the probable successes of people with different starting points, and with most U.S. candidates having so little tangible experience that it is very difficult to assess their talent for mathematics based on coursework grades and GRE. Not to mention my "very-mixed" feelings about typical undergrad U.S. math curricula actually giving an idea what live math is about.
(I have to add that I'm glad I was able to "test out" of essentially all undergrad math... partly, indeed, by being a good test-taker, but also by having read lots of books. No internet then, and TV went off at 10:00 pm...
If I'd been required to sit through two years of calculus (as it is presented in The Tomes), and then any of the pedantic [sic] versions of undergrad math, I don't think I would have seriously imagined that I could be a mathematician. More importantly, I would not have wanted to be a party to such grim, oppressive stuff. A substantial part of my luck was to be a good test-taker... which, let's confess, is not really much related to real mathematics. :)
In other words, in the U.S., undergrad grades, GRE, and that kind of thing are not a sample that I find/have-found most useful for imagining U.S. students' future success. Comparisons to students from abroad are difficult.
(About bias: If the question is really about kids in the U.S. with various ethnic backgrounds, then, no, there's no excuse. So, does "Asian" mean "someone literally from Asia, who's gone to school in Asia", or does it mean "a U.S. kid of Asian ancestry"?)

I think it's partly a historical thing.  From what I remember reading in my history classes, recommendation letters were big during the industrial revolution.  I seem to remember a passage where the historian talked about it literally being a case of job or no job for a laborer moving to a new city.  Think about it: they weren't looking for real skills or talent, since anyone could work a machine.  They probably cared more about your willingness to work stolidly and follow orders reliably, since you were easy to replace but having to do so could slow down production.  They would want to know you were committed and wouldn't cause problems, and the best way to confirm that would be the word of a past employer.  Nowdays, skills and experience are far more important since we do more specialized work, but employers still want to get a reading on your character before they spend the money to make you part of their team, as it's very costly to hire a new person and then have to terminate them and hire again when they can't adapt to the new workplace.

This seems vaguely plausible but seems rather generic, and not taking into account practices in academia which is what the OP is presumably asking about

Speaking from an American industry perspective, as opposed to an academic one, I've been on several teams that hired regularly.  I was given an copy of the resume (CV) several days before the interview, or sometimes an hour to before, but never ever saw a letter of recommendation.  On some teams we'd meet the applicant as a team, on others we'd meet one on one.
We'd ask questions about activities we saw on the resume and attempt to gauge the applicant by how competently they answered the question, plus over all impression of the applicant.
As someone already said, there is no perfect system.  And certainly trying to judge a person's character in a single interview is prone to failure.  We certainly hired more than one who did not work out in the end.
But once again, we never ever saw letters of recommendation.  Again, this might be different from industry to academia, but to me letters of recommendation are totally irrelevant.
James

Yes, this is  different from industry to academia.  Your experience in industry does not apply in Academia in the US. A kind reminder, this is Academia SE, not Workplace SE.

Yes, indeed, in the U.S., currently, apparently academe and industry are wildly different in this regard.


text:
Where should I place the citation in this sentence?
I have the following sentence, where the citation refers to the first part of the sentence. Because of how it appears in the formatting of my paper, and how it reads, I would like to have the citation at the end of the sentence as below. Is this acceptable in APA style formatting?

However, location controls should control for variation common across regions, while my placebo test does not provide evidence that an unseen trend in weight gain is responsible for my results (Mincy & De la Cruz Toledo, 2014).

The citation refers to a study which uses location controls, while the placebo test refers to something I did myself, but that I mention here to provide additional support to the plausibility of my results.
Even if it's not your personal preference, would it be OK by APA to have this reference at the end of the sentence?

It should go after regions, it is confusing to read this way

Perhaps remove however from the start of the sentence and use it like this : ..... regions - Citation - However..... ..

I think the bigger problem is with your sentence structure.

However, location controls should control for variation common across
regions, while my placebo test does not provide evidence that an
unseen trend in weight gain is responsible for my results (Mincy & De
la Cruz Toledo, 2014).

By starting the sentence with "However" a contrast is implied.  I'm assuming the contrast is against a (hopefully simple) point made in the prior sentence.
What really kills comprehension is the "while" in conjunction with the "however".  "While" is "coexisting in time" and since we have two items in contrast, it is not clear if the commentary is referring to the placebo test or the contrasted item.  This uncertainty impacts the citation, making it equally ambiguous.
I'd just start with the subject, the placebo test:

The placebo test does not support that an unseen trend in weight gain is responsible for
the results.

With this simple idea as an independent sentence, it is easier to place the citation with it or not.  The citation will be fully clear if placed in this sentence, as it is only supporting one idea; not a portion of a compound idea containing a contrast where one of those items occur simultaneously with a third item.
Incredibly long sentences and complex grammar are superficially brilliant; true brilliance is making a complex idea simple.

+1 for nice explanation of why sentence structure should be kept simple if possible in technical writing, where almost any ambiguity is BAD. I was also having trouble understanding exactly what was intended, and I was mentally thinking of something to say in a comment until I read your answer. One phrase I wondered about was "my placebo test does not provide evidence". This seems weaker than intended, since the claim about not providing evidence could also be made in cases where the placebo test was incorrectly carried out. In fact, my turning on a TV set also does not provide evidence.

@DaveLRenfro In my example I altered it a little to "does not support" because in my mind, tests either support or invalidate ideas in Science, they don't create evidence,   Of course, this only one viewpoint of a dozen or more useful viewpoints, tied to a strict definition of evidence as observation, that is rarely used.  Other viewpoints are valid too, provided they are useful, concise, and clear in whatever approaches they offer.


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How can researchers effectively stay current as the volume of publications increases?
For most academics, it is professionally vital to stay current in our fields. However, the volume of publication appears to be increasing exponentially [1, 2]. The first of these studies estimates a doubling time of 15 years.
What are good strategies for coping with this increasing volume of literature?

There is absolutely no need to keep up with the majority of review papers. Many of these are low-quality CV padding, especially when published in journals with very low acceptance thresholds.
I would seek out more authoritative reviews in selective journals or by particular influential individuals in your subfield.

@Snijderfrey Different high quality reviews can have different goals and scope. For someone in biomedical research it's likely that their field of interest overlaps in different dimensions with other people's.

If  you are alone in your pursuit, then you can read the abstracts and, based on that, prioritize the papers into, say, three bins according to their importance to you. Work on Bin-1 primarily and let the others slide until you have time.
If you are part of a group, or can form one, you can distribute/assign the papers to members and have regular meetings featuring short reports on what each member has learned from their papers. You can use these reports, also, to distribute to bins for reading yourself. Each member will be responsible for only a few of the papers.
You can also "bin" the papers prior to distribution if you have time to read the abstracts, or even the titles, which give some idea of relevance.
In a group, people might even "bid" on papers they want to read and report on. One conference review scheme (in CS, Software Patterns) lets reviewers bid on papers, but the review process is completely different there. (https://hillside.net/patterns/about-patterns)
And note that the "broader" your field, the harder the problem, and conversely, for narrow fields.

Fifteen years ago, I did try to read at least the abstract of every new paper relevant to my work, but you're right -- it's no longer really possible. Now I rely on Google Scholar alerts, colleagues who bring to my attention new papers that they found particularly important, students working with me, who read the literature on their narrower topics more closely, and my knowledge of the key players in the field and where they publish if they have important new results.

I'm coming from the viewpoint of a mathematician, but it seems to me like you need to specialize further.  Instead of studying classic Hodgkin lymphoma, you study how metastases of Hodgkin lymphoma with mutation X in gene ace1d2 in the liver affect the ability of the liver to metabolize acetominophen while patients are being treated with chemotherapy drug Z.  You restrict your reading primarily to that subsubsubsubsubfield and also look at connections to one or two other equally specialized area.
Then you rely on all the other people studying the same thing to point you to fruitful connections to other areas - after they've tried them and found them fruitful.
Yes this means you can miss out on some potential insights coming from connecting different areas, but you actually have time to really understand the specific area you're studying.

It helps to think of all published literature as an encyclopaedia rather than a novel. You don't read an encyclopaedia, you keep it handy to look up things you need. It's not just the rate of publication that's increasing, the tools for searching that database of publications are also improving. When you do research, you want to find specific answers, look up a particular result, or check if something has been done before. You do not need to actually read or remember things that much. It can still be helpful to open the encyclopedia to a random page and read an article or two just out of curiosity and to broaden your horizons, but that's optional. It is much more important to have access to these publications than to have actually read them. It's the concept of "antilibrary" coined by Nassim Taleb:

Read books are far less valuable than unread ones. The library should
contain as much of what you do not know as your financial means,
mortgage rates, and the currently tight real-estate market allows you
to put there. You will accumulate more knowledge and more books as you
grow older, and the growing number of unread books on the shelves will
look at you menacingly. Indeed, the more you know, the larger the rows
of unread books. Let us call this collection of unread books an
antilibrary.


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How to deal with student putting their (home)work on github
While using github for source code is generally something I love to encourage, if a student puts their (computer science) homework there, it's generally easy for others to find and copy - which creates a temptation to use it as a "baseline" for their own (identical in most cases) homework - while I understand the benefits of using github (versioning, transitioning across machines easily, teamwork-capabilities), and the individual student who is using it has verified that it is indeed their account and can explain the code well, I still feel uncomfortable with it.
Has anyone else dealt with this issue? how did you handle it? does the university have some sort of policy around publishing student-created work openly? (even if it is part of an assignment)?
As a side-note, my general policy regarding "very similar" assignments is that whomever submitted it first gets the points, and the other submissions do not receive any points, however I tend to ask the students to explain their code and how it works, why they chose X over Y, etc. in such cases first.
edit: I have been informed that there does exist a free version of github that students can use to host private repositories, and this is likely the course of action I will go with for the near future, however, there are several drawbacks:

The student will be unable to showcase their work (i.e. a link to their github on their resume)
The student will not be a student forever, and thus the repository won't be able to be private for free indefinitely
I have very little control (and interest in policing it) once the class is over, so the student could decide to make the repository public once the class is over.

Bitbucket is free.

Can't they post it on github on a private repository not accessible to other students?

GitHub private repositories are free for students: https://github.com/edu . As a teacher, you might also be able to get stuff. They call it "Request a discount", but for students the deal is "Micro account (normally $7/month) with five private repositories while you're a student"

@yakatz - I think that would be the solution, I will look into it - thanks!

Do note that Github takes forever to process a education account.

What about a local git repository? If you want cloud backup, you could use it together with dropbox etc.

To be frank, points 2 and 3 you have absolutely no control over anyway. The easiest thing to do would be to subtly change the assignment so that "last year's solution" doesn't work.

"does the university have some sort of policy around publishing student-created work openly?" That's for you to tell us: does your university have such a policy?

@fkraiem no, it currently does not and allows the professors to deal with as they see fit, thus my personal policy on similar assignments. I am asking what policies other institutions have.

I don't see it a big difference with discussing the assignment with their peers at lunch, except that the code is more readily available.

I see an enormous difference from discussing the assignment with their peers at lunch, because the code is more readily available.

"do nothing" seems like a reasonable option here.

Give students assignments where their work must address one of their personal interests.  For example, instead of having every student program pizza maker, have each student program a machine to make their favorite food.  This will make copy-and-paste cheating more difficult.  It will also make students more interested and make your grading more interesting.

Makes it a lot harder on the autograder

@user2813274 Providing individualized feedback will help student learn more, so it is worth it.

@user2813274: What exactly is that? I'm not a computer scientist, but I code for fun. Does it somehow access the complexity of the code?

@user1997744 an autograder is a site where students can upload their code, have it executed, and give feedback if it passes/fails - basically the same as a unit test case, however I can keep the test cases hidden from the students such that they don't code against specific scenarios and miss the general solution.

@user2813274: I assume after that you examine the code yourself? Because two students may get the general solution, but one piece of code may not be as well-written, efficient, etc.

@user1997744 the auto-grader is an optional tool for the students to use before turning in an assignment (although it correlates quite well as to how they do typically..)

@user2813274 A way is to put any personal info (such as personal interests) in a comment block and then use some software such as MOSS by Stanford (and also submit any other versions of the assignment you find online).

There are many things to balance here, and the "best" solution is somewhat subjective.
However, in my opinion, the educational benefit of allowing students to learn version control early far outweigh the increased risk of exposing their code to others who would cheat. If your students are planning to go on to work as programmers in industry, being skilled with version control is almost as valuable as being skilled with coding. Programming is not a solitary task these days, after all.
Another thing to consider: at my undergraduate university, there was no department-wide policy on public version control (and I don't remember any professors having such a policy). However, I remember hearing it suggested that posting code on a public GitHub violated the general policy against plagiarism. This sort of ambiguity is bad for everyone. Whatever you decide is the right way to go, I would recommend stating your expectations explicitly with respect to public version control.

I think your point 1 is fundamentally at odds with preventing homework sharing/copying.  If someone can showcase their work, they can showcase it to their fellow students.  Your points 2 and 3 suggest you want to re-use the same assignment over and over when teaching the class again, which makes this conflict even more inevitable.  There's no way to allow students to share their work publically with anyone who might want to employ them, while also keeping it secret from their fellow students.
There's nothing you can do to keep everything a student does in your class hidden forever.  I think the best solution is to require students to keep their work private during the class (using a Github edu account, Bitbucket, local git repo, whatever), then let them do whatever they want later.  That means you will have to make new assignments every time you teach the class, but I think that is good practice anyway.

My focus on programming assignments has moved to having students copy all they want from all the GitHub repositories in the world, but to reference them in a report about the process by which they solved the problem, written in complete sentences. This is seen as cruel and unusual punishment by first-year students, but when former students meet me in town after graduation that is what they thank me for, that I taught them to write reports. And that their reports make a great reference for themselves.
We can't police this behavior, so we have to try and educate people. We teach them to value other people's work by citing it or giving credit, and we insist that they reflect on what they did. So it is fine to say: I got this code from Nancy, and then I asked Steve how to put widgets on this, and as a result I finally got this to work. That makes it easier for me to judge what the contribution of the student is.
It is more work for me, so I have gone to having the students do pair programming, assigning them random partners each week. That's a good exercise for them as well, and they get to know each other better.

The optimal solution is to accompany the automatic code grading with a human face-to-face code-review, where the students must explain their code to you, and you can also ask them to make minor changes onlile to verify that they know what they did. If you do this, you do not have to worry about copying since the code-review will tell you how well they know the material.
The problem is that this solution requires a lot of work - at least 15 minutes per student per week. I do not have enough budget for this, so I use a sub-optimal solution: I make the weekly assignments only 10%-20% of the final grade, so that the incentive to copy is minimal. Meanwhile, I make sure that the final exam contains questions that are very similar to the assignments. Thus, students who have made the homework by themselves will have a higher grade in the final exam than copiers.

Ignore it.
It is homework and not an exam. The students who just use it without understanding it risk to fail the exam and that's their problem not yours. They are all grownups and need to decide themself if they want to learn something or just to copy something.
As homework usually does not influence the final grade but only the admission to the exam, it is not worth to try to prevent it.
And github is one thing, but students have internal fileservers and wikis and other ways to organize how to exchange current homework or even a complete set of assignments from last year.
Make sure that everything that gets an actually relevant grade is not done without supervision and be a bit more relaxed about homework that should just help the students to learn and is not used to document their skill like a graded exam.
If you actually see that the code is copied between two students, you may not accept it. But this should be done by comparing their solutions not by monitoring github. They may copy in private or they may have worked together and you need to decide it based on the submission of their work.
When they are actually able to re-use code from the previous year, you may consider changing the assigments in a way that the code cannot be used without at least understanding it.

I hear chem students in the library talking about cheating their final exams like they cheated the second exam. These people are going to fail Chem 2 hard; they won't make it through Orgo. At a point, you know so little about the topic you can't even figure out how to cheat.

You may try automated plagiarism detection, such as MOSS developed by Stanford. It detects similarities among code files, somewhat regardless of how the variables are named, the order of execution, etc. Then a human could manually look at the similarities and judge whether it is a case of plagiarism. Moreover, as I recall, MOSS allows input of shared codebase, meaning that the "starter code" provided to all students would not count towards similarity.

It "tries" to detect plagiarism. There are a few other programs out there, but none actually detect all plagiarism.


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Is Scimago a good way to rank conference impact?
I have seen that the Scimago Journal Rank make a rank of journals that cover different topics and classified them into quartiles. For what I know conferences also made their proceedings books, but I was dubious if they could be compared agains journals like Scimago does.
I say this because I believe that journals have most ot the time a higher impact than conferences, and compare them side to side (journals and conference proceedings) it is not such a good idea.
The question that I have is if Scimago could be a good way to rank a conference impact, and also if there is another computer science conference ranking that uses the same quartile calculus as Scimago?
Any help?
Thanks

@shane the field is Computer Science

This may help: http://scholar.google.com/citations?view_op=top_venues&hl=en&vq=eng_artificialintelligence

Is Scimago a good way to rank conference impact?

No. It isn't.
At best, Scimago is a good way to obtain a modified "PageRank" of a publication in the graph of citations between Scopus-indexed publications in a three-year window, with each citation weighted by the similarity of the citing and cited publications, as measured by their common citation profiles.
Even if you accept that Scimago's abstruse formula is an accurate indicator of "impact"—which is debatable for numerous reasons—neither the raw citation data nor the precise definition of "cocitation profile" (on which the formula depends) are available to independently verify Scimago's rankings.
In particular, a few spot checks suggests that Scimago's coverage of major computer science conferences is spotty, and that the data it extracts from those conferences (even for relatively straightforward things like "number of citeable documents") is not particularly accurate.

This depends a lot on particular area. In some areas, proceedings of the best conferences are comparable with decent journals, while in others conferences are more social events. Computer Science in general is more a conference-oriented area, so proceedings usually have decent impact.
To check it in particular subarea, if you have access to Scopus (other services probably have similar features), try the Analyze Journals tool, to compare some conferences and journals in your field. In my case (Computer Vision), the top conferences are beaten only by the top journals.
For more info on different habits in different subareas I recommend:
Wainer, Eckmann, Goldenstein, Rocha: How Productivity and Impact Differ Across Computer Science Subareas. Communications of the ACM, 2013.
edit: I just re-read your question and noticed your actual answer was about something else. There I can point you again to Scopus (which has both journals and top conferences) and their SJR/SNIP...


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Can publicly available datasets which are hosted in Github be used in research papers?
I am in a dilemma. I have used an old publicly available dataset for some of my analysis and want to publish it. But the problem is that it was publicly available and hosted in a website (infochimps.com) some 4 years ago. But now it's not available there and I got the data from a Github repository. It's not possible to reach the owner of the dataset as the email id given in the readme file is no longer valid. But recently there have been some analyses on the web which have used this data directly from the github repo.
So my question is can I use this data for my paper? And if yes, how to cite it?

Not sure about the legal aspects, but Re "how to cite" - see https://guides.github.com/activities/citable-code/. Not having done this myself, I'm not sure whether you can take a snapshot of somebody's else's repo this way - you may have to fork it first, and then make it very clear in the readme that it is not your work.

I can think of at least a couple issues.

Is the data actually available for use? Just because it is on Github does not necessarily mean that you can legally use it. You still need to determine how the data is licensed (easy if a license is published with the data, possibly difficult otherwise). I'm not exactly sure how data on Github is treated, but code published on Github is "All Rights Reserved" by default and I assume data is similar.
How do you know you can trust the data? One reason you cite the owner or original creator of data is to assert that it is reliable. If the data you're using is not from the source, you'll also want to cite where you obtained it and hope that it's a trustworthy source.

You may not need a license to use something to write a paper about it.

@AnonymousPhysicist Standard not-a-lawyer disclaimer, but I believe that if the data is not in the public domain, you can't simply use it at-will. You have to either abide by the terms of the license if it is licensed, or obtain permission from the owner. Without more details on the dataset it's unclear what the situation is.

Copyright restricts copying, but not ALL other uses.  In the United States, there is an exemption for critique or parody.  https://en.wikipedia.org/wiki/Fair_use

@AnonymousPhysicist Does fair use generally cover data used for research? Am I (legally) allowed to use any data I can get my hands on for research purposes, assuming that I am only publishing the results of analysis and not reproducing any data?