Maybe I'm interpreting the GP post wrong, but I take their use of "hard" to mean "unfair and stressful", and your use of "hard" to mean "high quantity and quality of work."
Also, it is unusual for a dissertation to be outright rejected because of how it reflects on the advisor and committee: the committee is (supposed to be) kept up to date on the student's progress and will recommend against defending if the student is unlikely to pass. Slightly less unusual would be a student being allowed to defend, but then needing to do major revisions to their dissertation for it to be accepted. Keep in mind that at the point one is defending, quite a bit of time and money has been invested in the candidate so there is a good incentive to see the candidate succeed for no other reason. Unsuited students are (ideally) dismissed much earlier, i.e., at admission to candidacy.
One absolutely worries about being scooped on papers, since those are the currency of academia and being scooped usually results in needing to publish your own (now less novel) work in a lesser journal. And as another commenter points out: a professor taking on 10 students with only 1 succeeding, if one defines success as being tenured, isn't that far off from reality.
As an aside, I personally think forming a research group at a university isn't all that different from creating a startup.
You're right in that they weed Ph.D. students out earlier, during their comprehensive exam. How it's done varies from department to department and university to university. My comprehensive was a lengthy oral exam by my committee with two rounds of questions. The first on background and the second on the written thesis proposal I submitted. I went for 3.5 hours straight, basically until the committee wanted lunch.
Equating a research group to a startup isn't a bad analogy. One of the professors in my department basically uses his students to do research for his company. He even makes them sign over the IP rights to him. Other professors have a continuing line of research across a number of students. Even my Ph.D. thesis was the latest in a number of theses on the same topic, each getting progressively more advanced. My thesis basically finished that line, with other related ones opening up as a result.
Nor do you have a 90% chance of failing in your business venture despite you trying your hardest.
Going from the statistic "90% of businesses fail" to "you have a 90% chance of failure when starting a business" is an incorrect deduction. The latter only follows from the former if business success is almost entirely random chance. It isn't. Some people are almost guaranteed to fail because they have no idea what they are doing or what they are getting into[1]. Some business ideas are just bad. On the flip side, some people are really good at running businesses, take the time to understand what is required, wait until they have a realistic idea, and through all that give themselves a very good chance of succeeding.
I wish we, as a community, would stop parroting this abuse of statistics.
[1] I'd wager that this explains the vast majority of restaurant failures.
same goes for any high stress, high risk business, like running a restaurant. if you've worked in one for years, you're more likely to succeed in running one yourself.
there is a running joke in the restaurant business about rich semi-retired professionals opening up a restaurant and failing miserably, because they simply don't realize how much work it is. they think because they're great home cooks and can throw an awesome dinner party, they can all of a sudden run a commercial kitchen and dining room. wrong. very, very wrong.
same goes with startups. most people fail because they don't understand how much work it is, and simply give up.
It's called "scooping". You do have to worry about other academic groups doing that, depending on the area you're working in.
And you may even also have to worry about Google or MSR scooping you.
In fact, I know of one person who had his thesis basically scooped by a large corporate research lab. Not so much his exact ideas, but they out-performed his would-have-been thesis work in every meaningful way in a sufficiently small sub-problem that he had to pivot.
> Your advisor doesn't take on 10 graduate students and encourage practices that will cause 9 to fail but 1 to succeed beyond anyone's dreams
I guess that depends on your advisor and program and your field of study. These sorts of attrition rates aren't unheard of in Math, for instance.
> Messing it up doesn't mean you don't have to tell 30 people that they need new jobs.
That is certainly true. But the upside is also significantly bounded.
> Maybe I'm interpreting the GP post wrong, but I take their use of "hard" to mean "unfair and stressful", and your use of "hard" to mean "high quantity and quality of work."
80 hr weeks working on something that the academic community might choose to reject for whatever reason all while making 20k/yr could be described as both...
First, the likelihood of earning a PhD shouldn't be viewed as p(graduate) but as p(graduate | admitted) * p(admitted). Once you factor in the high rejection rate of competitive PhD programs, the success rate drops off pretty sharply. Additionally, the applicant pool tends to self-select toward people who at least believe they are minimally qualified because of the time and expense in completing applications and gathering letters of recommendation.
Second, the random error term is much larger in the hypothetical formula for startup success than it is for PhD success--in fact, it's probably much larger than any variable one can control. A consequence of this is that a unit increase of talent/skill/drive will move the needle further toward success in the PhD world than in the startup world. Comparing successful or unsuccessful individuals across worlds tells you very little.
Third, for all the parroting of the "9 in 10 startups fail" statistic, there seems to be almost no work in connecting its relevance. A startup is not a person. A person may found multiple companies in their lifetime. A person only needs to earn a PhD once to be considered a PhD. I could go on, but I think "apples and oranges" is sufficient.
Sounds like a pretty good description of the academic job market to me.
-A Ph.D. usually often isn't the end point. If your end point is a tenured academic position, your odds are much, much worse than startup success
-About 50% of Ph.D. students don't complete, ever.
-"1 to succeed beyond anyone's dreams" seems odd. Most people who succeed in startups succeed precisely in scope of most peoples dreams. There are outliers, sure, but they are exactly that.
-You aren't scared of Google publishing before you - but in some areas you are justifiably scared of other people publishing before you and making your work unpublishable. You may know these people personally.
-Academic work is often best characterized as being unfair and stressful
-The 90%:10% statistic is just that, and you aren't really applying it meaningfully
-Like companies, Ph.D.s aren't fungible
People have had the problem of being beaten to publication by another researcher and having to re-start their PhD.
The big thing that both PhDs and startups have in common is that you have to do a lot of lonely work for years before you know whether you've succeeded.
Doing PhD research is basically a horrible job choice (imo).
