How would he not? Are you really arguing that someone with D.E. Shaw and Princeton on his resume would be in the same position as, in your words, a "typical minimum wage worker"?
Even ignoring the signaling value of D.E. Shaw and Princeton, are you arguing that the wealth he'd accumulated in his career up till that point is comparable to that of the "typical minimum wage worker"?
Then are you arguing that a hedge fund manager and a "typical minimum wage worker" face the same relative risk when they invest the same amount of money? In other words, are you saying that someone who has 110,000 dollars in savings and someone who has 11,000 dollars in savings face the same risk if they both invest 10,000 dollars?
I meant the teams in those companies as opposed to the companies more broadly (e.g., Core Data Science at Facebook, not Facebook in general). I mention those companies together because they're well-known for investing a lot in research (e.g., by hiring PhDs). And in these cases, they're hiring PhDs for reasons that are totally different from the reasons for which they hire engineers (who may also have doctorates). For example, there is indeed a difference between the institution-level goals of Facebook and Microsoft Research, but that difference is less substantial between researchers at Core Data Science at Facebook and researchers on the Computational Social Science team at Microsoft Research.
I'm making the point that there is a difference in the value of a PhD depending on where in the company you work. For the research-oriented teams, the value of a PhD lies in the fact that you've ostensibly been trained to contribute to what we know, rather than just applying it.
Going along with your ML example, the difference would be like comparing Athey, Tibshirani, and Wager's work on generalizing random forests against building a random forest using scikit-learn. I'm not saying that someone without a PhD can't write the paper that they did, but it's for sure not at all just a matter of who's better at writing code.
When some people FB Core Data Science came to campus, they made it pretty clear that they were looking for people with doctoral training for their research work (and not, for example, a Master's graduate who completed PhD-level coursework), so I guess it depends on the task/team.
Sure, but what do they do? Looking at Google Brain for example, "research scientists" are exclusively people with doctorates, while "engineers" only require an MS or BS/BA.
The work is totally different; they're not substitutes.
I think it depends a lot on what it is that you want to do. For example, there are entire teams at companies like Facebook (Core Data Science) and Netflix that hire exclusively people with PhDs. Amazon especially is famous for hiring economists. Microsoft pours huge sums of money into Microsoft Research where the only goal is to fund research with relatively little (short-run) profit motive.
But if you're not on one of these research-oriented teams, then I think it's easy to look at PhDs on your own team and think of them as worthless when in fact they were trained for a pretty different set of things. There's the thing about judging a fish's ability to climb a tree. People seem relatively eager (see other comments) to rip into people with doctoral training for some reason.
You should re-read what you've written. No qualifications for generalizing statements, so it sounds like you're insinuating what I'm saying you're insinuating.
Replying to the thing below: I claimed that your insinuation that no one in China knows about June 4 because of censorship is false. The small-sample survey cited by the Vox and NPR links that you sent support my claim.
That NPR link doesn't contradict anything I said. Tedious sure, but that doesn't mean that you shouldn't qualify the words you use. But good to know that you read what I wrote! How you choose to process it is up to you.
Unless you think VPNs don't exist in China, then of course your use of the word "censored" needs to be qualified.
Did you read these links yourself? One of the your links only mentions that it's not taught in school, others are also based on anecdotal evidence (some of which express that it's sometimes taught in schools and that some people know but don't care). The one statistic that I found in your articles asked about the tank man and not the event itself, and even then their number was 15/100, which is low but not zero.
I don't disagree with what's expressed in these links. I disagree with your characterization of people in China having zero access to this information. If you find my opinions/suspicions/admonitions irrelevant, that's a personal issue. I'm good as long as it's been communicated to you (apparently it has).
1. It depends on what you mean by censored. If by "censored" you mean a simple search, then yes, I agree. But as far as I can tell (and I'm fairly certain albeit with no way of verifying that I have better information about this than you do), VPNs are commonplace enough in China that this isn't a issue.
2. I don't have any numbers, and I doubt you do either.
In any case, your cute platitude of "you can't learn from history if you don't have the opportunity to learn the history in the first place" is incorrect in implying that Chinese people have no way to access this information and general in such a way that it suggests that you are indeed uninformed (or else you would never make such a sweeping statement). While my anecdote is indeed not representative of what happens at large, I believe strongly that I have better information about this than you do, and would bet everything I have that I've discussed this issue with more Chinese people affected by this than you have.
But I supposed this is a pointless argument (since you/I have no way of verifying any of this). I only ask that you think a little next time before irresponsibly spreading misinformation about a group of people that I suspect you've probably never meaningfully interacted with, as this particular post gives the impression that Chinese people are helpless enough in the face of censorship that they don't know their own history.
Again, my whole argument is predicated on the assumption that I have better information than you do based on my experiences, but if you have better information, please show me as I'm pretty curious about this myself.
I'm Chinese-American, and literally every Chinese person (from China) I've talked to knows about June 4, 1989. (So much so that it's colloquially referred to as 六四 or "six four".)
It may take some introspection, but please don't spread things that may not be well-informed.
After some of the initial pain of setting it up (which was educational for me anyway), it's exactly the sort of lightweight thing I was looking for after Google Reader shuttered.
Ah, I know a former engineering professor who left a large flagship university in the Midwest for exactly that reason. Based on what he told me that's more a phenomenon specific to institutions without a lot of money than a general truth about academia.
Well, yeah, there are other irrelevant things about reviewing that I also have the ability to bring up but my point is that to say that the "benefit" of reviewing is for the purpose of networking is misinformed.
Well, yeah, but if you submit a paper to "torture test" and it gets rejected, that cuts off a journal to be able to submit to.
Well, yeah, but I think what he's saying is it's probably the case that a large number if not majority of academic make the decision to go through the grueling PhD process and give up years of earnings in their prime for things other than monetary gain. But of course people can become disillusioned later down the road.
Economics and linguistics also publish their own journals which costs some money but significantly less than Elsevier's subscriptions (I believe linguistics' is 300 USD per year). There's probably enough momentum behind middlemen-run journals that prevents this from happening more en masse.
At least in the social sciences, journal editors delegate papers to reviewers. Your first sentence also suggests that you don't know what peer review is.
Peer review is not the same thing as replication, which is replicating the results of a paper after it's been published (e.g., confirming some groundbreaking finding). Peer review happens at the stage before publication of the original paper. Researcher(s) submit the paper to the journal. The journal editor sends the paper out to some reviewers, who review the paper (this is the "peer review" stage). Pending reviewer feedback and editor approval, the paper is published.
Edit: also the "benefit" that rsa4046 refers to probably doesn't mean networking. AFAIK, reviewers are always anonymous to the authors (which can generate its own problems e.g., if the reviewer gets a paper authored by someone he/she doesn't get along with). The benefit being referred to, I believe, is that of learning to write better reviews, and having reviewed other's work, learning how to improve your own.
I've only worked with professors in economics and political science but I'm under the impression that this is true more generally of academia. Some people do it to help advance the state of the field. Career incentives and standing in the field also come into play. As the poster above mentioned, a professor would be able to say more.
To respond succinctly to your comments: money isn't the only incentive in life, so it seems weird to not see "any incentive" as soon as money is taken out of the picture.
That's obviously not what he's suggesting? He's just saying (and correct me if I'm wrong) that, for a company whose business is based in no small part on trust, it's a bit weird to not have any information about any of the people involved in the project.
Even ignoring the signaling value of D.E. Shaw and Princeton, are you arguing that the wealth he'd accumulated in his career up till that point is comparable to that of the "typical minimum wage worker"?
Then are you arguing that a hedge fund manager and a "typical minimum wage worker" face the same relative risk when they invest the same amount of money? In other words, are you saying that someone who has 110,000 dollars in savings and someone who has 11,000 dollars in savings face the same risk if they both invest 10,000 dollars?