4 ms·

As a physics postdoc who is thinking of switching careers, I definitely sympathise with this article. And I agree with almost everything about it, except this l

by nagrom 13y ago

As a physics postdoc who is thinking of switching careers, I definitely sympathise with this article. And I agree with almost everything about it, except this line: Success as a faculty member requires one thing above all else: a good reputation in your field. And all I really disagree with is the wording - a good reputation does not mean a reputation for excellence. A good reputation means agreeable, means suitably deferential, means knows the correct people and will do as they're told. None of this correlates with excellence...and people who are excellent at research probably don't really want to become faculty, aside from the status and security - it takes away the ability to do research, for a large part. So I agree with the conclusion that the overall standard of faculty is not impressive to students, but it's not because the faculty are not risk takers or innovative - it's because for the most part, the faculty are political animals, not technical ones. They may also be very good technically, but this is an accident and not a feature of the system and untrue more often as not. The cynical students mentioned in the article will likely sniff that out quite quickly whereas, in my experience, the good students are simply more naive. Both types tend to be just as intelligent and hard working, but the cynical students will work on what they want, rather than what the professor wants.

dnautics 13y ago
As a practicing (bio)chemist, I am usually somewhat cynical about philosophy professors, but what this guy says is spot on. Perhaps this is a self-serving agreement, since I was definitely one of these "good bad students". In my experience, yes, including your minor clarification on the word 'good', the full description applies equally to chemistry as philosophy (presumably). But then that makes one wonder: Why are we entrusting this system with taxpayer resources to produce science? Secondly, "But the university doesn't need to exert any pressure, because it's already filtered out the people who would need to be pressured..." What does this mean for controversial topics, like climate science, where political decisions are made based on 'consensus'? "But the climate science community doesn't need to exert any pressure to conform to the accepted model, because it's already filtered out the people who would need to be pressured to accept it"? Equally valid, to replace "climate science" with "cancer research", eg.
- yummyfajitas 13y ago
  It's not even necessary for the topics to be politically controversial (by which I mean Democrats and Republicans have opinions on it) for this effect to occur. You can get the same filtering effect purely via internal pressures. As examples, consider the Copenhagen consensus in foundations of quantum mechanics or the (currently being overturned, thanks to machine learning) Frequentist consensus in statistics.
  - eli_gottlieb 13y ago
    About the statistics thing: I thought that Frequentism and Bayesianism were two separate frameworks to use in two separate contexts? Basically, I thought that you used Frequentism when you could do a definite experiment that yields an exhaustive probability distribution (like rolling a die to see how often it yields each number), while you use Bayesianism to evaluate accumulations of evidence about a distribution you can't experiment on directly. Is that wrong?
    - yummyfajitas 13y ago
      That's not correct. Frequentists view the world as an experiment measuring a set of unknown parameters describing a probability distribution. These parameters are fixed, and cannot be described probabilistically. In contrast, Bayesians use probability to represent uncertainty. I.e., to a Frequentist, it doesn't even make sense to ask the question "what is the probability that the coin is rigged", whereas the Bayesian would come up with a probability distribution for the probability of the coin coming up heads.
      - dnautics 13y ago
        Largely, though it's a matter of terminology[0]. I doubt that any but the most dogmatic frequentist would say there isn't something to the notion behind the question you're asking "what do you think is the chance the coin is rigged", but rather that it should not be conflated (by using the term "probability") with the notion of a situation where something can be repeated and measured - or at least one that sufficiently approximates that situation. [0] I find that battles over terminology can be the harshest and most recriminating minefields among the intelligent.

by nagrom 13y ago

dnautics 13y ago

As a practicing (bio)chemist, I am usually somewhat cynical about philosophy professors, but what this guy says is spot on. Perhaps this is a self-serving agreement, since I was definitely one of these "good bad students". In my experience, yes, including your minor clarification on the word 'good', the full description applies equally to chemistry as philosophy (presumably). But then that makes one wonder: Why are we entrusting this system with taxpayer resources to produce science? Secondly, "But the university doesn't need to exert any pressure, because it's already filtered out the people who would need to be pressured..." What does this mean for controversial topics, like climate science, where political decisions are made based on 'consensus'? "But the climate science community doesn't need to exert any pressure to conform to the accepted model, because it's already filtered out the people who would need to be pressured to accept it"? Equally valid, to replace "climate science" with "cancer research", eg.

yummyfajitas 13y ago
It's not even necessary for the topics to be politically controversial (by which I mean Democrats and Republicans have opinions on it) for this effect to occur. You can get the same filtering effect purely via internal pressures. As examples, consider the Copenhagen consensus in foundations of quantum mechanics or the (currently being overturned, thanks to machine learning) Frequentist consensus in statistics.
- eli_gottlieb 13y ago
  About the statistics thing: I thought that Frequentism and Bayesianism were two separate frameworks to use in two separate contexts? Basically, I thought that you used Frequentism when you could do a definite experiment that yields an exhaustive probability distribution (like rolling a die to see how often it yields each number), while you use Bayesianism to evaluate accumulations of evidence about a distribution you can't experiment on directly. Is that wrong?
  - yummyfajitas 13y ago
    That's not correct. Frequentists view the world as an experiment measuring a set of unknown parameters describing a probability distribution. These parameters are fixed, and cannot be described probabilistically. In contrast, Bayesians use probability to represent uncertainty. I.e., to a Frequentist, it doesn't even make sense to ask the question "what is the probability that the coin is rigged", whereas the Bayesian would come up with a probability distribution for the probability of the coin coming up heads.
    - dnautics 13y ago
      Largely, though it's a matter of terminology[0]. I doubt that any but the most dogmatic frequentist would say there isn't something to the notion behind the question you're asking "what do you think is the chance the coin is rigged", but rather that it should not be conflated (by using the term "probability") with the notion of a situation where something can be repeated and measured - or at least one that sufficiently approximates that situation. [0] I find that battles over terminology can be the harshest and most recriminating minefields among the intelligent.