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The real problem is "scientists". What is a scientist and how is he selected/trained ? Scientists are hands-on technicians, theoreticians/statisticians, fundra

The real problem is "scientists". What is a scientist and how is he selected/trained ? Scientists are hands-on technicians, theoreticians/statisticians, fundraisers, and team leaders/project managers. Four distinct skillsets. They are usually selected bassed on their ability to do bookwormish things such as ace tests in their teens and early twenties. The profession goes against the basic principle of capitalism - division of labour. I'm kinda amazed anything gets done by scientists, and this article is validating my intuition.

babar 17y ago
I would split theoretical ability and statistical ability into separate skillsets. Having the understanding in the field and the ability to posit reasonable hypotheses to test is very different (at least in most fields!) from having the statistical knowledge and ability to properly generate results. And I think larger labs do frequently separate out a few of these. I'd love to have a better understanding of how industry labs differ from academic labs in that respect.
fburnaby 17y ago
I'm doing a master's degree in science right now. I've previously worked as a telecomm engineer. I agree that there is relatively little division of labour in science, compared to engineering; or at least the labour isn't divided in the same way. I'm not convinced that this is bad, and in fact it's probably necessary. Most of the useful scientific results synthesize previous results from various fields. There are very few observations incoming that actually add to or question the prevailing theories of a given field. It seems to me from my short experience that most of the work is in reducing theories, and experimentally confirming the reductions. To be useful as a scientist, there's a good change that you'll need to be an expert in at least two things. I don't think it should be surprising that generating novel knowledge requires substantially more overhead than does acquiring and exploiting it (eg. engineering, or any practical pursuit where division of labour works so well). This may not apply to the medical research that was mentioned in the article, (the system is too complex for theoretic reduction to be useful) but I doubt that physical, ecological, mathematical, etc. sciences would progress as quickly without their practitioners having broad knowledge of their subjects.
flogic 17y ago
I think that's a bit unfair. Researchers work in teams and divide labor just like everyone else. The blunt truth of reality is there are more ways to be wrong than there are to be right in both science and business.
cdr-n-car 17y ago
Yes statistics, like logic itself, can be misused and fool the untrained/unthinking.
- joe_the_user 17y ago
  Training isn't useful unless institutions doing the train make awareness of the limits of statistics part of their curriculum.
  - cdr-n-car 17y ago
    The limits of statistics is build right into statistics..."all models are wrong...but some are useful.."

babar 17y ago

I would split theoretical ability and statistical ability into separate skillsets. Having the understanding in the field and the ability to posit reasonable hypotheses to test is very different (at least in most fields!) from having the statistical knowledge and ability to properly generate results. And I think larger labs do frequently separate out a few of these. I'd love to have a better understanding of how industry labs differ from academic labs in that respect.

fburnaby 17y ago

I'm doing a master's degree in science right now. I've previously worked as a telecomm engineer. I agree that there is relatively little division of labour in science, compared to engineering; or at least the labour isn't divided in the same way. I'm not convinced that this is bad, and in fact it's probably necessary. Most of the useful scientific results synthesize previous results from various fields. There are very few observations incoming that actually add to or question the prevailing theories of a given field. It seems to me from my short experience that most of the work is in reducing theories, and experimentally confirming the reductions. To be useful as a scientist, there's a good change that you'll need to be an expert in at least two things. I don't think it should be surprising that generating novel knowledge requires substantially more overhead than does acquiring and exploiting it (eg. engineering, or any practical pursuit where division of labour works so well). This may not apply to the medical research that was mentioned in the article, (the system is too complex for theoretic reduction to be useful) but I doubt that physical, ecological, mathematical, etc. sciences would progress as quickly without their practitioners having broad knowledge of their subjects.

flogic 17y ago

I think that's a bit unfair. Researchers work in teams and divide labor just like everyone else. The blunt truth of reality is there are more ways to be wrong than there are to be right in both science and business.

cdr-n-car 17y ago

Yes statistics, like logic itself, can be misused and fool the untrained/unthinking.

joe_the_user 17y ago
Training isn't useful unless institutions doing the train make awareness of the limits of statistics part of their curriculum.
- cdr-n-car 17y ago
  The limits of statistics is build right into statistics..."all models are wrong...but some are useful.."