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The same is true in computer science. Everyone cites the SHARD paper when discussing database design. But no modern researcher has read it. It does not appear i

by edent 4y ago

The same is true in computer science. Everyone cites the SHARD paper when discussing database design. But no modern researcher has read it. It does not appear in any archive. I spoke to several academics who had mentioned it, none had read the original - they all relied on someone else's referencing of it. See https://shkspr.mobi/blog/2021/06/where-is-the-original-overview-of-shard-paper/ https://shkspr.mobi/blog/2021/06/where-is-the-original-overv... for more details.

_glass 4y ago
I hate this, and in my field (social sciences, organization studies, management sciences) several papers/books are blatantly misrepresented. I still struggle to cite a book (or several!) for a single point. To be honest, often it is really confusing, because science moves so fast nowadays, and these original papers contain so much unintentional historical cruft, or implicit messages to be untangled.
actually_a_dog 4y ago
Very common in mathematics as well. There are lots of results that people use every day that don't seem to have a published proof. They're literally called "folklore" theorems. https://en.wikipedia.org/wiki/Mathematical_folklore https://en.wikipedia.org/wiki/Mathematical_folklore
mturmon 4y ago
Yeah, I think citation without reading is pretty common. You find a lot of citations of Metropolis, Metropolis, Rosenbluth, and Teller’s paper on MCMC but I bet 1 in 10 have read it. Ulf Grenander’s massive book on Pattern Theory is another, or Kolmogorov’s 1933 monograph on probability. Often cited but come on, did you really read it? Another I’m aware of is references to the notion of VC dimension in learning theory. Many papers mention a hard paper by Shelah as an original reference to the concept…I saw the same reference given in a book by mathematician David Pollard with a remark along the lines of, “people say this is the same as VC dimension but I confess this paper is impenetrable to me so I really don’t know.” I appreciated the honesty.
- Joker_vD 4y ago
  > Kolmogorov’s 1933 monograph on probability I actually read that. Its definition of probability is pretty nice: it allows non-impossible events to have zero probability even in discrete case, e.g. a coin landing on its edge.
- mistrial9 4y ago
  maybe 'read' is not descriptive enough here -- difficult materials takes multiple readings for anyone human; definitely different yet again when studied in a group with guidance and feedback.
Al-Khwarizmi 4y ago
It's a quite normal situation. For example, when I started working in NLP, I did some things with the CYK algorithm (https://en.wikipedia.org/wiki/CYK_algorithm https://en.wikipedia.org/wiki/CYK_algorithm), which was defined in three papers by three separate authors. While I learned the algorithm from secondary sources, I of course cited the original papers (because one has to acknowledge the original author of the algorithms one uses). At that point, I wanted to read the original papers, even if just for curiosity, but they were impossible to find (I think one of them was available, but behind an outrageous paywall). Now those papers are easier to find, but anyway I don't think I'd encourage a grad student to read them except for curiosity, the algorithm has been explained much better and in more accessible ways in more modern papers. Which doesn't mean that we shouldn't acknowledge the discoverers.

by edent 4y ago

_glass 4y ago

I hate this, and in my field (social sciences, organization studies, management sciences) several papers/books are blatantly misrepresented. I still struggle to cite a book (or several!) for a single point. To be honest, often it is really confusing, because science moves so fast nowadays, and these original papers contain so much unintentional historical cruft, or implicit messages to be untangled.

actually_a_dog 4y ago

Very common in mathematics as well. There are lots of results that people use every day that don't seem to have a published proof. They're literally called "folklore" theorems. https://en.wikipedia.org/wiki/Mathematical_folklore https://en.wikipedia.org/wiki/Mathematical_folklore

mturmon 4y ago

Yeah, I think citation without reading is pretty common. You find a lot of citations of Metropolis, Metropolis, Rosenbluth, and Teller’s paper on MCMC but I bet 1 in 10 have read it. Ulf Grenander’s massive book on Pattern Theory is another, or Kolmogorov’s 1933 monograph on probability. Often cited but come on, did you really read it? Another I’m aware of is references to the notion of VC dimension in learning theory. Many papers mention a hard paper by Shelah as an original reference to the concept…I saw the same reference given in a book by mathematician David Pollard with a remark along the lines of, “people say this is the same as VC dimension but I confess this paper is impenetrable to me so I really don’t know.” I appreciated the honesty.

Joker_vD 4y ago
> Kolmogorov’s 1933 monograph on probability I actually read that. Its definition of probability is pretty nice: it allows non-impossible events to have zero probability even in discrete case, e.g. a coin landing on its edge.
mistrial9 4y ago
maybe 'read' is not descriptive enough here -- difficult materials takes multiple readings for anyone human; definitely different yet again when studied in a group with guidance and feedback.

Al-Khwarizmi 4y ago

It's a quite normal situation. For example, when I started working in NLP, I did some things with the CYK algorithm (https://en.wikipedia.org/wiki/CYK_algorithm https://en.wikipedia.org/wiki/CYK_algorithm), which was defined in three papers by three separate authors. While I learned the algorithm from secondary sources, I of course cited the original papers (because one has to acknowledge the original author of the algorithms one uses). At that point, I wanted to read the original papers, even if just for curiosity, but they were impossible to find (I think one of them was available, but behind an outrageous paywall). Now those papers are easier to find, but anyway I don't think I'd encourage a grad student to read them except for curiosity, the algorithm has been explained much better and in more accessible ways in more modern papers. Which doesn't mean that we shouldn't acknowledge the discoverers.