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> even if they are incorrect Uh. Do you have a source for this? Correctness is a major need in academia.

by jraph 1y ago

tsimionescu 1y ago
I think they mean things like a tool that has feature X even if it crashes 50% when it is used is preferable to a tool that doesn't have feature X at all.
- jraph 1y ago
  Ok, makes sense, I hadn't read it like this. For me, "correct" means "provides correct results".
rglullis 1y ago
Correct != Bug-free. My experience working with software developed by academics is that it is focused on getting the job done for a very small user base of people who are okay with getting their hands dirty. This means lots of workarounds, one-off scripts, zero regards for maintainability or future-proofing...
- jraph 1y ago
  This I fully agree with.
- DougBTX 1y ago
  “Incomplete” seems like a better word than “incorrect” for this. The code is likely correct in the narrow scope it was needed for, but is missing features (and error checking!) beyond the happy path, making it easy to use incorrectly.
lmm 1y ago
> Correctness is a major need in academia. How so? Consider the famous result that most published research findings are false.
- jraph 1y ago
  How so? Finding correct stuff is the whole point of research, no matter the extent at which it actually succeeds in reaching this. So yes, regardless on the actual results it is a major need in academia. We have nothing better anyway (which doesn't need it can't improve; we critically need it to improve). Now. I'll assume you are referring to "Why Most Published Research Findings Are False". This paper is 20 years old, only addresses medical research despite its title, and seems to have mixed reception [1] > Biostatisticians Jager and Leek criticized the model as being based on justifiable but arbitrary assumptions rather than empirical data, and did an investigation of their own which calculated that the false positive rate in biomedical studies was estimated to be around 14%, not over 50% as Ioannidis asserted.[12] Their paper was published in a 2014 special edition of the journal Biostatistics along with extended, supporting critiques from other statisticians 14% is a huge concern and I think nobody will disagree with this. But we are far from most, if this is true. [1] https://en.wikipedia.org/wiki/Why_Most_Published_Research_Findings_Are_False#Reception https://en.wikipedia.org/wiki/Why_Most_Published_Research_Fi...

> even if they are incorrect Uh. Do you have a source for this? Correctness is a major need in academia.

by jraph 1y ago

> even if they are incorrect Uh. Do you have a source for this? Correctness is a major need in academia.

I think they mean things like a tool that has feature X even if it crashes 50% when it is used is preferable to a tool that doesn't have feature X at all.

jraph 1y ago
Ok, makes sense, I hadn't read it like this. For me, "correct" means "provides correct results".

rglullis 1y ago

Correct != Bug-free. My experience working with software developed by academics is that it is focused on getting the job done for a very small user base of people who are okay with getting their hands dirty. This means lots of workarounds, one-off scripts, zero regards for maintainability or future-proofing...

jraph 1y ago
This I fully agree with.
DougBTX 1y ago
“Incomplete” seems like a better word than “incorrect” for this. The code is likely correct in the narrow scope it was needed for, but is missing features (and error checking!) beyond the happy path, making it easy to use incorrectly.

lmm 1y ago

> Correctness is a major need in academia. How so? Consider the famous result that most published research findings are false.

jraph 1y ago
How so? Finding correct stuff is the whole point of research, no matter the extent at which it actually succeeds in reaching this. So yes, regardless on the actual results it is a major need in academia. We have nothing better anyway (which doesn't need it can't improve; we critically need it to improve). Now. I'll assume you are referring to "Why Most Published Research Findings Are False". This paper is 20 years old, only addresses medical research despite its title, and seems to have mixed reception [1] > Biostatisticians Jager and Leek criticized the model as being based on justifiable but arbitrary assumptions rather than empirical data, and did an investigation of their own which calculated that the false positive rate in biomedical studies was estimated to be around 14%, not over 50% as Ioannidis asserted.[12] Their paper was published in a 2014 special edition of the journal Biostatistics along with extended, supporting critiques from other statisticians 14% is a huge concern and I think nobody will disagree with this. But we are far from most, if this is true. [1] https://en.wikipedia.org/wiki/Why_Most_Published_Research_Findings_Are_False#Reception https://en.wikipedia.org/wiki/Why_Most_Published_Research_Fi...