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Computer Science's conventions solve these problems (although CS certainly has other problems): * papers are generally posted to arxiv.org immediately on being finished, so everyone can access them * conferences have fixed deadlines and relatively short, fixed/enforced review cycles
Earlier quoted context omitted.
Fraud is considered rare, and trust is fundamental. In which case, you choose to believe what they said they did and interrogate of what they said they did is reasonable. Nobody has the budget, time, and sometimes magical fingers required to reproduce every submission. You can disagree with this approach, but then there needs to be huge budgets set aside for reproduction.
Fraud is considered rare, but maybe not actually that rare; hence the replication crisis.
Peer review is a joke. Peer reviewers don’t look at your data and the programs you used to analyze it. They don’t look at your experimental apparatus, they don’t repeat your experiment, they don’t talk to the subjects you interviewed, at best they can spot obvious “red flags”. (Of course, in 2023 you should be able to publish your data and all your software with the paper.)
Earlier quoted context omitted.
Fraud is considered rare, and trust is fundamental. In which case, you choose to believe what they said they did and interrogate of what they said they did is reasonable. Nobody has the budget, time, and sometimes magical fingers required to reproduce every submission. You can disagree with this approach, but then there needs to be huge budgets set aside for reproduction.
Fraud is considered rare, but maybe not actually that rare; hence the replication crisis.
Sadly, integrity offices will rarely conduct serious investigations, and won't conclude misconduct happened unless what was done was incredibly harmful. Professors are often too big to fail, they attract tons of grants and are politically entrenched.
Computer Science's conventions solve these problems (although CS certainly has other problems): * papers are generally posted to arxiv.org immediately on being finished, so everyone can access them * conferences have fixed deadlines and relatively short, fixed/enforced review cycles
Everyone accessing someone's uncritically reviewed work is a bittersweet gift.
The best way to allow multiple submissions while amortizing the review work is to make reviews (and rebuttals) public, and overlay them on submissions made public on some preprint server. This establishes priority (if credit is a concern), can be made blind / double-blind if so desired, and also makes public the reviews (which are as much a public service as writing research papers). Which editorial boards “accept” t…
It is quite well regarded now, they publish excellent research and the whole process is crystal clear.
Peer review is a joke. Peer reviewers don’t look at your data and the programs you used to analyze it. They don’t look at your experimental apparatus, they don’t repeat your experiment, they don’t talk to the subjects you interviewed, at best they can spot obvious “red flags”. (Of course, in 2023 you should be able to publish your data and all your software with the paper.)
- question whether or not the conclusions you are making are supported by the data you are presenting
- ask for additional experiments
- evaluate whether or not your research is sufficiently novel and properly contextualized
- spotting obvious red flags - you seem to discount this, but it's quite valuable
In my experience, the process of peer review has been onerous, sometimes taking years of work and many experiments, and has by and large led to a better end-product. There are not so great aspects of peer review, but it's definitely not a joke as you characterize it.
I'll add that in biology and adjacent fields, it makes no sense to discount peer review because the reviewers do not repeat your experiment - doing so is simply not practical, and you don't have to stretch your imagination very far to understand why.
Peer review is a joke. Peer reviewers don’t look at your data and the programs you used to analyze it. They don’t look at your experimental apparatus, they don’t repeat your experiment, they don’t talk to the subjects you interviewed, at best they can spot obvious “red flags”. (Of course, in 2023 you should be able to publish your data and all your software with the paper.)
I don't if this is how it's done already. I have seen people complaining about peer review here and was wondering why there isn't a solution to that while software already enjoys a well established peer review system.
Computer Science's conventions solve these problems (although CS certainly has other problems): * papers are generally posted to arxiv.org immediately on being finished, so everyone can access them * conferences have fixed deadlines and relatively short, fixed/enforced review cycles
Let's distinguish between papers and preprints, please. arXiv has contributed to a blurring of the distinction. The arXiv preprints are useful but should always be taken with a grain of salt. There is nearly no filtering done on things uploaded to arXiv. Everyone accessing someone's uncritically reviewed work is a bittersweet gift.