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Maybe a future direction would be to train new models to identify plagiarism by training on this information. Use „non matching backtranslations for training cl
by doubtfuluser 5y ago
Maybe a future direction would be to train new models to identify plagiarism by training on this information. Use „non matching backtranslations for training classifiers. It’s again the typical cat and mouse game I guess
- tarboreus 5y agoOr someone could...read the papers.
- wereHamster 5y agoIt's the classical problem of people trying to find technological solutions to social problems. If plagiarism and fake research is still a problem after we've applied technology to fight it, clearly we haven't applied enough of it.
- waterhouse 5y agoSometimes technological solutions work really well to solve social problems. For example, at one point, one person using the internet would tie up the phone line for everyone else in the house, and vice versa. Negotiating this shared resource could be considered a household social problem. But now there's no such interference, and most people have their own cell phones.
- tnzm 5y agoThis is a social problem around the shared use of a technological resource. I'm reminded of the old saying, "computers can only solve problems that are created with computers". But then again you can view _all_ solutions to social problems as inherently technological in the broader sense; I adhere to that paradigm.
- robertlagrant 5y agoThat saying seems silly. Computers (i.e. Zoom) help with the problem of needing socially distanced education during Covid lockdowns.
- pas 5y agoReferees have no real incentive to keep quality high. They already don't get anything in return for doing it. (At best they do it for reciprocity/goodwill.) Papers are usually hard to follow, replication rate is abysmal, etc. The incentives are all set for publishing, not for making real progress.
- PragmaticPulp 5y agoThe number of papers being published is growing at a staggering rate. This requires proportional growth in the number of people reading these papers, which inevitably means the plagiarists and cheaters themselves are being pulled into the review system as well. They don’t care about letting fraudulent papers slip through because they never really cared about the science in the first place. They see it as a game that they’re playing and they’re doing their best to put as little effort as possible into the game while extracting as much reputation upside as they can. We really need to make publishing fraudulent papers a career-ending move across academia and even the industry. The only reason this continues to happen is because it has a lot of upside but very little downside. Caught publishing fraudulent papers? Oh well, just leave them off your resume and apply somewhere else.