3 ms·

Luckily the academic system will typically weed out unethical behaviour (e.g. faking results).

• fock 8y ago
  If you think the current process does, you either are in a very good environment or are plainly lying to yourself. I could just add some bits here and there, get excellent results and publish. Probably nobody will notice as it won't be a "big issue" and seems all fine with existing experimental data.
  • anjc 8y ago
    If you've faked your data to get these results then it could mean the end of your career, hence must be a very uncommon practice. This is a different from cherrypicking data, or putting a positive spin on your findings. But again, it's expected now that data and code are open, so you wont get away with much these days in high-impact conferences/journals.
    • fock 8y ago
      Not talking about high impact journals (where the majority of papers does not end up, when everyone is expected to publish twice a year...). Also I think cherrypicking your ML training data to achieve a certain result is akin to faking results?! And if you think that all data and code are open today you should certainly take a better look around you. Half of our lab is running on proprietary (simulation) software, good luck with auditing the code there (and evaluating the data because most of the people don't really document there workflow...). And both these examples take/took place on upper-mid-tiere european universities which consistently rank in the global upper 100/european upper 20-citation rankings... Besides that, most of the people do a PhD for getting better paid jobs, not academic tenure (where such things could backfire).
  • deleted 8y ago
    [deleted]