Retraction Watch

Tracking retractions as a window into the scientific process

Weekend reads: Idiotic reviews; wrong metrics in China; questions about preprints

with 4 comments

booksThe week at Retraction Watch featured the corrections of papers claiming that conservative beliefs were linked to psychotic traits, and a new member of our leaderboard, from philosophy. Here’s what was happening elsewhere:

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Written by Ivan Oransky

June 11th, 2016 at 9:30 am

Posted in weekend reads

  • Jaime A. Teixeira da Silva June 11, 2016 at 10:31 am

    Some may find this useful (published this week):
    Teixeira da Silva, J.A., Al-Khatib, A. (2016) Questioning the ethics of John Bohannon’s hoaxes and stings in the context of science publishing. KOME 4(1): 84-88.
    DOI: 10.17646/KOME.2016.16

  • lhac June 12, 2016 at 7:38 am

    The article “Why are so many researchers moving to Qatar?” can be recommended as a good example of contemporary Orwellian newspeak. Interesting that two female authors would compile an article that fades out obvious critical questions. Also in the news today: “Dutch woman jailed for reporting her rape in Qatar”.
    If you can read between the lines, you will note that a great things about Qatar is that “Qatar airlines fly everywhere. When we have the opportunity, we just go somewhere; my family loves it…” or “Qatar is a fantastic place to live because it is so central … we can take our kids to Europe, Asia, and Africa to see the world”. So the best thing about the place seems to be that you can easily get away… (unless you’ve already been arrested like the Dutch woman).

  • Bob L. Sturm June 13, 2016 at 9:12 am

    I wonder if you might include in the next weekend reads the upcoming workshop, HORSE 2016 ( A “horse” is a machine learning system promoted as solving a specific problem but that is actually solving an unrelated problem. Poor experimental methodology and unacknowledged assumptions and limitations are to blame. My research has uncovered several published “horses”, but retractions are not typical in my field (machine listening). HORSE 2016 is devoted to discussing “horses”, and promoting superior research methods in applied machine learning. So far, I have contributions from computational creativity, surveillence, finance, and reproducible research efforts. Thank you!

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